Summary
Biology Development
Debian Med packages for development of bioinformatics applications
This metapackage will install Debian packages which might be helpful
for development of applications for biological research.
Description
For a better overview of the project's availability as a Debian package, each head row has a color code according to this scheme:
If you discover a project which looks like a good candidate for Debian Med
to you, or if you have prepared an unofficial Debian package, please do not hesitate to
send a description of that project to the Debian Med mailing list
Links to other tasks
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Debian Med Biology Development packages
Official Debian packages with high relevance
bio-tradis
analyse the output from TraDIS analyses of genomic sequences
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Versions of package bio-tradis |
Release | Version | Architectures |
sid | 1.4.5+dfsg2-2 | all |
bullseye | 1.4.5+dfsg2-1 | all |
buster | 1.4.1+dfsg-1 | all |
stretch-backports | 1.3.3+dfsg-3~bpo9+1 | all |
bookworm | 1.4.5+dfsg2-1 | all |
trixie | 1.4.5+dfsg2-2 | all |
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License: DFSG free
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Bio-Tradis contains a set of tools to analyse the output from
TraDIS analyses.
The Bio-Tradis analysis pipeline is implemented as an extensible Perl
library which can either be used as is, or as a basis for the
development of more advanced analysis tools.
Please note: You need to manually install BioConductor Edger which can
not be distributed by Debian in recent version since it is using
non-distributable code locfit.
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biobambam2
tools for early stage alignment file processing
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Versions of package biobambam2 |
Release | Version | Architectures |
bookworm | 2.0.185+ds-1 | amd64,arm64,i386,ppc64el |
bullseye | 2.0.179+ds-1 | amd64,arm64,i386,ppc64el |
trixie | 2.0.185+ds-2 | amd64,i386,mips64el,ppc64el,riscv64 |
sid | 2.0.185+ds-2 | amd64,i386,mips64el,ppc64el,riscv64 |
upstream | 2.0.185-release-20221211202123 |
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License: DFSG free
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This package contains some tools for processing BAM files, including
bamsormadup: parallel sorting and duplicate marking
bamcollate2: reads BAM and writes BAM reordered such that alignment
or collated by query name
bammarkduplicates: reads BAM and writes BAM with duplicate alignments
marked using the BAM flags field
bammaskflags: reads BAM and writes BAM while masking (removing) bits
from the flags column
bamrecompress: reads BAM and writes BAM with a defined compression
setting. This tool is capable of multi-threading.
bamsort: reads BAM and writes BAM resorted by coordinates or
query name
bamtofastq: reads BAM and writes FastQ; output can be collated
or uncollated by query name
The package is enhanced by the following packages:
multiqc
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bioperl
Perl tools for computational molecular biology
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Versions of package bioperl |
Release | Version | Architectures |
bookworm | 1.7.8-1 | all |
buster | 1.7.2-3 | all |
bullseye | 1.7.7-2 | all |
stretch | 1.7.1-2 | all |
trixie | 1.7.8-1 | all |
sid | 1.7.8-1 | all |
jessie | 1.6.924-1 | all |
Debtags of package bioperl: |
devel | lang:perl, library |
field | biology, biology:bioinformatics |
role | devel-lib, shared-lib |
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License: DFSG free
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The Bioperl project is a coordinated effort to collect computational methods
routinely used in bioinformatics into a set of standard CPAN-style,
well-documented, and freely available Perl modules. It is well-accepted
throughout the community and used in many high-profile projects, e.g.,
Ensembl.
The recommended packages are needed to run some of the included
binaries, for a detailed explanation including the specific Perl
modules please see README.Debian.
The suggested package enhances the manual pages.
Please cite:
Jason E Stajich, David Block, Kris Boulez, Steven E Brenner, Stephen A Chervitz, Chris Dagdigian, Georg Fuellen, James G R Gilbert, Ian Korf, Hilmar Lapp, Heikki Lehvaslaiho, Chad Matsalla, Chris J Mungall, Brian I Osborne, Matthew R Pocock, Peter Schattner, Martin Senger, Lincoln D Stein, Elia Stupka, Mark D Wilkinson and Ewan Birney:
The Bioperl toolkit: Perl modules for the life sciences.
(PubMed,eprint)
Genome Res.
12(10):1611-1618
(2002)
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bioperl-run
BioPerl wrappers: scripts
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Versions of package bioperl-run |
Release | Version | Architectures |
buster | 1.7.2-4 | all |
stretch | 1.7.1-3 | all |
sid | 1.7.3-13 | all |
trixie | 1.7.3-13 | all |
bookworm | 1.7.3-9 | all |
bullseye | 1.7.3-6 | all |
jessie | 1.6.9-2 | all |
Debtags of package bioperl-run: |
field | biology, biology:bioinformatics |
interface | commandline |
role | program |
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License: DFSG free
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Contains scripts from the BioPerl-Run package. This package will also install
all wrappable applications packaged in Debian. The ones that are not Free are
"Suggested" by this package.
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biosquid
utilities for biological sequence analysis
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Versions of package biosquid |
Release | Version | Architectures |
trixie | 1.9g+cvs20050121-15.1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch | 1.9g+cvs20050121-7 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
sid | 1.9g+cvs20050121-15.1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch-backports | 1.9g+cvs20050121-11~bpo9+1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 1.9g+cvs20050121-11 | amd64,arm64,armhf,i386 |
bullseye | 1.9g+cvs20050121-12 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.9g+cvs20050121-12 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
jessie | 1.9g+cvs20050121-4 | amd64,armel,armhf,i386 |
Debtags of package biosquid: |
field | biology, biology:bioinformatics |
interface | commandline |
role | program |
scope | utility |
use | comparing, converting, editing |
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License: DFSG free
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SQUID is a library of C code functions for sequence analysis. It also
includes a number of small utility programs to convert, show statistics,
manipulate and do other functions on sequence files.
The original name of the package is "squid", but since there is already
a squid on the archive (a proxy cache), it was renamed to "biosquid".
This package contains some tools to demonstrate the features of the
SQUID library.
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cwltool
Common Workflow Language reference implementation
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Versions of package cwltool |
Release | Version | Architectures |
bullseye | 3.0.20210124104916-3+deb11u1 | all |
trixie | 3.1.20241112140730-1 | all |
bookworm | 3.1.20230209161050-1 | all |
buster | 1.0.20181217162649+dfsg-10 | all |
stretch | 1.0.20170114120503-1 | all |
sid | 3.1.20241112140730-1 | all |
upstream | 3.1.20241217163858 |
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License: DFSG free
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This is the reference implementation of the Common Workflow Language
standards.
The CWL open standards are for describing analysis workflows and tools in a
way that makes them portable and scalable across a variety of software and
hardware environments, from workstations to cluster, cloud, and high
performance computing (HPC) environments. CWL is designed to meet the needs of
data-intensive science, such as Bioinformatics, Medical Imaging, Astronomy,
Physics, and Chemistry.
The CWL reference implementation (cwltool) is intended to be feature complete
and to provide comprehensive validation of CWL files as well as provide other
tools related to working with CWL descriptions.
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gffread
GFF/GTF format conversions, region filtering, FASTA sequence extraction
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Versions of package gffread |
Release | Version | Architectures |
bullseye | 0.12.1-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 0.12.7-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 0.12.7-8 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 0.12.7-8 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
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License: DFSG free
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Gffread is a GFF/GTF parsing utility providing format conversions,
region filtering, FASTA sequence extraction and more.
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goby-java
next-generation sequencing data and results analysis tool
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Versions of package goby-java |
Release | Version | Architectures |
trixie | 3.3.1+dfsg2-11 | all |
sid | 3.3.1+dfsg2-11 | all |
bookworm | 3.3.1+dfsg2-9 | all |
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License: DFSG free
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Goby is a next-gen data management framework designed to facilitate the
implementation of efficient data analysis pipelines.
Goby provides very efficient file formats to store next-generation sequencing
data and intermediary analysis results.
Goby also provides utilities that implement common next-gen data computations.
These utilities are designed to be relatively easy to use, yet very efficient.
This package provides the entire Goby framework, including application
programs (i.e., Goby modes). It is released under the GPL3 license.
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libace-perl
Object-Oriented Access to ACEDB Databases
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Versions of package libace-perl |
Release | Version | Architectures |
bookworm | 1.92-11 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.92-12 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch | 1.92-4 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
jessie | 1.92-3 | amd64,armel,armhf,i386 |
buster | 1.92-8 | amd64,arm64,armhf,i386 |
bullseye | 1.92-10 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.92-12 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
Debtags of package libace-perl: |
devel | lang:perl, library |
field | biology |
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License: DFSG free
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AcePerl is an object-oriented Perl interface for the AceDB
database. It provides functionality for connecting to remote AceDB
databases, performing queries, fetching ACE objects, and updating
databases. The programmer's API is compatible with the JADE Java API,
and interoperable with the API used by BoulderIO.
AceDB is a genome database system developed since 1989 primarily by
Jean Thierry-Mieg (CNRS, Montpellier) and Richard Durbin (Sanger
Institute). It was originally developed for the C.elegans genome
project , from which its name was derived (A C. elegans DataBase).
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libai-fann-perl
Perl wrapper for the FANN library
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Versions of package libai-fann-perl |
Release | Version | Architectures |
trixie | 0.10-5 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 0.10-5 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 0.10-5 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 0.10-5 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 0.10-4 | amd64,arm64,armhf,i386 |
stretch | 0.10-3 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
jessie | 0.10-2 | amd64,armel,armhf,i386 |
Debtags of package libai-fann-perl: |
devel | lang:perl, library |
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License: DFSG free
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This module provides a Perl wrapper for the Fast Artificial Neural Network
(FANN) library (http://leenissen.dk/fann/wp/).
The AI::FANN object oriented interface provides an almost direct map to the
C library API.
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libbambamc-dev
Development files for reading and writing BAM (genome alignment) files
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Versions of package libbambamc-dev |
Release | Version | Architectures |
bookworm | 0.0.50-6 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 0.0.50-6 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch | 0.0.50-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
jessie | 0.0.50-1 | amd64,armel,armhf,i386 |
buster | 0.0.50-3 | amd64,arm64,armhf,i386 |
trixie | 0.0.50-6 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 0.0.50-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
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License: DFSG free
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The BAM Format is a binary format for storing sequence data. This is a
lightweight C implementation of the read name collation code from the
larger bambam C++ project to handle BAM file input and BAM file output.
This package contains the static library and header files.
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libbamtools-dev
C++ API for manipulating BAM (genome alignment) files
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Versions of package libbamtools-dev |
Release | Version | Architectures |
buster | 2.5.1+dfsg-3 | amd64,arm64,armhf,i386 |
stretch | 2.4.1+dfsg-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
trixie | 2.5.2+dfsg-6 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
jessie | 2.3.0+dfsg-2 | amd64,armel,armhf,i386 |
bookworm | 2.5.2+dfsg-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 2.5.2+dfsg-6 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 2.5.1+dfsg-9 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
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License: DFSG free
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BamTools facilitates research analysis and data management using BAM
files. It copes with the enormous amount of data produced by current
sequencing technologies that is typically stored in compressed, binary
formats that are not easily handled by the text-based parsers commonly
used in bioinformatics research.
BamTools provides both a C++ API for BAM file support as well as a
command-line toolkit.
This is the developers API package.
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libbigwig-dev
C library for handling bigWig files - header files
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Versions of package libbigwig-dev |
Release | Version | Architectures |
bookworm | 0.4.7+dfsg-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 0.4.4+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 0.4.7+dfsg-3.1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 0.4.7+dfsg-3.1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
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License: DFSG free
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This package provides the files needed to develop with the libBigWig
C library for reading/parsing local and remote bigWig and bigBed files.
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libbio-alignio-stockholm-perl
stockholm sequence input/output stream
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Versions of package libbio-alignio-stockholm-perl |
Release | Version | Architectures |
bullseye | 1.7.3-2 | all |
bookworm | 1.7.3-2 | all |
sid | 1.7.3-2 | all |
trixie | 1.7.3-2 | all |
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License: DFSG free
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Indexes Stockholm format alignments such as those from Pfam and Rfam. Returns
raw stream data using the ID or a Bio::SimpleAlign object (via Bio::AlignIO).
Bio::AlignIO::stockholm also allows for ID parsing using a callback:
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libbio-asn1-entrezgene-perl
parser for NCBI Entrez Gene and NCBI Sequence records
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Versions of package libbio-asn1-entrezgene-perl |
Release | Version | Architectures |
stretch | 1.720-1 | all |
bookworm | 1.730-2 | all |
jessie | 1.700-1 | all |
sid | 1.730-3 | all |
trixie | 1.730-3 | all |
bullseye | 1.730-2 | all |
buster | 1.720-2 | all |
Debtags of package libbio-asn1-entrezgene-perl: |
devel | lang:perl |
field | biology |
works-with-format | plaintext |
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License: DFSG free
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Bio::ASN1::EntrezGene and Bio::ASN1::Sequence are regular expression-based
parsers for NCBI Entrez Gene genome databases
(http://www.ncbi.nih.gov/entrez/query.fcgi?db=gene).
They parse ASN.1-formatted Entrez Gene records and NCBI sequences,
returning data structures that contain all data items from the gene records
or the sequence records.
The parser will report error & line number if input data does not conform to
the NCBI Entrez Gene genome or NCBI Sequence annotation file format.
Bio::ASN1::Sequence is basically a modified version of the high-performance
Bio::ASN1::EntrezGene parser. However this standalone module exists since it
is more efficient to keep Sequence-specific code out of EntrezGene.pm.
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libbio-chado-schema-perl
DBIx::Class layer for the Chado database schema
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Versions of package libbio-chado-schema-perl |
Release | Version | Architectures |
jessie | 0.20000-1 | all |
stretch | 0.20000-1 | all |
buster | 0.20000-2 | all |
bullseye | 0.20000-3 | all |
bookworm | 0.20000-3 | all |
trixie | 0.20000-3 | all |
sid | 0.20000-3 | all |
Debtags of package libbio-chado-schema-perl: |
devel | lang:perl, library |
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License: DFSG free
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The module Bio::Chado::Schema is a standard object-relational mapping
layer for use with the GMOD Chado database schema.
Chado is an open-source modular database schema for biological data.
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libbio-cluster-perl
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Versions of package libbio-cluster-perl |
Release | Version | Architectures |
trixie | 1.7.3-6 | all |
sid | 1.7.3-6 | all |
bullseye | 1.7.3-5 | all |
bookworm | 1.7.3-6 | all |
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License: DFSG free
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The ClusterIO module works with the ClusterIO format module to read various
cluster formats such as NCBI UniGene.
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libbio-coordinate-perl
BioPerl modules for working with biological coordinates
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Versions of package libbio-coordinate-perl |
Release | Version | Architectures |
stretch | 1.7.1-1 | all |
bookworm | 1.7.1-4 | all |
bullseye | 1.7.1-4 | all |
buster | 1.7.1-3 | all |
sid | 1.7.1-4 | all |
trixie | 1.7.1-4 | all |
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License: DFSG free
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The Bioperl project is a coordinated effort to collect computational methods
routinely used in bioinformatics into a set of standard CPAN-style,
well-documented, and freely available Perl modules.
Since BioPerl version 1.7 several modules where split into separate projects.
This package provides the Bio::Coordinate module for working with biological
coordinates.
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libbio-das-lite-perl
implementation of the BioDas protocol
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Versions of package libbio-das-lite-perl |
Release | Version | Architectures |
jessie | 2.04-1.1 | all |
stretch | 2.11-5 | all |
buster | 2.11-7 | all |
sid | 2.11-9 | all |
bullseye | 2.11-8 | all |
trixie | 2.11-9 | all |
bookworm | 2.11-8 | all |
Debtags of package libbio-das-lite-perl: |
devel | lang:perl, library |
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License: DFSG free
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Bio::Das::Lite is an implementation of the BioDas protocol
for the retrieval of biological data from XML sources over HTTP.
Bio::Das::Lite is designed as a lightweight and more forgiving alternative to
the client/retrieval/parsing components of Bio::Das. Bio::Das::Lite itself is
not a drop-in replacement for Bio::Das but it can be subclassed to do so.
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libbio-db-biofetch-perl
Database object interface to BioFetch retrieval
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Versions of package libbio-db-biofetch-perl |
Release | Version | Architectures |
sid | 1.7.3-4 | all |
bookworm | 1.7.3-4 | all |
trixie | 1.7.3-4 | all |
bullseye | 1.7.3-4 | all |
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License: DFSG free
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Bio::DB::BioFetch is a guaranteed best effort sequence entry fetching method.
It goes to the Web-based dbfetch server located at the EBI
(http://www.ebi.ac.uk/Tools/dbfetch/dbfetch) to retrieve sequences in the
EMBL or GenBank sequence repositories.
Bio::DB::BioFetch implements all the Bio::DB::RandomAccessI interface, plus
the get_Stream_by_id() and get_Stream_by_acc() methods that are found in the
Bio::DB::SwissProt interface.
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libbio-db-embl-perl
Database object interface for EMBL entry retrieval
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Versions of package libbio-db-embl-perl |
Release | Version | Architectures |
bullseye | 1.7.4-4 | all |
sid | 1.7.4-4 | all |
trixie | 1.7.4-4 | all |
bookworm | 1.7.4-4 | all |
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License: DFSG free
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Allows the dynamic retrieval of sequence objects Bio::Seq from the EMBL
database using the dbfetch script at EBI:
http://www.ebi.ac.uk/Tools/dbfetch/dbfetch.
In order to make changes transparent host type (currently only ebi) and
location (defaults to ebi) were separated out. This allows later additions
of more servers in different geographical locations.
The functionality of this module is inherited from Bio::DB::DBFetch which
implements Bio::DB::WebDBSeqI.
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libbio-db-hts-perl
Perl interface to the HTS library
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Versions of package libbio-db-hts-perl |
Release | Version | Architectures |
bookworm | 3.01-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 3.01-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
trixie | 3.01-5 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 3.01-5 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
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License: DFSG free
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HTSlib is an implementation of a unified C library for accessing common file
formats, such as SAM (Sequence Alignment/Map), CRAM and VCF (Variant Call
Format), used for high-throughput sequencing data, and is the core library
used by samtools and bcftools. HTSlib only depends on zlib. It is known to be
compatible with gcc, g++ and clang.
HTSlib implements a generalized BAM (binary SAM) index, with file extension
'csi' (coordinate-sorted index). The HTSlib file reader first looks for the
new index and then for the old if the new index is absent.
This package provides a Perl interface to the HTS library.
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libbio-db-ncbihelper-perl
collection of routines useful for queries to NCBI databases
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Versions of package libbio-db-ncbihelper-perl |
Release | Version | Architectures |
sid | 1.7.8-1 | all |
bullseye | 1.7.6-4 | all |
bookworm | 1.7.7-1 | all |
trixie | 1.7.8-1 | all |
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License: DFSG free
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Provides a single place to setup some common methods for querying NCBI web
databases. Bio::DB::NCBIHelper just centralizes the methods for constructing
a URL for querying NCBI GenBank and NCBI GenPept and the common HTML
stripping done in postprocess_data().
The base NCBI query URL used is:
https://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi
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libbio-db-seqfeature-perl
Normalized feature for use with Bio::DB::SeqFeature::Store
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Versions of package libbio-db-seqfeature-perl |
Release | Version | Architectures |
trixie | 1.7.5-1 | all |
bullseye | 1.7.4-1 | all |
bookworm | 1.7.4-2 | all |
sid | 1.7.5-1 | all |
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License: DFSG free
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The Bio::DB::SeqFeature object is the default SeqFeature class stored in
Bio::DB::SeqFeature databases. It implements both the
Bio::DB::SeqFeature::NormalizedFeatureI and
Bio::DB::SeqFeature::NormalizedTableFeatureI interfaces, which means that its
subfeatures, if any, are stored in the database in a normalized fashion, and
that the parent/child hierarchy of features and subfeatures are also stored
in the database as set of tuples. This provides efficiencies in both storage
and retrieval speed.
Typically you will not create Bio::DB::SeqFeature directly, but will ask the
database to do so on your behalf, as described in Bio::DB::SeqFeature::Store.
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|
libbio-eutilities-perl
BioPerl interface to the Entrez Programming Utilities (E-utilities)
|
Versions of package libbio-eutilities-perl |
Release | Version | Architectures |
trixie | 1.77-2 | all |
sid | 1.77-2 | all |
bookworm | 1.77-2 | all |
bullseye | 1.77-1 | all |
buster | 1.75-4 | all |
|
License: DFSG free
|
The Bioperl project is a coordinated effort to collect computational
methods routinely used in bioinformatics into a set of standard
CPAN-style, well-documented, and freely available Perl modules. This
package provides a programmatic interface to NCBI's Entrez Programming
Utilities commonly referred to as E-utilities. Namely, it provides the
Bio::DB::EUtilities and Bio::Tools::EUtilities perl modules.
Entrez is a federated search engine at the National Center for
Biotechnology Information (NCBI) for a large number of databases
covering a variety of biomedical data, including nucleotide and
protein sequences, gene records, three-dimensional molecular
structures, and the biomedical literature. E-utilities are a set of
eight server-side programs that provide a stable interface into the
Entrez query and database system at the National Center for
Biotechnology Information (NCBI).
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|
libbio-featureio-perl
Modules for reading, writing, and manipulating sequence features
|
Versions of package libbio-featureio-perl |
Release | Version | Architectures |
bullseye | 1.6.905-2 | all |
sid | 1.6.905-2 | all |
trixie | 1.6.905-2 | all |
bookworm | 1.6.905-2 | all |
|
License: DFSG free
|
An I/O iterator subsystem for genomic sequence features.
Bio::FeatureIO is a handler module for the formats in the FeatureIO set (eg,
Bio::FeatureIO::GFF). It is the officially sanctioned way of getting at the
format objects, which most people should use.
The Bio::FeatureIO system can be thought of like biological file handles.
They are attached to filehandles with smart formatting rules (eg, GFF format,
or BED format) and can either read or write feature objects (Bio::SeqFeature
objects, or more correctly, Bio::FeatureHolderI implementing objects, of
which Bio::SeqFeature is one such object). If you want to know what to do
with a Bio::SeqFeatureI object, read Bio::SeqFeatureI.
The idea is that you request a stream object for a particular format. All the
stream objects have a notion of an internal file that is read from or written
to. A particular FeatureIO object instance is configured for either input or
output. A specific example of a stream object is the Bio::FeatureIO::gff
object.
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libbio-graphics-perl
Generate GD images of Bio::Seq objects
|
Versions of package libbio-graphics-perl |
Release | Version | Architectures |
buster | 2.40-3 | all |
bullseye | 2.40-6 | all |
sid | 2.40-6 | all |
stretch | 2.40-1 | all |
trixie | 2.40-6 | all |
bookworm | 2.40-6 | all |
jessie | 2.39-2 | all |
Debtags of package libbio-graphics-perl: |
devel | lang:perl, library |
field | biology, biology:bioinformatics |
role | shared-lib |
|
License: DFSG free
|
The Bio::Graphics::Panel class provides drawing and formatting
services for any object that implements the Bio::SeqFeatureI
interface, including Ace::Sequence::Feature, Das::Segment::Feature and
Bio::DB::Graphics objects. It can be used to draw sequence
annotations, physical (contig) maps, protein domains, or any other
type of map in which a set of discrete ranges need to be laid out on
the number line.
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libbio-mage-perl
Container module for classes in the MAGE package: MAGE
|
Versions of package libbio-mage-perl |
Release | Version | Architectures |
stretch | 20030502.3-3 | all |
bookworm | 20030502.3-6 | all |
trixie | 20030502.3-6 | all |
buster | 20030502.3-5 | all |
sid | 20030502.3-6 | all |
bullseye | 20030502.3-6 | all |
jessie | 20030502.3-3 | all |
Debtags of package libbio-mage-perl: |
field | biology, biology:bioinformatics |
role | devel-lib |
|
License: DFSG free
|
MAGE-TAB (MicroArray Gene Expression Tabular) format is a standard from the
Microarray Gene Expression Data Society (MGED). This package contains Perl
modules in the Bio::MAGE hierarchy to manipulate MIAME-compliant (Minimum
Information About a Microarray Experiment) records of microarray ("DNA chips")
experiments.
The Bio::MAGE module contains the following Bio::MAGE classes:
- NameValueType
- Extendable
- Identifiable
- Describable
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libbio-mage-utils-perl
Extra modules for classes in the MAGE package: MAGE
|
Versions of package libbio-mage-utils-perl |
Release | Version | Architectures |
bookworm | 20030502.0-5 | all |
sid | 20030502.0-5 | all |
jessie | 20030502.0-2 | all |
stretch | 20030502.0-2 | all |
bullseye | 20030502.0-5 | all |
buster | 20030502.0-4 | all |
trixie | 20030502.0-5 | all |
Debtags of package libbio-mage-utils-perl: |
field | biology, biology:bioinformatics |
|
License: DFSG free
|
MAGE-TAB (MicroArray Gene Expression Tabular) format is a standard from the
Microarray Gene Expression Data Society (MGED). This package contains Perl
modules in the Bio::MAGE hierarchy to manipulate MIAME-compliant (Minimum
Information About a Microarray Experiment) records of microarray ("DNA chips")
experiments.
Bio-MAGE-Utils contains extra modules for handling MAGE XML and MGED ontology,
as well as SQL utilities.
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|
libbio-primerdesigner-perl
Perl module to design PCR primers using primer3 and epcr
|
Versions of package libbio-primerdesigner-perl |
Release | Version | Architectures |
trixie | 0.07-8 | all |
sid | 0.07-8 | all |
bookworm | 0.07-8 | all |
bullseye | 0.07-8 | all |
buster | 0.07-6 | all |
stretch | 0.07-5 | all |
jessie | 0.07-3 | all |
Debtags of package libbio-primerdesigner-perl: |
devel | lang:perl, library |
role | shared-lib |
|
License: DFSG free
|
Bio::PrimerDesigner provides a low-level interface to the primer3 and epcr
binary executables and supplies methods to return the results. In addition to
accessing local installations of primer3 or e-PCR, it also offers the ability
to accessing the primer3 binary via a remote server.
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|
libbio-samtools-perl
Perl interface to SamTools library for DNA sequencing
|
Versions of package libbio-samtools-perl |
Release | Version | Architectures |
buster | 1.43-2 | amd64,arm64,armhf,i386 |
sid | 1.43-5 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
jessie | 1.39-1 | amd64,armel,armhf,i386 |
trixie | 1.43-5 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 1.43-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 1.43-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
stretch | 1.43-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
Debtags of package libbio-samtools-perl: |
devel | lang:perl, library |
role | shared-lib |
|
License: DFSG free
|
Bio::SamTools provides a Perl interface to the libbam library for indexed and
unindexed SAM/BAM sequence alignment databases. It provides support for
retrieving information on individual alignments, read pairs, and alignment
coverage information across large regions. It also provides callback
functionality for calling SNPs and performing other base-by-base functions.
Most operations are compatible with the BioPerl Bio::SeqFeatureI interface,
allowing BAM files to be used as a backend to the GBrowse genome browser
application.
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libbio-scf-perl
Perl extension for reading and writing SCF sequence files
|
Versions of package libbio-scf-perl |
Release | Version | Architectures |
bookworm | 1.03-6 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
jessie | 1.03-2 | amd64,armel,armhf,i386 |
stretch | 1.03-3 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
trixie | 1.03-7 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 1.03-7 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.03-5 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 1.03-4 | amd64,arm64,armhf,i386 |
Debtags of package libbio-scf-perl: |
devel | lang:perl, library |
role | shared-lib |
|
License: DFSG free
|
The Bio::SCF (Standard Chromatogram Format) module allows you to read and
update (in a restricted way) SCF chromatographic sequence files. It is an
interface to Roger Staden's io-lib. It has both tied hash and an
object-oriented interfaces. It provides the ability to read fields from SCF
files and limited ability to modify them and write them back.
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libbio-tools-phylo-paml-perl
Bioperl interface to the PAML suite
|
Versions of package libbio-tools-phylo-paml-perl |
Release | Version | Architectures |
bullseye | 1.7.3-3 | all |
buster | 1.7.3-2 | all |
bookworm | 1.7.3-4 | all |
trixie | 1.7.3-4 | all |
sid | 1.7.3-4 | all |
|
License: DFSG free
|
This distribution provides a Perl interface to PAML, a suite of
programs (baseml, codeml, evolver, and yn00) for phylogenetic
analyses of DNA or protein sequences using maximum likelihood.
The Bio::Tools::Run::Phylo::PAML::* modules provide an interface to
run the PAML programs while Bio::Tools::Phylo::PAML provides an
interface to parse their output files.
This distribution is part of the Bioperl project.
|
|
libbio-tools-run-alignment-clustalw-perl
Bioperl interface to Clustal W
|
Versions of package libbio-tools-run-alignment-clustalw-perl |
Release | Version | Architectures |
bookworm | 1.7.4-3 | all |
sid | 1.7.4-4 | all |
bullseye | 1.7.4-2 | all |
buster | 1.7.4-1 | all |
trixie | 1.7.4-4 | all |
|
License: DFSG free
|
Bio::Tools::Run::Alignment::Clustalw provides a Perl interface to
Clustal W, a program for alignment of multiple nucleotide and peptide
sequences.
This module distribution is part of the Bioperl project.
|
|
libbio-tools-run-alignment-tcoffee-perl
Bioperl interface to T-Coffee
|
Versions of package libbio-tools-run-alignment-tcoffee-perl |
Release | Version | Architectures |
bookworm | 1.7.4-3 | all |
sid | 1.7.4-3 | all |
buster | 1.7.4-1 | all |
bullseye | 1.7.4-2 | all |
|
License: DFSG free
|
Bio::Tools::Run::Alignment::TCoffee provides a Perl interface to
T-Coffee, a program for multiple alignments of DNA, RNA, and protein
sequences and structures.
This module distribution is part of the Bioperl project.
|
|
libbio-tools-run-remoteblast-perl
Object for remote execution of the NCBI Blast via HTTP
|
Versions of package libbio-tools-run-remoteblast-perl |
Release | Version | Architectures |
bookworm | 1.7.3-3 | all |
sid | 1.7.3-3 | all |
trixie | 1.7.3-3 | all |
bullseye | 1.7.3-3 | all |
|
License: DFSG free
|
Class for remote execution of the NCBI Blast via HTTP.
For a description of the many CGI parameters see:
https://www.ncbi.nlm.nih.gov/BLAST/Doc/urlapi.html
Various additional options and input formats are available.
|
|
libbio-variation-perl
BioPerl variation-related functionality
|
Versions of package libbio-variation-perl |
Release | Version | Architectures |
sid | 1.7.5-3 | all |
bullseye | 1.7.5-2 | all |
bookworm | 1.7.5-3 | all |
trixie | 1.7.5-3 | all |
|
License: DFSG free
|
The code in this distribution focuses on simple low-dependency variant-related
functionality for BioPerl.
Bio::Variation name space contains modules to store sequence variation
information as differences between the reference sequence and changes
sequences. Also included are classes to write out and recrete objects
from EMBL-like flat files and XML. Lastly, there are simple classes to
calculate values for sequence change objects.
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|
libbiojava-java
Java API to biological data and applications (default version)
|
Versions of package libbiojava-java |
Release | Version | Architectures |
stretch | 1.7.1-5 | all |
buster | 1.7.1-8 | all |
bullseye | 1.7.1-9 | all |
trixie | 1.9.7+dfsg-2 | all |
sid | 1.9.7+dfsg-2 | all |
bookworm | 1.9.5+dfsg-3 | all |
jessie | 1.7.1-5 | all |
Debtags of package libbiojava-java: |
devel | lang:java, library |
field | biology, biology:bioinformatics |
role | devel-lib |
|
License: DFSG free
|
BioJava is an open-source project dedicated to providing a Java framework
for processing biological data. It includes objects for manipulating
sequences, file parsers, DAS client and server support, access to BioSQL
and Ensembl databases, and powerful analysis and statistical routines
including a dynamic programming toolkit.
BioJava is provided by a vibrant community which meets annually at
the Bioinformatics Open Source Conference (BOSC) that traditionally
accompanies the Intelligent Systems in Molecular Biology (ISMB)
meeting. Much like BioPerl, the employment of this library is valuable
for everybody active in the field because of the many tricks of the
trade one learns just by communicating on the mailing list.
This is a dependency package which should enable smooth upgrades to new
versions.
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|
libbiojava6-java
Java API to biological data and applications (version 6)
|
Versions of package libbiojava6-java |
Release | Version | Architectures |
trixie | 6.1.0+dfsg-5 | all |
sid | 6.1.0+dfsg-5 | all |
bookworm | 6.1.0+dfsg-4 | all |
|
License: DFSG free
|
This package presents the Open Source Java API to biological databases
and a series of mostly sequence-based algorithms.
BioJava is an open-source project dedicated to providing a Java framework
for processing biological data. It includes objects for manipulating
sequences, file parsers, server support, access to BioSQL
and Ensembl databases, and powerful analysis and statistical routines
including a dynamic programming toolkit.
|
|
libbioparser-dev
library for parsing several formats in bioinformatics
|
Versions of package libbioparser-dev |
Release | Version | Architectures |
stretch-backports-sloppy | 2.0.1-1~bpo9+1 | all |
bullseye | 3.0.12-1 | all |
sid | 3.1.0-1 | all |
trixie | 3.1.0-1 | all |
stretch-backports | 1.2.0-2~bpo9+1 | all |
buster | 1.2.1-1 | all |
bookworm | 3.0.15-3 | all |
|
License: DFSG free
|
Bioparser is a c++ implementation of parsers for several bioinformatics
formats. It consists of only one header file containing template parsers
for FASTA, FASTQ, MHAP, PAF and SAM format. It also supports compressed
files with gzip.
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|
libblasr-dev
tools for aligning PacBio reads to target sequences (development files)
|
Versions of package libblasr-dev |
Release | Version | Architectures |
buster | 5.3.1+dfsg-2.1 | amd64,arm64 |
trixie | 5.3.5+dfsg-8 | amd64,arm64,mips64el,ppc64el,riscv64 |
stretch | 0~20161219-1 | amd64,arm64,mips64el,ppc64el |
sid | 5.3.5+dfsg-9 | amd64,arm64,mips64el,ppc64el,riscv64 |
bullseye | 5.3.4+dfsg-3 | amd64,arm64,mips64el,ppc64el |
bookworm | 5.3.5+dfsg-4 | amd64,arm64,mips64el,ppc64el |
|
License: DFSG free
|
Blasr_libcpp is a library used by blasr and other executables such as
samtoh5, loadPulses for analyzing PacBio sequences. This library contains
three sub-libraries, including pbdata, hdf and alignment.
This package contains the header files and static library for the alignment
sublibrary.
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|
libbpp-core-dev
Bio++ Core library development files
|
Versions of package libbpp-core-dev |
Release | Version | Architectures |
buster | 2.4.1-3 | amd64,arm64,armhf,i386 |
trixie | 2.4.1-13 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch | 2.2.0-3 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
sid | 2.4.1-13 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
jessie | 2.1.0-1 | amd64,armel,armhf,i386 |
bullseye | 2.4.1-5 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 2.4.1-9 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
Debtags of package libbpp-core-dev: |
devel | library |
role | devel-lib |
|
License: DFSG free
|
Bio++ is a set of C++ libraries for Bioinformatics, including sequence
analysis, phylogenetics, molecular evolution and population genetics.
Bio++ is Object Oriented and is designed to be both easy to use and
computer efficient. Bio++ intends to help programmers to write computer
expensive programs, by providing them a set of re-usable tools.
This package contains the static library and the header files of the
Bio++ core classes.
|
|
libbpp-phyl-dev
Bio++ Phylogenetic library development files
|
Versions of package libbpp-phyl-dev |
Release | Version | Architectures |
bullseye | 2.4.1-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 2.4.1-11 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 2.4.1-8 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 2.4.1-11 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster | 2.4.1-2 | amd64,arm64,armhf,i386 |
stretch | 2.2.0-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
jessie | 2.1.0-1 | amd64,armel,armhf,i386 |
Debtags of package libbpp-phyl-dev: |
devel | library |
role | devel-lib |
|
License: DFSG free
|
Bio++ is a set of C++ libraries for Bioinformatics, including sequence
analysis, phylogenetics, molecular evolution and population genetics.
Bio++ is Object Oriented and is designed to be both easy to use and
computer efficient. Bio++ intends to help programmers to write computer
expensive programs, by providing them a set of re-usable tools.
This package contains the static library and the header files of the
Bio++ classes for phylogenetics.
|
|
libbpp-phyl-omics-dev
Bio++ Phylogenetics library: genomics components (development files)
|
Versions of package libbpp-phyl-omics-dev |
Release | Version | Architectures |
buster | 2.4.1-1 | amd64,arm64,armhf,i386 |
sid | 2.4.1-7 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 2.4.1-7 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 2.4.1-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 2.4.1-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
jessie | 2.1.0-1 | amd64,armel,armhf,i386 |
stretch | 2.2.0-2 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
Debtags of package libbpp-phyl-omics-dev: |
devel | library |
role | devel-lib |
|
License: DFSG free
|
Bio++ is a set of C++ libraries for Bioinformatics, including sequence
analysis, phylogenetics, molecular evolution and population genetics.
Bio++ is Object Oriented and is designed to be both easy to use and
computer efficient. Bio++ intends to help programmers to write computer
expensive programs, by providing them a set of re-usable tools.
This package contains the static library and the header files of the
Bio++ classes dedicated to genomic phylogeny.
|
|
libbpp-popgen-dev
Bio++ Population Genetics library development files
|
Versions of package libbpp-popgen-dev |
Release | Version | Architectures |
bookworm | 2.4.1-8 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 2.4.1-11 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
jessie | 2.1.0-1 | amd64,armel,armhf,i386 |
stretch | 2.2.0-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 2.4.1-1 | amd64,arm64,armhf,i386 |
bullseye | 2.4.1-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 2.4.1-11 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
Debtags of package libbpp-popgen-dev: |
devel | library |
role | devel-lib |
|
License: DFSG free
|
Bio++ is a set of C++ libraries for Bioinformatics, including sequence
analysis, phylogenetics, molecular evolution and population genetics.
Bio++ is Object Oriented and is designed to be both easy to use and
computer efficient. Bio++ intends to help programmers to write computer
expensive programs, by providing them a set of re-usable tools.
This package contains the static library and the header files of the
Bio++ Population Genetics classes.
|
|
libbpp-qt-dev
Bio++ Qt Graphic classes library development files
|
Versions of package libbpp-qt-dev |
Release | Version | Architectures |
bullseye | 2.4.1-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 2.4.1-12 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 2.4.1-8 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
jessie | 2.1.0-1 | amd64,armel,armhf,i386 |
stretch | 2.2.0-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 2.4.1-1 | amd64,arm64,armhf,i386 |
trixie | 2.4.1-12 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
Debtags of package libbpp-qt-dev: |
devel | library |
role | devel-lib |
uitoolkit | qt |
|
License: DFSG free
|
Bio++ is a set of C++ libraries for Bioinformatics, including sequence
analysis, phylogenetics, molecular evolution and population genetics.
Bio++ is Object Oriented and is designed to be both easy to use and
computer efficient. Bio++ intends to help programmers to write computer
expensive programs, by providing them a set of re-usable tools.
Contains development files of the Bio++ graphical classes developed
with Qt.
|
|
libbpp-raa-dev
Bio++ Remote Acnuc Access library development files
|
Versions of package libbpp-raa-dev |
Release | Version | Architectures |
sid | 2.4.1-9 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster | 2.4.1-1 | amd64,arm64,armhf,i386 |
bookworm | 2.4.1-7 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
jessie | 2.1.0-1 | amd64,armel,armhf,i386 |
bullseye | 2.4.1-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
stretch | 2.2.0-2 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
trixie | 2.4.1-9 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
Debtags of package libbpp-raa-dev: |
devel | library |
role | devel-lib |
|
License: DFSG free
|
This library contains utilitary and classes to query public databases
(GenBank, EMBL, SwissProt, etc) using acnuc.
It is part of the Bio++ project.
This package contains header files and static library.
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libbpp-seq-dev
Bio++ Sequence library development files
|
Versions of package libbpp-seq-dev |
Release | Version | Architectures |
bullseye | 2.4.1-5 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
jessie | 2.1.0-1 | amd64,armel,armhf,i386 |
buster | 2.4.1-3 | amd64,arm64,armhf,i386 |
stretch | 2.2.0-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
sid | 2.4.1-13 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 2.4.1-13 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 2.4.1-9 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
Debtags of package libbpp-seq-dev: |
devel | library |
role | devel-lib |
|
License: DFSG free
|
Bio++ is a set of C++ libraries for Bioinformatics, including sequence
analysis, phylogenetics, molecular evolution and population genetics.
Bio++ is Object Oriented and is designed to be both easy to use and
computer efficient. Bio++ intends to help programmers to write computer
expensive programs, by providing them a set of re-usable tools.
This package contains the static library and the header files of Bio++
classes for sequence analysis classes.
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libbpp-seq-omics-dev
Bio++ Sequence library: genomics components (development files)
|
Versions of package libbpp-seq-omics-dev |
Release | Version | Architectures |
stretch | 2.2.0-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
bookworm | 2.4.1-9 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 2.4.1-12 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 2.4.1-12 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
jessie | 2.1.0-1 | amd64,armel,armhf,i386 |
buster | 2.4.1-3 | amd64,arm64,armhf,i386 |
bullseye | 2.4.1-5 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
Debtags of package libbpp-seq-omics-dev: |
devel | library |
role | devel-lib |
|
License: DFSG free
|
Bio++ is a set of C++ libraries for Bioinformatics, including sequence
analysis, phylogenetics, molecular evolution and population genetics.
Bio++ is Object Oriented and is designed to be both easy to use and
computer efficient. Bio++ intends to help programmers to write computer
expensive programs, by providing them a set of re-usable tools.
This package contains the static library and the header files of the
Bio++ classes dedicated to genomic sequencing.
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|
libcdk-java
Chemistry Development Kit (CDK) Java libraries
|
Versions of package libcdk-java |
Release | Version | Architectures |
stretch | 1.2.10-6 | all |
bookworm | 2.8-2 | all |
trixie | 2.9-2 | all |
sid | 2.9-2 | all |
buster | 1.2.10-7 | all |
jessie | 1.2.10-6 | all |
bullseye | 2.3.134.g1bb9a64587-2 | all |
Debtags of package libcdk-java: |
devel | lang:java, library |
field | chemistry |
role | devel-lib |
|
License: DFSG free
|
The CDK is a library of Java classes used in computational and
information chemistry and in bioinformatics. It includes renderers,
file IO, SMILES generation/parsing, maximal common substructure
algorithms, fingerprinting and much, much more.
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|
libchado-perl
database schema and tools for genomic data
|
Versions of package libchado-perl |
Release | Version | Architectures |
sid | 1.31-6 | all |
trixie | 1.31-6 | all |
bullseye | 1.31-6 | all |
buster | 1.31-5 | all |
stretch | 1.31-3 | all |
jessie | 1.23-2 | all |
bookworm | 1.31-6 | all |
Debtags of package libchado-perl: |
devel | lang:perl, library |
|
License: DFSG free
|
Chado is a relational database schema that underlies many GMOD
installations. It is capable of representing many of the general
classes of data frequently encountered in modern biology such as
sequence, sequence comparisons, phenotypes, genotypes, ontologies,
publications, and phylogeny. It has been designed to handle complex
representations of biological knowledge and should be considered one
of the most sophisticated relational schemas currently available in
molecular biology. The price of this capability is that the new user
must spend some time becoming familiar with its fundamentals.
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libcifpp-dev
??? missing short description for package libcifpp-dev :-(
|
Versions of package libcifpp-dev |
Release | Version | Architectures |
bookworm | 5.0.7.1-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 1.0.1-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 7.0.7-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 7.0.7-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
upstream | 7.0.8 |
|
License: DFSG free
|
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libconsensuscore-dev
algorithms for PacBio multiple sequence consensus -- development files
|
Versions of package libconsensuscore-dev |
Release | Version | Architectures |
buster | 1.1.1+dfsg-1 | amd64,i386 |
stretch | 1.0.2-2 | amd64,i386 |
sid | 1.1.1+dfsg-7 | amd64,arm64,i386,mips64el,ppc64el,riscv64 |
trixie | 1.1.1+dfsg-7 | amd64,arm64,i386,mips64el,ppc64el,riscv64 |
bookworm | 1.1.1+dfsg-4 | amd64,i386 |
bullseye | 1.1.1+dfsg-2 | amd64,i386 |
|
License: DFSG free
|
ConsensusCore is a library of C++ algorithms for Pacific Biosciences
multiple sequence consensus that powers Quiver (Python) and ConsensusTools
(.NET). This library primarily exists as the backend for GenomicConsensus,
which implements Quiver.
This package is part of the SMRT Analysis suite.
It provides the header files and static library.
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libdivsufsort-dev
libdivsufsort header files
|
Versions of package libdivsufsort-dev |
Release | Version | Architectures |
sid | 2.0.1-6 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch | 2.0.1-2 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 2.0.1-4 | amd64,arm64,armhf,i386 |
bullseye | 2.0.1-5 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 2.0.1-5 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 2.0.1-6 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
|
License: DFSG free
|
The libdivsufsort project provides a fast, lightweight, and robust
C API library to construct the suffix array and the Burrows-Wheeler
transformed string for any input string of a constant-size alphabet.
This package installs files needed for development.
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libedlib-dev
library for sequence alignment using edit distance (devel)
|
Versions of package libedlib-dev |
Release | Version | Architectures |
trixie | 1.2.7-6 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 1.2.7-6 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.2.6-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.2.7-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
stretch-backports | 1.2.3-3~bpo9+1 | amd64,i386,mips,mips64el,mipsel |
buster | 1.2.4-1 | amd64,arm64,armhf,i386 |
|
License: DFSG free
|
A lightweight and super fast C/C++ library for sequence alignment using
edit distance.
Calculating edit distance of two strings is as simple as:
edlibAlign("hello", 5, "world!", 6,
edlibDefaultAlignConfig()).editDistance;
Features
- Calculates edit distance (Levehnstein distance).
- It can find optimal alignment path (instructions how to transform
first sequence into the second sequence).
- It can find just the start and/or end locations of alignment path -
can be useful when speed is more important than having exact
alignment path.
- Supports multiple alignment methods: global(NW), prefix(SHW) and
infix(HW), each of them useful for different scenarios.
- You can extend character equality definition, enabling you to e.g.
have wildcard characters, to have case insensitive alignment or to
work with degenerate nucleotides.
- It can easily handle small or very large sequences, even when finding
alignment path, while consuming very little memory.
- Super fast thanks to Myers's bit-vector algorithm.
This package contains the static library and the header files.
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|
libfast5-dev
library for reading Oxford Nanopore Fast5 files -- headers
|
Versions of package libfast5-dev |
Release | Version | Architectures |
stretch | 0.5.8-1 | all |
sid | 0.6.5-8 | all |
bullseye | 0.6.5-4 | all |
bookworm | 0.6.5-7 | all |
buster | 0.6.5-2 | all |
trixie | 0.6.5-8 | all |
stretch-backports | 0.6.5-1~bpo9+1 | all |
|
License: DFSG free
|
A lightweight C++11 library to read raw signal data from Oxford
Nanopore's FAST5 files.
This package provides the header files for development with fast5.
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libfastahack-dev
library for indexing and sequence extraction from FASTA files (devel)
|
Versions of package libfastahack-dev |
Release | Version | Architectures |
bullseye | 1.0.0+dfsg-7 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.0.0+dfsg-11 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 1.0.0+dfsg-11 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch | 0.0+20160702-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el |
buster | 0.0+git20160702.bbc645f+dfsg-6 | amd64,arm64,armhf,i386 |
bookworm | 1.0.0+dfsg-10 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
|
License: DFSG free
|
fastahack is a small application for indexing and extracting sequences and
subsequences from FASTA files. The included Fasta.cpp library provides a FASTA
reader and indexer that can be embedded into applications which would benefit
from directly reading subsequences from FASTA files. The library automatically
handles index file generation and use.
Features:
- FASTA index (.fai) generation for FASTA files
- Sequence extraction
- Subsequence extraction
- Sequence statistics (currently only entropy is provided)
Sequence and subsequence extraction use fseek64 to provide fastest-possible
extraction without RAM-intensive file loading operations. This makes fastahack
a useful tool for bioinformaticists who need to quickly extract many
subsequences from a reference FASTA sequence.
This is the development package containing the statically linked
library and the header files.
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libffindex0-dev
library for simple index/database for huge amounts of small files (development)
|
Versions of package libffindex0-dev |
Release | Version | Architectures |
sid | 0.9.9.9-7 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 0.9.9.9-7 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 0.9.9.9-6 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 0.9.9.9-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 0.9.9.9-2 | amd64,arm64,armhf,i386 |
stretch | 0.9.9.7-3 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
jessie | 0.9.9.3-2 | amd64,armel,armhf,i386 |
Debtags of package libffindex0-dev: |
devel | library |
role | devel-lib |
|
License: DFSG free
|
FFindex is a very simple index/database for huge amounts of small files. The
files are stored concatenated in one big data file, separated by '\0'. A
second file contains a plain text index, giving name, offset and length of
the small files. The lookup is currently done with a binary search on an
array made from the index file.
This package contains the header files and documentation needed to develop
applications with libffindex.
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libfml-dev
development headers for libfml
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Versions of package libfml-dev |
Release | Version | Architectures |
stretch | 0.1-2 | amd64 |
bullseye | 0.1+git20190320.b499514-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 0.1+git20221215.85f159e-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 0.1+git20221215.85f159e-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 0.1+git20190320.b499514-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 0.1-5 | amd64 |
stretch-backports | 0.1-4~bpo9+1 | amd64 |
|
License: DFSG free
|
Fermi-lite is a standalone C library tool for assembling Illumina short
reads in regions from 100bp to 10 million bp in size.
This package contains the C library headers for using libfml in custom tools,
along with a static library.
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libgatbcore-dev
development library of the Genome Analysis Toolbox
|
Versions of package libgatbcore-dev |
Release | Version | Architectures |
trixie | 1.4.2+dfsg-13 | amd64,arm64,mips64el,ppc64el,riscv64 |
buster | 1.4.1+git20181225.44d5a44+dfsg-3 | amd64,arm64,i386 |
bullseye | 1.4.2+dfsg-6 | amd64,arm64,i386,mips64el,ppc64el,s390x |
bookworm | 1.4.2+dfsg-11 | amd64,arm64,mips64el,ppc64el |
sid | 1.4.2+dfsg-13 | amd64,arm64,mips64el,ppc64el,riscv64 |
|
License: DFSG free
|
The GATB-CORE project provides a set of highly efficient
algorithms to analyse NGS data sets. These methods enable
the analysis of data sets of any size on multi-core desktop
computers, including very huge amount of reads data coming
from any kind of organisms such as bacteria, plants,
animals and even complex samples (e.g. metagenomes).
Read more about GATB at https://gatb.inria.fr/.
By itself GATB-CORE is not an NGS data analysis tool.
However, it can be used to create such tools. There already
exist a set of ready-to-use tools relying on GATB-CORE
library: see https://gatb.inria.fr/software/
This package contains the static library and the header files
of the gatb-core library.
Please cite:
Erwan Drezen, Guillaume Rizk, Rayan Chikhi, Charles Deltel, Claire Lemaitre, Pierre Peterlongo and Dominique Lavenier:
GATB: Genome Assembly & Analysis Tool Box.
Bioinformatics
30(20):2959-2961
(2014)
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libgclib-dev
header files for Genome Code Lib (GCLib)
|
Versions of package libgclib-dev |
Release | Version | Architectures |
bookworm | 0.12.7+ds-5 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 0.12.7+ds-5 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 0.11.10+ds-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 0.12.7+ds-5 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
|
License: DFSG free
|
This is an eclectic gathering of (mostly) C++ code which upstream used
for some bioinformatics projects. The main idea is to provide
lean code and efficient data structures, trying to avoid too many code
dependencies of heavy libraries while minimizing production cycles (and
this also implies a decent compile/build time -- looking at you,
bloated configure scripts and lengthy compile times of Boost code or
other heavy C++ template code..).
This code was gathered even before the C++ STL had been fully adopted as
a cross-platform "standard". Since STL by itself is a bit heavier for
most of the C++ needs, it is preferred to use simpler&leaner C++ classes
or templates for basic strings, containers, basic algorithms etc.
Header files of Genome Code Lib. It is mainly known for being
used by StringTie but with its own release cycle.
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libgenome-dev
toolkit for developing bioinformatic related software (devel)
|
Versions of package libgenome-dev |
Release | Version | Architectures |
bullseye | 1.3.11+svn20110227.4616-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.3.11+svn20110227.4616-6 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 1.3.11+svn20110227.4616-6 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster | 1.3.11+svn20110227.4616-2 | amd64,arm64,armhf,i386 |
bookworm | 1.3.11+svn20110227.4616-5 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
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License: DFSG free
|
libGenome is a freely available toolkit for developing bioinformatic related
software in C++. It is intended to take the hassle out of performing common
tasks on genetic sequence and annotation data.
Among other things, libGenome can help you:
- Read and write Multi-FastA format files
- Read and write GenBank flat file database entries
- Append, chop, truncate, reverse, complement, translate, and otherwise
mangle sequence data
- Access annotation in GenBank flat files
This is the development package containing the statically linked
library and the header files.
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libgenome-model-tools-music-perl
module for finding mutations of significance in cancer
|
Versions of package libgenome-model-tools-music-perl |
Release | Version | Architectures |
bookworm | 0.04-5 | all |
buster | 0.04-4 | all |
stretch | 0.04-3 | all |
jessie | 0.04-1 | all |
sid | 0.04-5 | all |
trixie | 0.04-5 | all |
bullseye | 0.04-5 | all |
Debtags of package libgenome-model-tools-music-perl: |
devel | lang:perl, library |
|
License: DFSG free
|
The MuSiC suite is a set of tools aimed at discovering the significance of
somatic mutations found within a given cohort of cancer samples, and with
respect to a variety of external data sources.
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libgenome-perl
pipelines, tools, and data management for genomics
|
Versions of package libgenome-perl |
Release | Version | Architectures |
jessie | 0.06-1 | all |
trixie | 0.06-7 | all |
bookworm | 0.06-7 | all |
buster | 0.06-5 | all |
stretch | 0.06-3 | all |
sid | 0.06-7 | all |
bullseye | 0.06-6 | all |
Debtags of package libgenome-perl: |
devel | lang:perl, library |
|
License: DFSG free
|
This is the base namespace module for the Genome software tree.
That tree has several primary components:
Genome::Model: a data modeling pipeline management system for genomics
Genome::Model::Tools a tree of >1000 tools and tool wrappers for genomics
Genome::* a variety of sample tracking classes with an RDBMS back-end
Only the tools system is currently released.
See genome for a complete inventory of all tool packages, and for
command-line access to those tools.
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libgenometools0-dev
development files for GenomeTools
|
Versions of package libgenometools0-dev |
Release | Version | Architectures |
trixie | 1.6.5+ds-2.2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
jessie | 1.5.3-2 | amd64,armel,armhf,i386 |
stretch | 1.5.9+ds-4 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 1.5.10+ds-3 | amd64,arm64,armhf,i386 |
buster-backports | 1.6.1+ds-3~bpo10+1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
bullseye | 1.6.1+ds-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.6.2+ds-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye-backports-sloppy | 1.6.5+ds-2~bpo11+1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm-backports | 1.6.5+ds-2~bpo12+1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.6.5+ds-2.2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
Debtags of package libgenometools0-dev: |
devel | library |
role | devel-lib |
|
License: DFSG free
|
This package contains the GenomeTools static library and necessary
header files.
Besides basic bioinformatics data structures, the library contains components
for sequence and annotation handling, sequence compression, index structure
generation and access, efficient matching, annotation visualization and much
more.
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libgff-dev
GFF/GTF parsing from cufflinks as a library
|
Versions of package libgff-dev |
Release | Version | Architectures |
trixie | 2.0.0-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 2.0.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 1.0-2 | amd64,arm64,armhf,i386 |
stretch | 1.0-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
sid | 2.0.0-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 2.0.0-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
|
License: DFSG free
|
This is a simple "libraryfication" of the GFF/GTF parsing code that is used in
the Cufflinks codebase. There are not many (any?) relatively lightweight
GTF/GFF parsers exposing a C++ interface, and the goal of this library is to
provide this functionality without the necessity of drawing in a heavy-weight
dependency like SeqAn.
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libgkarrays-dev
library to query large collection of NGS sequences (development)
|
Versions of package libgkarrays-dev |
Release | Version | Architectures |
trixie | 2.1.0+dfsg-4.2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 2.1.0+dfsg-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
stretch | 2.1.0+dfsg-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 2.1.0+dfsg-2 | amd64,arm64,armhf,i386 |
sid | 2.1.0+dfsg-4.2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 2.1.0+dfsg-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
|
License: DFSG free
|
Gk-arrays are provided as a simple-to-use C++ library dedicated to
queries on large collection of sequences as produced by high-throughput
sequencers (e.g. HiSeq 2000 from Illumina, 454 from Roche).
Gk-arrays index k-mers of reads and allows one to answer different queries
on that read collection (e.g. how many reads share this k-mer? where does
this k-mer occur in the read collection?).
Gk-arrays consist of a space-efficient alternative to hash tables while
being similar in terms of query times.
This is the development library for libgkarrays.
|
|
libgo-perl
perl modules for GO and other OBO ontologies
|
Versions of package libgo-perl |
Release | Version | Architectures |
bookworm | 0.15-9 | all |
jessie | 0.15-1 | all |
stretch | 0.15-5 | all |
sid | 0.15-10 | all |
buster | 0.15-7 | all |
bullseye | 0.15-9 | all |
trixie | 0.15-10 | all |
Debtags of package libgo-perl: |
field | biology, biology:bioinformatics |
interface | commandline |
role | devel-lib, program |
scope | utility |
use | analysing, converting |
works-with-format | plaintext, xml |
|
License: DFSG free
|
This is a collection of perl code for dealing with Gene Ontologies (GO) and
Open Biomedical Ontologies (OBO) style ontologies. It is part of the ‘go-dev’
distribution, but this Debian package is made from the CPAN archive. This
package contains both scripts (which can be used with no knowledge of perl),
and libraries which will be of use to perl programmers using GO or OBO.
|
|
libhdf5-dev
HDF5 - development files - serial version
|
Versions of package libhdf5-dev |
Release | Version | Architectures |
buster-security | 1.10.4+repack-10+deb10u1 | amd64,arm64,armhf,i386 |
trixie | 1.10.10+repack-5 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
jessie | 1.8.13+docs-15+deb8u1 | amd64,armel,armhf,i386 |
jessie-security | 1.8.13+docs-15+deb8u1 | amd64,armel,armhf,i386 |
stretch | 1.10.0-patch1+docs-3+deb9u1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
bullseye | 1.10.6+repack-4+deb11u1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.14.5+repack-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 1.10.8+repack1-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 1.10.4+repack-10 | amd64,arm64,armhf,i386 |
Debtags of package libhdf5-dev: |
devel | library |
role | devel-lib |
|
License: DFSG free
|
Hierarchical Data Format 5 (HDF5) is a file format and library for
storing scientific data. HDF5 was designed and implemented to address
the deficiencies of HDF4.x. It has a more powerful and flexible data
model, supports files larger than 2 GB, and supports parallel I/O.
This package contains development files for serial platforms.
|
|
libhmsbeagle-dev
High-performance lib for Bayesian and Maximum Likelihood phylogenetics (devel)
|
Versions of package libhmsbeagle-dev |
Release | Version | Architectures |
buster | 3.1.2+dfsg-6 | amd64,arm64,armhf,i386 |
sid | 4.0.1+dfsg-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 3.1.2+dfsg-13 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 3.1.2+dfsg-13 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
jessie | 2.1.2-1 | amd64,armel,armhf,i386 |
stretch | 2.1.2+20160831-5 | amd64,arm64,armhf,i386 |
bullseye | 3.1.2+dfsg-10 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
Debtags of package libhmsbeagle-dev: |
devel | library |
role | devel-lib |
|
License: DFSG free
|
BEAGLE is a high-performance library that can perform the core calculations at
the heart of most Bayesian and Maximum Likelihood phylogenetics packages. It
can make use of highly-parallel processors such as those in graphics cards
(GPUs) found in many PCs.
The project involves an open API and fast implementations of a library for
evaluating phylogenetic likelihoods (continuous time Markov processes) of
biomolecular sequence evolution.
The aim is to provide high performance evaluation 'services' to a wide range
of phylogenetic software, both Bayesian samplers and Maximum Likelihood
optimizers. This allows these packages to make use of implementations that
make use of optimized hardware such as graphics processing units.
This package contains development files needed to build against Beagle library.
Please cite:
Daniel L. Ayres, Aaron Darling, Derrick J. Zwickl, Peter Beerli, Mark T. Holder, Paul O. Lewis, John P. Huelsenbeck, Fredrik Ronquist, David L. Swofford, Michael P. Cummings, Andrew Rambaut and Marc A. Suchard:
BEAGLE: an Application Programming Interface and High-Performance Computing Library for Statistical Phylogenetics.
(PubMed,eprint)
Systematic Biology
61(1):170-3
(2012)
|
|
libhts-dev
development files for the HTSlib
|
Versions of package libhts-dev |
Release | Version | Architectures |
stretch-backports | 1.7-2~bpo9+1 | amd64,arm64,armel,armhf,mips,mips64el,mipsel,ppc64el,s390x |
experimental | 1.21+ds-0+exp2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
jessie | 1.1-1 | amd64,armel,i386 |
stretch | 1.3.2-2 | amd64,arm64,armel,i386,mips64el,mipsel,ppc64el |
sid | 1.20+ds-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster | 1.9-12~deb10u1 | amd64,arm64,armhf,i386 |
bullseye | 1.11-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.16+ds-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.20+ds-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
upstream | 1.21 |
Debtags of package libhts-dev: |
devel | library |
role | devel-lib |
|
License: DFSG free
|
HTSlib is an implementation of a unified C library for accessing common file
formats, such as SAM (Sequence Alignment/Map), CRAM and VCF (Variant Call
Format), used for high-throughput sequencing data, and is the core library
used by samtools and bcftools. HTSlib only depends on zlib. It is known to be
compatible with gcc, g++ and clang.
HTSlib implements a generalized BAM (binary SAM) index, with file extension
‘csi’ (coordinate-sorted index). The HTSlib file reader first looks for the
new index and then for the old if the new index is absent.
This package contains development files for the HTSlib: headers, static
library, manual pages, etc.
For compatibility with sambamba, the internal routine cram_to_bam was
exported, hereto adopting a patch found in guix.
|
|
libhtscodecs-dev
Development headers for custom compression for CRAM and others
|
Versions of package libhtscodecs-dev |
Release | Version | Architectures |
trixie | 1.6.1-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 1.6.1-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 0.5-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.3.0-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
|
License: DFSG free
|
This library implements the custom CRAM codecs used for "EXTERNAL" block
types. These consist of two variants of the rANS codec (8-bit and 16-bit
renormalisation, with run-length encoding and bit-packing also supported
in the latter), a dynamic arithmetic coder, and custom codecs for name/ID
compression and quality score compression derived from fqzcomp.
They come with small command line test tools to act as both compression
exploration programs and as part of the test harness.
This package contains the development headers
|
|
libhtsjdk-java
Java API for high-throughput sequencing data (HTS) formats
|
Versions of package libhtsjdk-java |
Release | Version | Architectures |
bookworm | 3.0.4+dfsg-2 | all |
stretch | 2.8.1+dfsg-1 | all |
trixie | 4.1.0+dfsg-2 | all |
bullseye | 2.23.0+dfsg-2 | all |
buster | 2.18.2+dfsg-2 | all |
sid | 4.1.0+dfsg-2 | all |
upstream | 4.1.3 |
|
License: DFSG free
|
HTSJDK is an implementation of a unified Java library for accessing common
file formats, such as SAM (Sequence Alignment/Map) and VCF, used for
high-throughput sequencing data. There are also an number of useful utilities
for manipulating HTS data.
|
|
libjebl2-java
Java Evolutionary Biology Library
|
Versions of package libjebl2-java |
Release | Version | Architectures |
sid | 0.1+git20230701.b3c0f25-1 | all |
jessie | 0.0.r22-1 | all |
stretch | 0.1+20140614-1 | all |
buster | 0.1+git20180418.653eb83-1 | all |
bullseye | 0.1+git20201011.969bd4b-1 | all |
bookworm | 0.1+git20201011.969bd4b-1 | all |
trixie | 0.1+git20230701.b3c0f25-1 | all |
upstream | 0.1+git20231105.51da3b1 |
|
License: DFSG free
|
A Java library for evolutionary biology and bioinformatics, including
objects representing biomolecular sequences, multiple sequence
alignments and phylogenetic trees.
This is a branch of the original JEBL on
http://sourceforge.net/projects/jebl/ to develop a new API and class
library.
|
|
libjloda-java
Java library of data structures and algorithms for bioinformatics
|
Versions of package libjloda-java |
Release | Version | Architectures |
stretch | 0.0+20161018-1 | all |
buster | 0.0+git20180523.cbaf6d1-1 | all |
sid | 2.1+ds-3 | all |
trixie | 2.1+ds-3 | all |
bookworm | 2.1-2 | all |
bullseye | 2.0-1 | all |
|
License: DFSG free
|
The jloda Java library provides some basic data structures and
algorithms used by bioinformatics applications like SplitsTree,
Dendroscope and MEGAN.
|
|
libkmer-dev
suite of tools for DNA sequence analysis (development lib)
|
Versions of package libkmer-dev |
Release | Version | Architectures |
bullseye | 0~20150903+r2013-8 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 0~20150903+r2013-9 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 0~20150903+r2013-9 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 0~20150903+r2013-8 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 0~20150903+r2013-6 | amd64,arm64,armhf,i386 |
stretch | 0~20150903+r2013-3 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
|
License: DFSG free
|
The kmer package is a suite of tools for DNA sequence analysis.
It provides tools for searching (ESTs, mRNAs, sequencing reads);
aligning (ESTs, mRNAs, whole genomes); and a variety of analyses
based on kmers.
This package contains headers and static libraries for kmer.
|
|
libmems-dev
development library to support DNA string matching and comparative genomics
|
Versions of package libmems-dev |
Release | Version | Architectures |
buster | 1.6.0+4725-8 | amd64,arm64,armhf,i386 |
bullseye | 1.6.0+4725-9 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.6.0+4725-9 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.6.0+4725-11 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 1.6.0+4725-11 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
|
License: DFSG free
|
libMems is a freely available software development library to support DNA
string matching and comparative genomics. Among other things, libMems
implements an algorithm to perform approximate multi-MUM and multi-MEM
identification. The algorithm uses spaced seed patterns in conjunction
with a seed-and-extend style hashing method to identify matches. The method
is efficient, requiring a maximum of only 16 bytes per base of the largest
input sequence, and this data can be stored externally (i.e. on disk) to
further reduce memory requirements.
This is the development package containing the statically linked
library and the header files.
|
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libminimap2-dev
development headers for libminimap
|
Versions of package libminimap2-dev |
Release | Version | Architectures |
trixie | 2.27+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 2.17+dfsg-12 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 2.24+dfsg-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 2.27+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
upstream | 2.28 |
|
License: DFSG free
|
Minimap2 is a versatile sequence alignment program that aligns DNA or
mRNA sequences against a large reference database. Typical use cases
include: (1) mapping PacBio or Oxford Nanopore genomic reads to the
human genome; (2) finding overlaps between long reads with error rate up
to ~15%; (3) splice-aware alignment of PacBio Iso-Seq or Nanopore cDNA
or Direct RNA reads against a reference genome; (4) aligning Illumina
single- or paired-end reads; (5) assembly-to-assembly alignment; (6) full-
genome alignment between two closely related species with divergence
below ~15%.
This package contains the C library headers for using minimap in custom tools,
along with a static library.
|
|
libmmblib-dev
development files of MacroMoleculeBuilder
|
Versions of package libmmblib-dev |
Release | Version | Architectures |
bullseye | 3.2+dfsg-2+deb11u1 | amd64,arm64,ppc64el |
|
License: DFSG free
|
MacroMoleculeBuilder, previously known as RNABuilder, can be used for morphing,
homology modeling, folding (e.g. using base pairing contacts), redesigning
complexes, fitting to low-resolution density maps, predicting local
rearrangements upon mutation, and many other applications.
This package contains the development files.
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libmuscle-dev
multiple alignment development library for protein sequences
|
Versions of package libmuscle-dev |
Release | Version | Architectures |
trixie | 3.7+4565-8 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 3.7+4565-7 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 3.7+4565-7 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 3.7+4565-6 | amd64,arm64,armhf,i386 |
sid | 3.7+4565-8 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
|
License: DFSG free
|
MUSCLE is a multiple alignment program for protein sequences. MUSCLE
stands for multiple sequence comparison by log-expectation. In the
authors tests, MUSCLE achieved the highest scores of all tested
programs on several alignment accuracy benchmarks, and is also one of
the fastest programs out there.
This library was derived from the original MUSCLE and turned into
a library.
This package contains the static library and header files.
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libncbi-vdb-dev
libraries for using data in the INSDC Sequence Read Archives (devel)
|
Versions of package libncbi-vdb-dev |
Release | Version | Architectures |
buster | 2.9.3+dfsg-2 | amd64,i386 |
trixie | 3.0.9+dfsg-2 | amd64,arm64 |
sid | 3.0.9+dfsg-2 | amd64,arm64 |
bookworm | 3.0.2+dfsg-2 | amd64,arm64 |
experimental | 3.1.1+dfsg-1 | amd64,arm64 |
bullseye | 2.10.9+dfsg-2 | amd64,i386 |
stretch | 2.8.1+dfsg-2 | amd64,i386 |
upstream | 3.1.1 |
|
License: DFSG free
|
The (US) National Center for Biotechnology Information (NCBI)'s
Virtual/Vertical Database (VDB) is a highly compressed column-oriented
data warehousing technology developed initially to address the needs
of the Sequence Read Archive (SRA). It is unique in that it builds
databases from smaller parts that can function independently as
documents, supports effective and efficient compression, supports
encryption while remaining encrypted on disk, transparent distribution
and remote access.
This is the development package for reading VDB data.
|
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libncbi6-dev
NCBI libraries for biology applications (development files)
|
Versions of package libncbi6-dev |
Release | Version | Architectures |
trixie | 6.1.20170106+dfsg2-5 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 6.1.20170106+dfsg1-10 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 6.1.20170106+dfsg1-9 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 6.1.20170106+dfsg1-0+deb10u2 | amd64,arm64,armhf,i386 |
stretch | 6.1.20170106+dfsg1-0+deb9u1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
jessie | 6.1.20120620-8 | amd64,armel,armhf,i386 |
sid | 6.1.20170106+dfsg2-5 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
Debtags of package libncbi6-dev: |
biology | nuceleic-acids, peptidic |
devel | lang:c, library |
field | biology, biology:bioinformatics |
role | devel-lib |
science | calculation |
use | analysing, calculating, converting, searching |
works-with | biological-sequence |
works-with-format | plaintext, xml |
|
License: DFSG free
|
This package supplies development versions of NCBI's non-graphical C
libraries, along with the corresponding header files.
|
|
libncl-dev
NEXUS Class Library (static lib and header files)
|
Versions of package libncl-dev |
Release | Version | Architectures |
bullseye | 2.1.21+git20190531.feceb81-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 2.1.21+git20210811.b1213a7-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 2.1.21+git20210811.b1213a7-6 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch | 2.1.18+dfsg-2 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 2.1.21+git20180827.c71b264-2 | amd64,arm64,armhf,i386 |
sid | 2.1.21+git20210811.b1213a7-6 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
upstream | 2.1.21+git20231019.f845ec2 |
|
License: DFSG free
|
The NEXUS Class Library is a C++ library for parsing NEXUS files.
The NEXUS file format is widely used in bioinformatics. Several popular
phylogenetic programs such as Paup, MrBayes, Mesquite, and MacClade use
this format.
This package contains the static library and header files of the NEXUS
library.
|
|
libngs-java
Next Generation Sequencing language Bindings (Java bindings)
|
Versions of package libngs-java |
Release | Version | Architectures |
buster | 2.9.3-1 | amd64,i386 |
bullseye | 2.10.9-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 3.0.9+dfsg-7 | amd64,arm64 |
stretch | 1.3.0-2 | amd64,i386 |
trixie | 3.0.9+dfsg-7 | amd64,arm64 |
bookworm | 3.0.3+dfsg-6~deb12u1 | amd64,arm64 |
upstream | 3.1.1 |
|
License: DFSG free
|
NGS is a new, domain-specific API for accessing reads, alignments and
pileups produced from Next Generation Sequencing. The API itself is
independent from any particular back-end implementation, and supports
use of multiple back-ends simultaneously. It also provides a library for
building new back-end "engines". The engine for accessing SRA data is
contained within the sister repository ncbi-vdb.
The API is currently expressed in C++, Java and Python languages. The
design makes it possible to maintain a high degree of similarity between
the code in one language and code in another - especially between C++
and Java.
Java bindings.
Please cite:
Rasko Leinonen, Ruth Akhtar, Ewan Birney, James Bonfield, Lawrence Bower, Matt Corbett, Ying Cheng, Fehmi Demiralp, Nadeem Faruque, Neil Goodgame, Richard Gibson, Gemma Hoad, Christopher Hunter, Mikyung Jang, Steven Leonard, Quan Lin, Rodrigo Lopez, Michael Maguire, Hamish McWilliam, Sheila Plaister, Rajesh Radhakrishnan, Siamak Sobhany, Guy Slater, Petra Ten Hoopen, Franck Valentin, Robert Vaughan, Vadim Zalunin, Daniel Zerbino and Guy Cochrane:
Improvements to services at the European Nucleotide Archive.
(PubMed,eprint)
Nucleic Acids Research
38(Database issue):D39-45
(2010)
|
|
libngs-sdk-dev
Next Generation Sequencing language Bindings (development)
|
Versions of package libngs-sdk-dev |
Release | Version | Architectures |
bullseye | 2.10.9-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
stretch | 1.3.0-2 | amd64,i386 |
buster | 2.9.3-1 | amd64,i386 |
|
License: DFSG free
|
NGS is a new, domain-specific API for accessing reads, alignments and
pileups produced from Next Generation Sequencing. The API itself is
independent from any particular back-end implementation, and supports
use of multiple back-ends simultaneously. It also provides a library for
building new back-end "engines". The engine for accessing SRA data is
contained within the sister repository ncbi-vdb.
The API is currently expressed in C++, Java and Python languages. The
design makes it possible to maintain a high degree of similarity between
the code in one language and code in another - especially between C++
and Java.
This is the development package.
|
|
libnhgri-blastall-perl
Perl extension for running and parsing NCBI's BLAST 2.x
|
Versions of package libnhgri-blastall-perl |
Release | Version | Architectures |
trixie | 0.66-4 | all |
jessie | 0.66-1 | all |
stretch | 0.66-2 | all |
buster | 0.66-3 | all |
bullseye | 0.66-4 | all |
bookworm | 0.66-4 | all |
sid | 0.66-4 | all |
Debtags of package libnhgri-blastall-perl: |
devel | lang:perl, library |
|
License: DFSG free
|
NHGRI::Blastall will enable usage of BLAST out of a Perl script, if BLAST2
or WU-BLAST are installed locally. Main features are:
- run BLAST (also via network, which requires blastcl3)
- BLAST single sequences against each other or against a given library
- format databases
- mask out repetitive DNA
- read, parse and filter existing BLAST reports
|
|
libopenmm-dev
C++ header files for the OpenMM library
|
Versions of package libopenmm-dev |
Release | Version | Architectures |
trixie | 8.1.2+dfsg-2 | amd64,arm64,armhf,mips64el,ppc64el,riscv64 |
bullseye | 7.5.0+dfsg-1 | amd64,arm64,ppc64el |
sid | 8.1.2+dfsg-2 | amd64,arm64,armhf,mips64el,ppc64el,riscv64 |
bookworm | 7.7.0+dfsg-9 | amd64,arm64,ppc64el |
upstream | 8.2.0 |
|
License: DFSG free
|
OpenMM is a software toolkit for performing molecular simulations on a range
of high performance computing architectures. This package provides C++ header
files for the development with that library.
Please cite:
P. Eastman, J. Swails, J. D. Chodera, R. T. McGibbon, Y. Zhao, K. A. Beauchamp, L.-P. Wang, A. C. Simmonett, M. P. Harrigan, C. D. Stern, R. P. Wiewiora, B. R. Brooks and V. S. Pande:
OpenMM 7: Rapid development of high performance algorithms for molecular dynamics.
(PubMed,eprint)
PLOS Comp. Biol.
13(7):e1005659
(2017)
|
|
libopenms-dev
library for LC/MS data management and analysis - dev files
|
Versions of package libopenms-dev |
Release | Version | Architectures |
trixie | 2.6.0+cleaned1-4 | amd64,arm64,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 2.6.0+cleaned1-3 | amd64,arm64,i386,mips64el,mipsel,ppc64el,s390x |
jessie | 1.11.1-5 | amd64,armel,armhf,i386 |
buster | 2.4.0-real-1 | amd64,arm64,i386 |
bullseye | 2.6.0+cleaned1-3 | amd64,arm64,i386,mips64el,mipsel,ppc64el,s390x |
sid | 2.6.0+cleaned1-4 | amd64,arm64,i386,mips64el,ppc64el,riscv64,s390x |
Debtags of package libopenms-dev: |
devel | library |
role | devel-lib |
|
License: DFSG free
|
OpenMS is a library for LC/MS data management and analysis. OpenMS
offers an infrastructure for the development of mass
spectrometry-related software and powerful 2D and 3D visualization
solutions.
OpenMS offers analyses for various quantitation protocols, including
label-free quantitation, SILAC, iTRAQ, SRM, SWATH…
It provides built-in algorithms for de-novo identification and
database search, as well as adapters to other state-of-the art tools
like X!Tandem, Mascot, OMSSA…
OpenMS supports the Proteomics Standard Initiative (PSI) formats for
MS data and supports easy integration of tools into workflow engines
like Knime, Galaxy, WS-Pgrade, and TOPPAS via the TOPPtools concept
and a unified parameter handling.
This package ships the library development files.
Please cite:
Marc Sturm, Andreas Bertsch, Clemens Gröpl, Andreas Hildebrandt, Rene Hussong, Eva Lange, Nico Pfeifer, Ole Schulz-Trieglaff, Alexandra Zerck, Knut Reinert and Oliver Kohlbacher:
OpenMS – an Open-Source Software Framework for Mass Spectrometry.
(PubMed,eprint)
BMC Bioinformatics
9(163)
(2008)
|
|
libpal-java
Phylogenetic Analysis Library
|
Versions of package libpal-java |
Release | Version | Architectures |
bullseye | 1.5.1+dfsg-6 | all |
jessie | 1.5.1-2 | all |
stretch | 1.5.1+dfsg-2 | all |
buster | 1.5.1+dfsg-5 | all |
bookworm | 1.5.1+dfsg-8 | all |
trixie | 1.5.1+dfsg-9 | all |
sid | 1.5.1+dfsg-9 | all |
|
License: DFSG free
|
The PAL project is a collaborative effort to provide a high quality Java
library for use in molecular evolution and phylogenetics. At present PAL
consists of approximately 200 public classes/interfaces in 16 packages
Please refer to the API documentation for a detailed description of all
classes and methods available, and to the release history for an
overview of the development history of PAL.
|
|
libparasail-dev
Development heaaders and static libraries for parasail
|
Versions of package libparasail-dev |
Release | Version | Architectures |
trixie | 2.6.2+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 2.6+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 2.4.3+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 2.6.2+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
|
License: DFSG free
|
This package provides development headers and static libraries for
parasail. It is a SIMD C library containing implementations of the
Smith-Waterman, Needleman-Wunsch, and various semi-global pairwise
sequence alignment algorithm.
|
|
libpbbam-dev
Pacific Biosciences binary alignment/map (BAM) library (headers)
|
Versions of package libpbbam-dev |
Release | Version | Architectures |
bookworm | 2.1.0+dfsg-2 | amd64,arm64,mips64el,ppc64el |
stretch | 0.7.4+ds-1 | amd64,arm64,mips64el,ppc64el |
buster | 0.19.0+dfsg-4 | amd64,arm64 |
trixie | 2.4.0+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64 |
sid | 2.4.0+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64 |
bullseye | 1.6.0+dfsg-2 | amd64,arm64,mips64el,ppc64el |
|
License: DFSG free
|
The BAM format is a binary, compressed, record-oriented container format
for raw or aligned sequence reads. The associated SAM format is a text
representation of the same data. The specifications for BAM/SAM are maintained
by the SAM/BAM Format Specification Working Group.
PacBio-produced BAM files are fully compatible with the BAM specification,
but makes use of the extensibility mechanisms of the BAM specification to
encode PacBio-specific information. The pbbam library provides tools to
work with these files
This package contains the library header files.
|
|
libpbdata-dev
tools for handling PacBio sequences (development files)
|
Versions of package libpbdata-dev |
Release | Version | Architectures |
bookworm | 5.3.5+dfsg-4 | amd64,arm64,mips64el,ppc64el |
bullseye | 5.3.4+dfsg-3 | amd64,arm64,mips64el,ppc64el |
buster | 5.3.1+dfsg-2.1 | amd64,arm64 |
trixie | 5.3.5+dfsg-8 | amd64,arm64,mips64el,ppc64el,riscv64 |
stretch | 0~20161219-1 | amd64,arm64,mips64el,ppc64el |
sid | 5.3.5+dfsg-9 | amd64,arm64,mips64el,ppc64el,riscv64 |
|
License: DFSG free
|
Blasr_libcpp is a library used by blasr and other executables such as
samtoh5, loadPulses for analyzing PacBio sequences. This library contains
three sub-libraries, including pbdata, hdf and alignment.
This package contains the header files and static library for the pbdata
sublibrary.
|
|
libpbihdf-dev
tools for handling PacBio hdf5 files (development files)
|
Versions of package libpbihdf-dev |
Release | Version | Architectures |
buster | 5.3.1+dfsg-2.1 | amd64,arm64 |
bullseye | 5.3.4+dfsg-3 | amd64,arm64,mips64el,ppc64el |
bookworm | 5.3.5+dfsg-4 | amd64,arm64,mips64el,ppc64el |
trixie | 5.3.5+dfsg-8 | amd64,arm64,mips64el,ppc64el,riscv64 |
stretch | 0~20161219-1 | amd64,arm64,mips64el,ppc64el |
sid | 5.3.5+dfsg-9 | amd64,arm64,mips64el,ppc64el,riscv64 |
|
License: DFSG free
|
Blasr_libcpp is a library used by blasr and other executables such as
samtoh5, loadPulses for analyzing PacBio sequences. This library contains
three sub-libraries, including pbdata, hdf and alignment.
This package contains the header files and static library for the hdf
sublibrary.
|
|
libpbseq-dev
library for analyzing PacBio sequencing data (development files)
|
Versions of package libpbseq-dev |
Release | Version | Architectures |
stretch | 0~20161219-1 | all |
bullseye | 5.3.4+dfsg-3 | amd64,arm64,mips64el,ppc64el |
trixie | 5.3.5+dfsg-8 | amd64,arm64,mips64el,ppc64el,riscv64 |
buster | 5.3.1+dfsg-2.1 | all |
sid | 5.3.5+dfsg-9 | amd64,arm64,mips64el,ppc64el,riscv64 |
bookworm | 5.3.5+dfsg-4 | amd64,arm64,mips64el,ppc64el |
|
License: DFSG free
|
Blasr_libcpp is a library used by blasr and other executables such as
samtoh5, loadPulses for analyzing PacBio sequences. This library contains
three sub-libraries, including pbdata, hdf and alignment.
This is a metapackage that depends on the pbseqlib component development files.
|
|
libpdb-redo-dev
Development files for libpdb-redo
|
Versions of package libpdb-redo-dev |
Release | Version | Architectures |
trixie | 3.1.5-5 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 3.0.5-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 1.0.2-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 3.1.5-5 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
|
License: DFSG free
|
This library contains shared code for the various programs
in the project PDB-REDO.
This specific package contains all files needed to develop new
software using libpdb-redo.
|
|
libpll-dev
Phylogenetic Likelihood Library (development)
|
Versions of package libpll-dev |
Release | Version | Architectures |
bookworm | 0.3.2-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 0.3.2-5 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 0.3.2-5 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 0.3.2-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 0.3.2-2 | amd64,arm64,armhf,i386 |
|
License: DFSG free
|
PLL is a highly optimized, parallelized software library to ease the
development of new software tools dealing with phylogenetic inference.
Among the functions included in PLL are parsing multiple sequence
alignments (MSA) from PHYLIP and FASTA files, reading Newick trees,
performing topological moves such as SPR and NNI, model optimization,
likelihood evaluation and partitioned analysis by assigning different
substitution models to each partition of the MSA. PLL fully implements
the GTR nucleotide substitution model for DNA data and a number of
models for aminoacid data.
This package contains the static library and the header file.
|
|
libpwiz-dev
library to perform proteomics data analyses (devel files)
|
Versions of package libpwiz-dev |
Release | Version | Architectures |
bookworm | 3.0.18342-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 3.0.18342-4.1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
jessie | 3.0.6585-2 | amd64,armel,armhf,i386 |
stretch | 3.0.9393-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 3.0.18342-2 | amd64,arm64,armhf,i386 |
bullseye | 3.0.18342-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
Debtags of package libpwiz-dev: |
devel | library |
role | devel-lib |
|
License: DFSG free
|
The libpwiz library from the ProteoWizard project provides a modular
and extensible set of open-source, cross-platform tools and
libraries. The tools perform proteomics data analyses; the libraries
enable rapid tool creation by providing a robust, pluggable
development framework that simplifies and unifies data file access,
and performs standard chemistry and LCMS dataset computations.
The primary goal of ProteoWizard is to eliminate the existing
barriers to proteomic software development so that researchers can
focus on the development of new analytic approaches, rather than
having to dedicate significant resources to mundane (if important)
tasks, like reading data files.
This package ships the library development files.
|
|
libqes-dev
DNA sequence parsing library -- development
|
Versions of package libqes-dev |
Release | Version | Architectures |
bullseye | 0.2.8+ds-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 0.2.8+ds-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 0.2.8-1 | amd64,arm64,armhf,i386 |
trixie | 0.2.8+ds-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 0.2.8+ds-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch | 0.2.7-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
|
License: DFSG free
|
A small C library, with a bioinformatic focus. Optimised for speed and a clean
API. Handles sequence parsing and miscellaneous manipulation of DNA sequences.
These are the development headers required to use libqes in your own
applications.
|
|
librcsb-core-wrapper0-dev
development files for librcsb-core-wrapper0t64
|
Versions of package librcsb-core-wrapper0-dev |
Release | Version | Architectures |
trixie | 1.005-12 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 1.005-13 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 1.005-11 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
jessie | 1.005-3 | amd64,armel,armhf,i386 |
bullseye | 1.005-10 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 1.005-6 | amd64,arm64,armhf,i386 |
stretch | 1.005-4 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
Debtags of package librcsb-core-wrapper0-dev: |
devel | library |
role | devel-lib |
|
License: DFSG free
|
The RCSB Core Wrapper library was developed to provide an object-oriented
application interface to information in mmCIF format. It includes several
classes for accessing data dictionaries and mmCIF format data files.
This package contains files necessary for developing applications with
the library.
|
|
librdp-taxonomy-tree-java
taxonomy tree library from Ribosomal Database Project (RDP)
|
Versions of package librdp-taxonomy-tree-java |
Release | Version | Architectures |
trixie | 1.2.0-6 | all |
bullseye | 1.2.0-4 | all |
buster | 1.2.0-3 | all |
stretch | 1.2.0-1 | all |
sid | 1.2.0-6 | all |
bookworm | 1.2.0-6 | all |
|
License: DFSG free
|
The TaxonomyTree project is a library used by other Ribosomal Database
Project (RDP) tools.
|
|
librelion-dev
C++ API for RELION (3D reconstructions in cryo-electron microscopy)
|
Versions of package librelion-dev |
Release | Version | Architectures |
stretch | 1.4+dfsg-2 | amd64,i386 |
buster | 1.4+dfsg-4 | amd64,i386 |
jessie | 1.3+dfsg-2 | amd64,i386 |
upstream | 5.0.0 |
|
License: DFSG free
|
RELION (for REgularised LIkelihood OptimisatioN) is a stand-alone
computer program for Maximum A Posteriori refinement of (multiple) 3D
reconstructions or 2D class averages in cryo-electron microscopy.
RELION provides a GUI, several command-line tools in parallel (MPI) and serial
versions as well as a C++ API.
This is the developers API package for use without GUI and MPI.
|
|
librg-blast-parser-perl
very fast NCBI BLAST parser - binding for Perl
|
Versions of package librg-blast-parser-perl |
Release | Version | Architectures |
stretch | 0.03-4 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
bullseye | 0.03-7 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
jessie | 0.03-2 | amd64,armel,armhf,i386 |
bookworm | 0.03-9 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 0.03-9 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 0.03-9 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster | 0.03-6 | amd64,arm64,armhf,i386 |
Debtags of package librg-blast-parser-perl: |
devel | lang:perl, library |
|
License: DFSG free
|
This package contains Perl binding for a very fast C++ library that parses
the default output of NCBI BLAST programs. BLAST results are returned in a
convenient hash structure.
Evaluated on a very small test set, this parser is considerably faster
than Zerg::Report from libzerg-perl.
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librg-reprof-bundle-perl
protein secondary structure and accessibility predictor (perl module)
|
Versions of package librg-reprof-bundle-perl |
Release | Version | Architectures |
bullseye | 1.0.1-7 | all |
buster | 1.0.1-6 | all |
stretch | 1.0.1-4 | all |
jessie | 1.0.1-1 | all |
sid | 1.0.1-8 | all |
trixie | 1.0.1-8 | all |
bookworm | 1.0.1-8 | all |
Debtags of package librg-reprof-bundle-perl: |
devel | lang:perl, library |
|
License: DFSG free
|
'reprof' is an improved implementation of 'prof', a popular protein secondary
structure and accessibility predictor. Prediction is either
done from protein sequence alone or from an alignment - the latter should be
used for optimal performance.
This package provides the perl modules implementing 'reprof' along with the
necessary data files.
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librostlab-blast0-dev
very fast C++ library for parsing the output of NCBI BLAST programs (devel)
|
Versions of package librostlab-blast0-dev |
Release | Version | Architectures |
sid | 1.0.1-14 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.0.1-10 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.0.1-13 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
jessie | 1.0.1-3 | amd64,armel,armhf,i386 |
trixie | 1.0.1-14 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster | 1.0.1-10 | amd64,arm64,armhf,i386 |
stretch | 1.0.1-7 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
Debtags of package librostlab-blast0-dev: |
devel | library |
role | devel-lib |
|
License: DFSG free
|
This package provides a very fast library for parsing the default output of
NCBI BLAST programs into a C++ structure.
libzerg is faster, but it provides only lexing (i.e. it only returns pairs
of token identifiers and token string values). librostlab-blast uses a
parser generated with bison on top of a flex-generated lexer very similar to
that of libzerg.
This package contains files necessary for developing applications with
librostlab-blast.
|
|
librostlab3-dev
C++ library for computational biology (development)
|
Versions of package librostlab3-dev |
Release | Version | Architectures |
bullseye | 1.0.20-10 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.0.20-13.1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 1.0.20-13.1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 1.0.20-12 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
stretch | 1.0.20-6 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 1.0.20-8 | amd64,arm64,armhf,i386 |
jessie | 1.0.20-4 | amd64,armel,armhf,i386 |
Debtags of package librostlab3-dev: |
devel | library |
role | devel-lib |
|
License: DFSG free
|
This library was developed by the Rost Lab. The lab's research is
driven by a conviction that protein and DNA sequences encode a
significant core of information about the ultimate structure and
function of genetic material and its gene products.
The library provides the following facilities:
- current working directory resource
- exception with stack backtrace
- file lock resource
- passwd and group structures for C++
- effective uid and gid resource
- rostlab::bio::seq class with stream input operator for FASTA format
- umask resource
This package contains files necessary for developing applications with
librostlab.
|
|
libsbml5-dev
System Biology Markup Language library - development files
|
Versions of package libsbml5-dev |
Release | Version | Architectures |
buster | 5.17.2+dfsg-3 | amd64,arm64,armhf,i386 |
jessie | 5.10.0+dfsg-1 | amd64,armel,armhf,i386 |
sid | 5.20.2+dfsg-8 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 5.20.2+dfsg-8 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 5.19.7+dfsg-2 | amd64,arm64,armel,armhf,i386,ppc64el,s390x |
stretch | 5.13.0+dfsg-1 | amd64,arm64,armel,armhf,i386,mipsel,ppc64el,s390x |
bullseye | 5.19.0+dfsg-1 | amd64,arm64,armel,armhf,i386,ppc64el,s390x |
upstream | 5.20.4 |
Debtags of package libsbml5-dev: |
devel | library |
role | devel-lib |
|
License: DFSG free
|
LibSBML is a library designed to help you read, write, manipulate,
translate, and validate SBML files and data streams. It is not an
application itself (though it does come with many example programs),
but rather a library you can embed in your own applications.
This package contains files necessary for development with libsbml.
|
|
libseqan2-dev
C++ library for the analysis of biological sequences (development)
|
Versions of package libseqan2-dev |
Release | Version | Architectures |
bullseye | 2.4.0+dfsg-14 | all |
stretch-backports | 2.4.0+dfsg-11~bpo9+1 | all |
buster | 2.4.0+dfsg-11 | all |
stretch | 2.3.1+dfsg-4 | all |
experimental | 2.5.0~rc3+dfsg-1 | all |
sid | 2.4.0+dfsg-16 | all |
trixie | 2.4.0+dfsg-16 | all |
bookworm | 2.4.0+dfsg-15 | all |
|
License: DFSG free
|
SeqAn is a C++ template library of efficient algorithms and data
structures for the analysis of sequences with the focus on
biological data. This library applies a unique generic design that
guarantees high performance, generality, extensibility, and
integration with other libraries. SeqAn is easy to use and
simplifies the development of new software tools with a minimal loss
of performance.
This package contains the developer files.
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libseqan3-dev
C++ library for the analysis of biological sequences v3 (development)
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Versions of package libseqan3-dev |
Release | Version | Architectures |
bookworm | 3.2.0+ds-6 | all |
buster-backports | 3.0.1+ds-3~bpo10+1 | amd64,arm64,mips64el,ppc64el,s390x |
experimental | 3.4.0~rc.1+ds-1~0exp0 | all |
bullseye | 3.0.2+ds-9 | all |
sid | 3.3.0+ds-3 | all |
trixie | 3.3.0+ds-3 | all |
upstream | 3.4.0~rc.2 |
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License: DFSG free
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SeqAn is a C++ template library of efficient algorithms and data
structures for the analysis of sequences with the focus on
biological data. This library applies a unique generic design that
guarantees high performance, generality, extensibility, and
integration with other libraries. SeqAn is easy to use and
simplifies the development of new software tools with a minimal loss
of performance.
This package contains the developer files.
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libseqlib-dev
C++ htslib/bwa-mem/fermi interface for interrogating sequence data (dev)
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Versions of package libseqlib-dev |
Release | Version | Architectures |
buster | 1.1.2+dfsg-3 | amd64 |
bullseye | 1.2.0+dfsg-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.2.0+dfsg-9 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.2.0+dfsg-11 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 1.2.0+dfsg-11 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch-backports | 1.1.2+dfsg-1~bpo9+1 | amd64 |
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License: DFSG free
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C++ API and command line tool that provides a rapid and user-friendly
interface to BAM/SAM/CRAM files, global sequence alignment operations
and sequence assembly. Four C libraries perform core operations in
SeqLib: HTSlib for BAM access, BWA-MEM and BLAT for sequence alignment
and Fermi for error correction and sequence assembly. Benchmarking
indicates that SeqLib has lower CPU and memory requirements than leading
C++ sequence analysis APIs. Minimal SeqLib code can extract, error-correct
and assemble reads from a CRAM file and then align with BWA-MEM.
SeqLib also provides additional capabilities, including chromosome-aware
interval queries and read plotting. Command line tools are available for
performing integrated error correction, micro-assemblies and alignment.
This package contains the header files and static library.
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libslow5-dev
header and static library for reading & writing SLOW5 files
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Versions of package libslow5-dev |
Release | Version | Architectures |
trixie | 0.7.0+dfsg-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
bookworm | 0.7.0+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
sid | 0.7.0+dfsg-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
upstream | 1.3.0 |
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License: DFSG free
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Slow5lib is a software library for reading & writing SLOW5 files.
Slow5lib is designed to facilitate use of data in SLOW5 format by third-
party software packages. Existing packages that read/write data in FAST5
format can be easily modified to support SLOW5.
SLOW5 is a new file format for storing signal data from Oxford Nanopore
Technologies (ONT) devices. SLOW5 was developed to overcome inherent
limitations in the standard FAST5 signal data format that prevent
efficient, scalable analysis and cause many headaches for developers.
SLOW5 can be encoded in human-readable ASCII format, or a more compact
and efficient binary format (BLOW5) - this is analogous to the seminal
SAM/BAM format for storing DNA sequence alignments. The BLOW5 binary
format supports zlib (DEFLATE) compression, or other compression
methods, thereby minimising the data storage footprint while still
permitting efficient parallel access. Detailed benchmarking experiments
have shown that SLOW5 format is an order of magnitude faster and
significantly smaller than FAST5.
This is the development package containing headers and static library.
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libsmithwaterman-dev
determine similar regions between two strings or genomic sequences (devel)
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Versions of package libsmithwaterman-dev |
Release | Version | Architectures |
trixie | 0.0+git20160702.2610e25-12 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 0.0+git20160702.2610e25-12 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
stretch | 0.0+20160702-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el |
stretch-backports | 0.0+git20160702.2610e25-4~bpo9+1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el |
buster | 0.0+git20160702.2610e25-7 | amd64,arm64,armhf,i386 |
bullseye | 0.0+git20160702.2610e25-11 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 0.0+git20160702.2610e25-12 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
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License: DFSG free
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The Smith–Waterman algorithm performs local sequence alignment; that is,
for determining similar regions between two strings or nucleotide or
protein sequences. Instead of looking at the total sequence, the
Smith–Waterman algorithm compares segments of all possible lengths and
optimizes the similarity measure.
This is the development package containing the statically linked
library and the header files.
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libsnp-sites1-dev
Static libraries and header files for the package snp-sites
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Versions of package libsnp-sites1-dev |
Release | Version | Architectures |
stretch | 2.3.2-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
bookworm | 2.5.1-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 2.5.1-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 2.5.1-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 2.5.1-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
jessie | 1.5.0-1 | amd64,armel,armhf,i386 |
buster | 2.4.1-1 | amd64,arm64,armhf,i386 |
Debtags of package libsnp-sites1-dev: |
devel | library |
role | devel-lib |
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License: DFSG free
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Snp-sites finds single nucleotide polymorphism (SNP) sites from
multi-fasta alignment input files (which might be compressed). Its
output can be in various widely used formats (Multi Fasta Alignment,
Vcf, phylip).
The software has been developed at the Wellcome Trust Sanger Institute.
This package contains the development files to include snp-sites
into your own code. The library enables Python developers to make
snp-sites function calls (Python bindings) through the Boost Python
Library.
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libsort-key-top-perl
Perl module to select and sort top n elements of a list
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Versions of package libsort-key-top-perl |
Release | Version | Architectures |
sid | 0.08-4 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 0.08-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 0.08-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 0.08-4 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
jessie | 0.08-1 | amd64,armel,armhf,i386 |
stretch | 0.08-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 0.08-3 | amd64,arm64,armhf,i386 |
Debtags of package libsort-key-top-perl: |
devel | lang:perl, library |
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License: DFSG free
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The functions available from this module select the top n elements from a
list using several common orderings and custom key extraction procedures.
They are all variations around 'keytopsort { CALC_KEY($_) } $n => @data;'.
In array context, this function calculates the ordering key for every element
in @data using the expression inside the block. Then it selects and orders
the $n elements with the lower keys when compared lexicographically.
In scalar context, the value returned by the functions on this module is the
cutoff value allowing to select nth element from the array.
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libspoa-dev
SIMD partial order alignment library (development files)
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Versions of package libspoa-dev |
Release | Version | Architectures |
trixie | 4.1.4-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch-backports-sloppy | 3.0.1-1~bpo9+1 | amd64 |
stretch-backports | 1.1.3-2~bpo9+1 | amd64 |
bookworm | 4.0.8-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 4.0.7+ds-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 1.1.5-1 | amd64 |
sid | 4.1.4-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
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License: DFSG free
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Spoa (SIMD POA) is a c++ implementation of the partial order alignment
(POA) algorithm (as described in 10.1093/bioinformatics/18.3.452) which
is used to generate consensus sequences (as described in
10.1093/bioinformatics/btg109). It supports three alignment modes: local
(Smith-Waterman), global (Needleman-Wunsch) and semi-global alignment
(overlap).
This package contains the static library and the header files.
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libsrf-dev
C++ implementation of the SRF format for DNA sequence data
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Versions of package libsrf-dev |
Release | Version | Architectures |
jessie | 0.1+dfsg-4 | amd64,armel,armhf,i386 |
sid | 0.1+dfsg-7 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 0.1+dfsg-7 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 0.1+dfsg-7 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 0.1+dfsg-7 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 0.1+dfsg-6 | amd64,arm64,armhf,i386 |
stretch | 0.1+dfsg-4 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
Debtags of package libsrf-dev: |
devel | library |
role | shared-lib |
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License: DFSG free
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SRF (sort for Sequence Read Format) is a generic format capable of storing
data generated by any DNA sequencing technology. This library is an
implementation of SRF and provides basic input-output functions.
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libssm-dev
macromolecular superposition library - development files
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Versions of package libssm-dev |
Release | Version | Architectures |
trixie | 1.4.0-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster | 1.4.0-1 | amd64,arm64,armhf,i386 |
jessie | 1.3-2 | amd64,armel,armhf,i386 |
bullseye | 1.4.0-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.4.0-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.4.0-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
Debtags of package libssm-dev: |
devel | library |
role | devel-lib |
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License: DFSG free
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SSM is a macromolecular coordinate superposition library, written by
Eugene Krissinel of the EBI.
The library implements the SSM algorithm of protein structure
comparison in three dimensions, which includes an original procedure
of matching graphs built on the protein's secondary-structure
elements, followed by an iterative three-dimensional alignment of
protein backbone Calpha atoms.
This package contains libraries and header files needed for program
development.
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libssu-dev
high-performance phylogenetic diversity calculations (dev)
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Versions of package libssu-dev |
Release | Version | Architectures |
bookworm | 1.2-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
sid | 1.4-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
trixie | 1.4-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
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License: DFSG free
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The de facto repository for high-performance phylogenetic diversity
calculations. The methods in this repository are based on an
implementation of the Strided State UniFrac algorithm which is faster,
and uses less memory than Fast UniFrac. Strided State UniFrac supports
Unweighted UniFrac, Weighted UniFrac, Generalized UniFrac, Variance
Adjusted UniFrac and meta UniFrac. This repository also includes Stacked
Faith (manuscript in preparation), a method for calculating Faith's PD
that is faster and uses less memory than the Fast UniFrac-based
reference implementation.
This package contains the static library and header files.
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libssw-dev
Development headers and static libraries for libssw
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Versions of package libssw-dev |
Release | Version | Architectures |
bullseye | 1.1-13 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 1.1-2 | amd64 |
stretch | 1.1-1 | amd64 |
experimental | 1.2.5-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 1.1-15 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 1.1-15 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 1.1-13 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
upstream | 1.2.5 |
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License: DFSG free
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This package provides development headers and static libraries for libssw,
a fast implementation of the Smith-Waterman algorithm using
Single-Instruction Multiple-Data (SIMD) instructions to parallelize the
algorithm at the instruction level.
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libssw-java
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Versions of package libssw-java |
Release | Version | Architectures |
buster | 1.1-2 | amd64 |
trixie | 1.1-15 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 1.1-13 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
experimental | 1.2.5-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch | 1.1-1 | amd64 |
bullseye | 1.1-13 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.1-15 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
upstream | 1.2.5 |
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License: DFSG free
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This package provides JNI based Java bindings for libssw, a fast
implementation of the Smith-Waterman algorithm using Single-Instruction
Multiple-Data (SIMD) instructions to parallelize the algorithm at the
instruction level.
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libstaden-read-dev
development files for libstaden-read
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Versions of package libstaden-read-dev |
Release | Version | Architectures |
bullseye | 1.14.13-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
jessie | 1.13.7-1 | amd64,armel,armhf,i386 |
bookworm | 1.14.15-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
stretch | 1.14.8-2 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
trixie | 1.15.0-1.1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 1.15.0-1.1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster | 1.14.11-6 | amd64,arm64,armhf,i386 |
Debtags of package libstaden-read-dev: |
devel | library |
role | devel-lib |
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License: DFSG free
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This package contains the header and development files needed to build
programs and packages using the Staden io_lib.
The io_lib from the Staden package is a library of file reading and writing
code to provide a general purpose trace file (and Experiment File) reading
interface. It has been compiled and tested on a variety of unix systems,
MacOS X and MS Windows.
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libstatgen-dev
development files for the libStatGen
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Versions of package libstatgen-dev |
Release | Version | Architectures |
bullseye | 1.0.14-7 | amd64 |
bookworm | 1.0.15-6 | amd64 |
trixie | 1.0.15-8 | amd64 |
sid | 1.0.15-8 | amd64 |
buster | 1.0.14-5 | amd64 |
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License: DFSG free
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libStatGen is a library for statistical genetic programs. It includes some:
A. General Operation Classes including: File/Stream I/O, String processing
and Parameter Parsing.
B. Statistical Genetic Specific Classes including: Handling Common file
formats (Accessors to get/set values, Indexed access to BAM files) and
some utility classes, including: 1. Cigar: interpretation and mapping
between query and reference. 2. Pileup: structured access to data by
individual reference position.
This package provides the development files for libstatgen.
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libswiss-perl
Perl API to the UniProt database
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Versions of package libswiss-perl |
Release | Version | Architectures |
jessie | 1.67-1 | all |
sid | 1.80-1 | all |
trixie | 1.80-1 | all |
bookworm | 1.80-1 | all |
bullseye | 1.79-3 | all |
buster | 1.75-1 | all |
stretch | 1.67-1.1 | all |
Debtags of package libswiss-perl: |
devel | lang:perl, library |
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License: DFSG free
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UniProt, SwissProt and TrEMBL are different views on protein sequence
data that is prepared by groups at the European Bioinformatics Institute
(EMBL-EBI) in Cambridge and the Swiss Bioinformatics Institute (SIB) at
the University Hospital in Geneva.
The SwissKnife Perl library is used by the developers of these databases
to perform all the automated editing and sytax checks. The users of
this package will profit from the stable API on an ever evolving
representation of biological knowledge.
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libtabixpp-dev
C++ wrapper to tabix indexer (development files)
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Versions of package libtabixpp-dev |
Release | Version | Architectures |
trixie | 1.1.2-2.1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster | 1.0.0-4 | amd64,arm64,armhf |
stretch | 1.0.0-2 | amd64,arm64,armel,i386,mips64el,mipsel,ppc64el |
bookworm | 1.1.2-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 1.1.0-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.1.2-2.1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
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License: DFSG free
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This package provides development headers and static libraries for libtabixpp,
a C++ interface wrapper for Tabix. Tabix is a part of htslib to index tabular
files in which some columns indicate sequence coordinates.
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libthread-pool-dev
C++ header-only thread pool library (devel)
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Versions of package libthread-pool-dev |
Release | Version | Architectures |
stretch-backports | 1.0.0-1~bpo9+1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,s390x |
buster-backports | 2.0.1-4~bpo10+1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
stretch-backports-sloppy | 2.0.1-4~bpo9+1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
bookworm | 4.0.0-1 | amd64,arm64,mips64el,ppc64el,s390x |
trixie | 4.0.0-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 4.0.0-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 3.0.2-1 | all |
buster | 1.0.0-2 | amd64,arm64,armhf,i386 |
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License: DFSG free
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A thread pool is a software design pattern for achieving concurrency of
execution in a computer program. Often also called a replicated workers
or worker-crew model, a thread pool maintains multiple threads
waiting for tasks to be allocated for concurrent execution by the
supervising program.
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libvcflib-dev
C++ library for parsing and manipulating VCF files (development)
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Versions of package libvcflib-dev |
Release | Version | Architectures |
stretch | 1.0.0~rc1+dfsg1-3 | amd64 |
stretch-backports | 1.0.0~rc1+dfsg1-6~bpo9+1 | amd64 |
buster | 1.0.0~rc2+dfsg-2 | amd64 |
buster-backports | 1.0.1+dfsg-3~bpo10+1 | amd64 |
bullseye | 1.0.2+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.0.3+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.0.9+dfsg1-3 | amd64,arm64,mips64el,ppc64el,riscv64 |
sid | 1.0.9+dfsg1-3 | amd64,arm64,mips64el,ppc64el,riscv64 |
upstream | 1.0.12 |
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License: DFSG free
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The Variant Call Format (VCF) is a flat-file, tab-delimited textual format
intended to concisely describe reference-indexed variations between
individuals. VCF provides a common interchange format for the description of
variation in individuals and populations of samples, and has become the defacto
standard reporting format for a wide array of genomic variant detectors.
vcflib provides methods to manipulate and interpret sequence variation as it
can be described by VCF. It is both:
- an API for parsing and operating on records of genomic variation as it can
be described by the VCF format,
- and a collection of command-line utilities for executing complex
manipulations on VCF files.
This package contains the static library and the header files.
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libvibrant6-dev
NCBI libraries for graphic biology applications (development files)
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Versions of package libvibrant6-dev |
Release | Version | Architectures |
trixie | 6.1.20170106+dfsg2-5 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
jessie | 6.1.20120620-8 | amd64,armel,armhf,i386 |
bullseye | 6.1.20170106+dfsg1-9 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
stretch | 6.1.20170106+dfsg1-0+deb9u1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 6.1.20170106+dfsg1-0+deb10u2 | amd64,arm64,armhf,i386 |
bookworm | 6.1.20170106+dfsg1-10 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 6.1.20170106+dfsg2-5 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
Debtags of package libvibrant6-dev: |
biology | nuceleic-acids, peptidic |
devel | lang:c, library |
field | biology, biology:bioinformatics, biology:structural |
interface | 3d, x11 |
role | devel-lib |
science | visualisation |
uitoolkit | motif |
use | analysing, calculating, editing, viewing |
works-with | 3dmodel, biological-sequence |
works-with-format | plaintext, xml |
x11 | library |
|
License: DFSG free
|
Vibrant allows you to develop portable (Motif, MS-Windows, Mac-OS) graphic
biological applications.
|
|
libwfa2-dev
exact gap-affine algorithm (development)
|
Versions of package libwfa2-dev |
Release | Version | Architectures |
sid | 2.3.3-4 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bookworm | 2.3.3-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 2.3.3-4 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
upstream | 2.3.5 |
|
License: DFSG free
|
The wavefront alignment (WFA) algorithm is an exact gap-affine algorithm
that takes advantage of homologous regions between the sequences to
accelerate the alignment process. Unlike to traditional dynamic
programming algorithms that run in quadratic time, the WFA runs in time
O(ns+s^2), proportional to the sequence length n and the alignment score
s, using O(s^2) memory (or O(s) using the ultralow/BiWFA mode).
Moreover, the WFA algorithm exhibits simple computational patterns that
the modern compilers can automatically vectorize for different
architectures without adapting the code. To intuitively illustrate why
the WFA algorithm is so interesting, look at the following figure. The
left panel shows the cells computed by a classical dynamic programming
based algorithm (like Smith-Waterman or Needleman Wunsch). In contrast,
the right panel shows the cells computed by the WFA algorithm to obtain
the same result (i.e., the optimal alignment).
This package contains the static library and the header files.
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libzerg-perl
fast perl module for parsing the output of NCBI BLAST programs
|
Versions of package libzerg-perl |
Release | Version | Architectures |
trixie | 1.0.4-8 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster | 1.0.4-7 | amd64,arm64,armhf,i386 |
bookworm | 1.0.4-8 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
jessie | 1.0.4-3 | amd64,armel,armhf,i386 |
sid | 1.0.4-8 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch | 1.0.4-5 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
bullseye | 1.0.4-8 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
Debtags of package libzerg-perl: |
devel | lang:perl, library |
role | shared-lib |
|
License: DFSG free
|
The Zerg library contains a C/flex lexical scanner for BLAST reports
and a set of supporting functions. It is centered on a "get_token"
function that scans the input for specified lexical elements and, when
one is found, returns its code and value to the user.
It is intended to be fast: for that the authors used flex, which provides
simple regular expression matching and input buffering in the
generated C scanner. And it is intended to be simple in the sense of
providing just a lexical scanner, with no features whose support could
slow down its main function.
|
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libzerg0-dev
development libraries and header files for libzerg
|
Versions of package libzerg0-dev |
Release | Version | Architectures |
buster | 1.0.7-10 | amd64,arm64,armhf,i386 |
bullseye | 1.0.7-11 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.0.7-11 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.0.7-11 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 1.0.7-11 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
jessie | 1.0.7-6 | amd64,armel,armhf,i386 |
stretch | 1.0.7-8 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
Debtags of package libzerg0-dev: |
devel | library |
role | devel-lib |
|
License: DFSG free
|
Zerg is a C library for lexing - lexically scanning - the output of NCBI
BLAST programs.
Based on a
GNU Flex-generated lexical scanner, it runs extremely fast, being especially
useful for processing large volumes of data. Benchmark tests show that Zerg
is over two orders of magnitude faster than some widely used BLAST parsers.
If you need a parser and not only a lexer, check out librostlab-blast.
This package contains the header files and documentation
needed to develop applications with libzerg.
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mcl
|
Versions of package mcl |
Release | Version | Architectures |
trixie | 22-282+ds-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch | 14-137-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 14-137+ds-3 | amd64,arm64,armhf,i386 |
bullseye | 14-137+ds-9 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 22-282+ds-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
jessie | 14-137-1 | amd64,armel,armhf,i386 |
sid | 22-282+ds-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
Debtags of package mcl: |
field | mathematics |
role | program |
|
License: DFSG free
|
The MCL package is an implementation of the MCL algorithm, and offers
utilities for manipulating sparse matrices (the essential data
structure in the MCL algorithm) and conducting cluster experiments.
MCL is currently being used in sciences like biology (protein family
detection, genomics), computer science (node clustering in
Peer-to-Peer networks), and linguistics (text analysis).
The package is enhanced by the following packages:
zoem
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nim-hts-dev
wrapper for hts C library
|
Versions of package nim-hts-dev |
Release | Version | Architectures |
bookworm | 0.3.19+ds-1 | all |
sid | 0.3.25+ds-2 | all |
bullseye | 0.3.14+ds-1 | all |
|
License: DFSG free
|
The hts library is well accepted for the handling of millions of
DNA sequences from what once was the high-throughput sequencing machines
in biological research and medical diagnostics/therapy control.
|
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nim-kexpr-dev
kexpr math expressions for nim
|
Versions of package nim-kexpr-dev |
Release | Version | Architectures |
bullseye | 0.0.2-2 | all |
bookworm | 0.0.2-3 | all |
sid | 0.0.2-3 | all |
|
License: DFSG free
|
This package contains the nim wrapper for Heng Li's kexpr
math expression library.
|
|
nim-lapper-dev
simple, fast interval searches for nim
|
Versions of package nim-lapper-dev |
Release | Version | Architectures |
bookworm | 0.1.7-5 | all |
bullseye | 0.1.7-3 | all |
sid | 0.1.7-5 | all |
|
License: DFSG free
|
This package uses a binary search in a sorted list of intervals along
with knowledge of the longest interval. It works when the size of the
largest interval is smaller than the average distance between intervals.
As that ratio of largest-size::mean-distance increases, the performance
decreases. On realistic (for the author's use-case) data, this is 1000
times faster to query results and >5000 times faster to check for
presence than a brute-force method.
Lapper also has a special case seek method when queries are expected
to be in order. This method uses a cursor to indicate that start of the
last search and does a linear search from that cursor to find matching
intervals. This gives an additional 2-fold speedup over the find
method.
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ont-fast5-api
simple interface to HDF5 files of the Oxford Nanopore .fast5 file format
|
Versions of package ont-fast5-api |
Release | Version | Architectures |
sid | 4.1.1+dfsg-4 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
bookworm | 4.1.1+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
trixie | 4.1.1+dfsg-4 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
upstream | 4.1.3 |
|
License: DFSG free
|
Ont_fast5_api is a simple interface to HDF5 files of the Oxford
Nanopore .fast5 file format.
It provides:
- Concrete implementation of the fast5 file schema using the generic h5py
library
- Plain-english-named methods to interact with and reflect the fast5 file
schema
- Tools to convert between multi_read and single_read formats
- Tools to compress/decompress raw data in files
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|
pyfai
Fast Azimuthal Integration scripts
|
Versions of package pyfai |
Release | Version | Architectures |
bookworm-backports | 2023.9.0-1~bpo12+1 | all |
sid | 2024.05-3 | all |
buster | 0.17.0+dfsg1-3 | all |
buster-backports | 0.19.0+dfsg1-3~bpo10+1 | all |
bookworm | 0.21.3+dfsg1-4 | all |
experimental | 2024.09-1 | all |
jessie | 0.10.2-1 | amd64,armel,armhf,i386 |
stretch-backports | 0.15.0+dfsg1-1~bpo9+1 | all |
stretch | 0.13.0+dfsg-1 | all |
bullseye | 0.20.0+dfsg1-3 | all |
trixie | 2024.05-3 | all |
upstream | 2024.09 |
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License: DFSG free
|
PyFAI is a Python library for azimuthal integration; it allows the conversion
of diffraction images taken with 2D detectors like CCD cameras into X-Ray
powder patterns that can be used by other software like Rietveld refinement
tools (i.e. FullProf), phase analysis or texture analysis.
As PyFAI is a library, its main goal is to be integrated in other tools like
PyMca, LiMa or EDNA. To perform online data analysis, the precise description
of the experimental setup has to be known. This is the reason why PyFAI
includes geometry optimization code working on "powder rings" of reference
samples. Alternatively, PyFAI can also import geometries fitted with other
tools like Fit2D.
PyFAI has been designed to work with any kind of detector with any geometry
(transmission, reflection, off-axis, ...). It uses the Python library FabIO
to read most images taken by diffractometer.
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python3-airr
Data Representation Standard library for antibody and TCR sequences
|
Versions of package python3-airr |
Release | Version | Architectures |
buster | 1.2.1-2 | all |
trixie | 1.5.0-1 | all |
sid | 1.5.0-1 | all |
bullseye | 1.3.1-1 | all |
bookworm | 1.3.1-1 | all |
upstream | 1.5.1 |
|
License: DFSG free
|
This package provides a library by the AIRR community to for describing,
reporting, storing, and sharing adaptive immune receptor repertoire
(AIRR) data, such as sequences of antibodies and T cell receptors
(TCRs). Some specific efforts include:
- The MiAIRR standard for describing minimal information about AIRR
datasets, including sample collection and data processing information.
- Data representations (file format) specifications for storing large
amounts of annotated AIRR data.
- APIs for exposing a common interface to repositories/databases
containing AIRR data.
- A community standard for software tools which will allow conforming
tools to gain community recognition.
This package installs the library for Python 3.
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python3-anndata
annotated gene by sample numpy matrix
|
Versions of package python3-anndata |
Release | Version | Architectures |
sid | 0.10.6-1 | all |
bullseye | 0.7.5+ds-3 | all |
bookworm | 0.8.0-4 | all |
upstream | 0.11.1 |
|
License: DFSG free
|
AnnData provides a scalable way of keeping track of data together
with learned annotations. It is used within Scanpy, for which it was
initially developed. Both packages have been introduced in Genome
Biology (2018).
|
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python3-bcbio-gff
Python3 library to read and write Generic Feature Format
|
Versions of package python3-bcbio-gff |
Release | Version | Architectures |
trixie | 0.7.1-2 | all |
bookworm | 0.6.9-1 | all |
sid | 0.7.1-2 | all |
bullseye | 0.6.6-3 | all |
|
License: DFSG free
|
A Python library to read and write Generic Feature Format (GFF).
Generic Feature Format (GFF) is a biological sequence file format for
representing features and annotations on sequences. It is a tab
delimited format, making it accessible to biologists and editable in
text editors and spreadsheet programs. It is also well defined and can
be parsed via automated programs. GFF files are available from many of
the large sequencing and annotation centers.
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python3-bioframe
library to enable flexible, scalable operations on genomic interval dataframes
|
Versions of package python3-bioframe |
Release | Version | Architectures |
bookworm | 0.3.3-2 | all |
trixie | 0.4.1-1 | all |
sid | 0.4.1-1 | all |
upstream | 0.7.2 |
|
License: DFSG free
|
Building bioframe directly on top of pandas enables immediate access
to a rich set of dataframe operations. Working in Python enables
rapid visualization (e.g. matplotlib, seaborn) and iteration of
genomic analyses.
Bioframe implements a variety of genomic interval operations directly on
dataframes. Bioframe also includes functions for loading diverse genomic
data formats, and performing operations on special classes of genomic
intervals, including chromosome arms and fixed size bins.
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python3-biom-format
Biological Observation Matrix (BIOM) format (Python 3)
|
Versions of package python3-biom-format |
Release | Version | Architectures |
bookworm | 2.1.12-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 2.1.16-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 2.1.10-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
stretch | 2.1.5+dfsg-7 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
buster | 2.1.7+dfsg-2 | amd64,arm64,armhf,i386 |
sid | 2.1.16-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
|
License: DFSG free
|
The BIOM file format (canonically pronounced biome) is designed to be a
general-use format for representing biological sample by observation
contingency tables. BIOM is a recognized standard for the Earth
Microbiome Project and is a Genomics Standards Consortium candidate
project.
The BIOM format is designed for general use in broad areas of
comparative -omics. For example, in marker-gene surveys, the primary use
of this format is to represent OTU tables: the observations in this case
are OTUs and the matrix contains counts corresponding to the number of
times each OTU is observed in each sample. With respect to metagenome
data, this format would be used to represent metagenome tables: the
observations in this case might correspond to SEED subsystems, and the
matrix would contain counts corresponding to the number of times each
subsystem is observed in each metagenome. Similarly, with respect to
genome data, this format may be used to represent a set of genomes: the
observations in this case again might correspond to SEED subsystems, and
the counts would correspond to the number of times each subsystem is
observed in each genome.
This package provides the BIOM format library for the Python 3 interpreter.
Please cite:
Daniel McDonald, Jose C. Clemente, Justin Kuczynski, Jai R. Rideout, Jesse Stombaugh, Doug Wendel, Andreas Wilke, Susan Huse, John Hufnagle, Folker Meyer, Rob Knight and J. G. Caporaso:
The Biological Observation Matrix (BIOM) format or: how I learned to stop worrying and love the ome-ome.
(eprint)
GigaScience
1:7
(2012)
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python3-biomaj3
BioMAJ workflow management library
|
Versions of package python3-biomaj3 |
Release | Version | Architectures |
buster | 3.1.6-1 | all |
bookworm | 3.1.23-1 | all |
bullseye | 3.1.18-2 | all |
trixie | 3.1.24-2 | all |
sid | 3.1.24-2 | all |
|
License: DFSG free
|
BioMAJ downloads remote data banks, checks their status and applies
transformation workflows, with consistent state, to provide ready-to-use
data for biologists and bioinformaticians. For example, it can transform
original FASTA files into BLAST indexes. It is very flexible and its
post-processing facilities can be extended very easily.
BioMAJ3 is a rewrite of BioMAJ v1.x, see online documentation for migration.
This package contains the library to manage the workflow update in BioMAJ3,
it is managed via python3-biomaj3-daemon (for microservices remote operations)
or biomaj3-cli (local or remote) packages
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python3-biopython
Python3 library for bioinformatics
|
Versions of package python3-biopython |
Release | Version | Architectures |
bullseye | 1.78+dfsg-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.80+dfsg-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.84+dfsg-4 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch | 1.68+dfsg-3 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
sid | 1.84+dfsg-4 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
jessie | 1.64+dfsg-5 | amd64,armel,armhf,i386 |
buster | 1.73+dfsg-1 | amd64,arm64,armhf,i386 |
|
License: DFSG free
|
The Biopython Project is an international association
of developers of freely available Python tools for
computational molecular biology.
It is a distributed collaborative effort to develop Python3
libraries and applications which address the needs of
current and future work in bioinformatics. The source code
is made available under the Biopython License, which is
extremely liberal and compatible with almost every license in
the world. The project works along with the Open Bioinformatics
Foundation, who generously provide web and CVS space for
the project.
Please cite:
Peter J. A. Cock, Tiago Antao, Jeffrey T. Chang, Brad A. Chapman, Cymon J. Cox, Andrew Dalke, Iddo Friedberg, Thomas Hamelryck, Frank Kauff, Bartek Wilczynski and Michiel J. L. de Hoon:
Biopython: freely available Python tools for computational molecular biology and bioinformatics.
(PubMed,eprint)
Bioinformatics
25(11):1422-1423
(2009)
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python3-biotools
??? missing short description for package python3-biotools :-(
|
Versions of package python3-biotools |
Release | Version | Architectures |
sid | 1.2.12-6 | all |
bookworm | 1.2.12-5 | all |
stretch-backports | 1.2.12-3~bpo9+1 | all |
bullseye | 1.2.12-5 | all |
buster | 1.2.12-3 | all |
trixie | 1.2.12-6 | all |
|
License: DFSG free
|
Please cite:
Rebecca Bart, Megan Cohn, Andrew Kassen, Emily J. McCallum, Mikel Shybut, Annalise Petriello, Ksenia Krasileva, Douglas Dahlbeck, Cesar Medina, Titus Alicai, Lava Kumar, Leandro M. Moreira, Júlio Rodrigues Neto, Valerie Verdier, María Angélica Santana, Nuttima Kositcharoenkul, Hervé Vanderschuren, Wilhelm Gruissem, Adriana Bernal and Brian J. Staskawicz:
High-throughput genomic sequencing of cassava bacterial blight strains identifies conserved effectors to target for durable resistance.
(PubMed)
PNAS
109(28):E1972-9
(2012)
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python3-bx
library to manage genomic data and its alignment
|
Versions of package python3-bx |
Release | Version | Architectures |
sid | 0.13.0-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 0.8.9-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 0.9.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 0.8.2-1 | amd64,arm64,armhf,i386 |
trixie | 0.13.0-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
|
License: DFSG free
|
The bx-python project is a Python3 library and associated set of scripts to
allow for rapid implementation of genome scale analyses. The library contains
a variety of useful modules, but the particular strengths are:
- Classes for reading and working with genome-scale multiple local
alignments (in MAF, AXT, and LAV formats)
- Generic data structure for indexing on disk files that contain blocks of
data associated with intervals on various sequences (used, for example, to
provide random access to individual alignments in huge files; optimized
for use over network filesystems)
- Data structures for working with intervals on sequences
- "Binned bitsets" which act just like chromosome sized bit arrays, but
lazily allocate regions and allow large blocks of all set or all unset
bits to be stored compactly
- "Intersecter" for performing fast intersection tests that preserve both
query and target intervals and associated annotation
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python3-cgecore
Python3 module for the Center for Genomic Epidemiology
|
Versions of package python3-cgecore |
Release | Version | Architectures |
sid | 1.5.6+ds-2 | all |
bullseye | 1.5.6+ds-1 | all |
trixie | 1.5.6+ds-2 | all |
bookworm | 1.5.6+ds-1 | all |
upstream | 2.0.0 |
|
License: DFSG free
|
This Python3 module contains classes and functions needed to run the
service wrappers and pipeline scripts developed by the Center for
Genomic Epidemiology.
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python3-cigar
manipulate SAM cigar strings
|
Versions of package python3-cigar |
Release | Version | Architectures |
trixie | 0.1.3-2 | all |
bookworm | 0.1.3-2 | all |
sid | 0.1.3-2 | all |
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License: DFSG free
|
Cigar is a simple Python3 library for dealing with cigar strings. the most
useful feature now is soft-masking from left or right. This allows one to
adjust a SAM record only by changing the cigar string to soft-mask a number
of bases such that the rest of the SAM record (pos, tlen, etc.) remain valid,
but downstream tools will not consider the soft-masked bases in further
analysis.
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python3-cobra
constraint-based modeling of biological networks with Python 3
|
Versions of package python3-cobra |
Release | Version | Architectures |
sid | 0.29.1-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el |
bullseye | 0.21.0-1 | amd64,arm64,armel,armhf,i386,ppc64el |
bookworm | 0.26.2-1 | amd64,arm64,armel,armhf,i386,ppc64el |
trixie | 0.29.1-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el |
buster | 0.14.1-1 | amd64,arm64,armhf,i386 |
stretch | 0.5.9-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
|
License: DFSG free
|
COnstraint-Based Reconstruction and Analysis (COBRA) methods are widely
used for genome-scale modeling of metabolic networks in both prokaryotes
and eukaryotes. COBRApy is a constraint-based modeling package that is
designed to accommodate the biological complexity of the next generation
of COBRA models and provides access to commonly used COBRA methods, such
as flux balance analysis, flux variability analysis, and gene deletion
analyses.
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python3-cogent3
framework for genomic biology
|
Versions of package python3-cogent3 |
Release | Version | Architectures |
sid | 2024.5.7a1+dfsg-3 | amd64,arm64,mips64el,ppc64el |
bookworm | 2023.2.12a1+dfsg-2+deb12u1 | amd64,arm64,mips64el,ppc64el,s390x |
bullseye | 2020.12.21a+dfsg-4+deb11u1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 2023.12.15a1+dfsg-1 | s390x |
upstream | 2024.12.19a1 |
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License: DFSG free
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PyCogent is a software library for genomic biology. It is a fully
integrated and thoroughly tested framework for:
- controlling third-party applications,
- devising workflows; querying databases,
- conducting novel probabilistic analyses of biological sequence
evolution, and
- generating publication quality graphics.
It is distinguished by many unique built-in capabilities (such as true codon
alignment) and the frequent addition of entirely new methods for the analysis
of genomic data.
Please cite:
Rob Knight, Peter Maxwell, Amanda Birmingham, Jason Carnes, J Gregory Caporaso, Brett C Easton, Michael Eaton, Micah Hamady, Helen Lindsay, Zongzhi Liu, Catherine Lozupone, Daniel McDonald, Michael Robeson, Raymond Sammut, Sandra Smit, Matthew J Wakefield, Jeremy Widmann, Shandy Wikman, Stephanie Wilson, Hua Ying and Gavin A Huttley:
PyCogent: a toolkit for making sense from sequence.
(PubMed,eprint)
Genome Biology
8(8):R171
(2007)
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python3-cooler
library for a sparse, compressed, binary persistent storage
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Versions of package python3-cooler |
Release | Version | Architectures |
trixie | 0.10.2-1 | amd64,arm64,mips64el,ppc64el,riscv64 |
bookworm | 0.9.1-1 | amd64,arm64,mips64el,ppc64el |
sid | 0.10.2-1 | amd64,arm64,mips64el,ppc64el,riscv64 |
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License: DFSG free
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Cooler is a support library for a sparse, compressed, binary persistent
storage format, also called cooler, used to store genomic interaction
data, such as Hi-C contact matrices.
The cooler file format is an implementation of a genomic matrix data
model using HDF5 as the container format. The cooler package includes a
suite of command line tools and a Python API to facilitate creating,
querying and manipulating cooler files.
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python3-corepywrap
library that exports C++ mmCIF accessors to Python3
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Versions of package python3-corepywrap |
Release | Version | Architectures |
bookworm | 1.005-11 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.005-12 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 1.005-13 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.005-10 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
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License: DFSG free
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The RCSB Core Wrapper library was developed to provide an object-oriented
application interface to information in mmCIF format. It includes several
classes for accessing data dictionaries and mmCIF format data files.
This library provides Python3 bindings for librcsb-core-wrapper.
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python3-csb
Python framework for structural bioinformatics (Python3 version)
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Versions of package python3-csb |
Release | Version | Architectures |
buster | 1.2.5+dfsg-3 | all |
sid | 1.2.5+dfsg-10 | all |
trixie | 1.2.5+dfsg-10 | all |
jessie | 1.2.3+dfsg-1 | all |
bookworm | 1.2.5+dfsg-8 | all |
stretch | 1.2.3+dfsg-3 | all |
bullseye | 1.2.5+dfsg-5 | all |
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License: DFSG free
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Computational Structural Biology Toolbox (CSB) is a Python class
library for reading, storing and analyzing biomolecular structures
in a variety of formats with rich support for statistical analyses.
CSB is designed for reusability and extensibility and comes with a clean,
well-documented API following good object-oriented engineering practice.
This is the Python3 version of the package.
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python3-cutadapt
Clean biological sequences from high-throughput sequencing reads (Python 3)
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Versions of package python3-cutadapt |
Release | Version | Architectures |
stretch | 1.12-2 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
sid | 4.7-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
buster | 1.18-1 | amd64,arm64,armhf,i386 |
bookworm | 4.2-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 3.2-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 4.7-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
upstream | 5.0 |
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License: DFSG free
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Cutadapt helps with biological sequence clean tasks by finding the adapter
or primer sequences in an error-tolerant way.
It can also modify and filter reads in various ways.
Adapter sequences can contain IUPAC wildcard characters.
Also, paired-end reads and even colorspace data is supported.
If you want, you can also just demultiplex your input data, without removing
adapter sequences at all.
This package contains the Python 3 module.
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python3-cyvcf2
VCF parser based on htslib (Python 3)
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Versions of package python3-cyvcf2 |
Release | Version | Architectures |
bullseye | 0.30.4-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 0.10.4-1 | amd64,arm64,armhf,i386 |
sid | 0.31.1-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 0.31.1-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 0.30.18-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
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License: DFSG free
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This modules allows fast parsing of VCF and BCF including region-queries
with Python. This is essential for efficient analyses of nucleotide
variation with Python on high-throughput sequencing data.
cyvcf2 is a cython wrapper around htslib. Attributes like
variant.gt_ref_depths return a numpy array directly so they are
immediately ready for downstream use.
This package installs the library for Python 3.
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python3-deeptools
platform for exploring biological deep-sequencing data
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Versions of package python3-deeptools |
Release | Version | Architectures |
bullseye | 3.5.0-1 | all |
sid | 3.5.5+dfsg-1 | all |
trixie | 3.5.5+dfsg-1 | all |
bookworm | 3.5.1-3 | all |
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License: DFSG free
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Aiming for compatibility with the Galaxy worklfow environment, but
also independently contributing to a series of workflows in
genomics, this package provides a series of tools to address
common tasks for the processing of high-throughput DNA/RNA sequencing.
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python3-deeptoolsintervals
handlig GTF-like sequence-associated interal-annotation
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Versions of package python3-deeptoolsintervals |
Release | Version | Architectures |
bookworm | 0.1.9-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 0.1.9-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 0.1.9-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 0.1.9-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
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License: DFSG free
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Regions in biological sequences are described (annotated) as genes,
transcription factor binding sites, low complexity, ... whatever
biological research brings.
This package supports the efficienct operation with this information.
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python3-dendropy
DendroPy Phylogenetic Computing Library (Python 3)
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Versions of package python3-dendropy |
Release | Version | Architectures |
stretch | 4.2.0+dfsg-1 | all |
bookworm | 4.5.2-1 | all |
trixie | 4.6.1-2 | all |
buster | 4.4.0-1 | all |
bullseye | 4.5.1-1 | all |
sid | 4.6.1-2 | all |
upstream | 5.0.1 |
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License: DFSG free
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DendroPy is a Python library for phylogenetic computing. It provides
classes and functions for the simulation, processing, and manipulation
of phylogenetic trees and character matrices, and supports the reading
and writing of phylogenetic data in a range of formats, such as NEXUS,
NEWICK, NeXML, Phylip, FASTA, etc. Application scripts for performing
some useful phylogenetic operations, such as data conversion and tree
posterior distribution summarization, are also distributed and installed
as part of the library. DendroPy can thus function as a stand-alone
library for phylogenetics, a component of more complex multi-library
phyloinformatic pipelines, or as a scripting “glue” that assembles and
drives such pipelines.
This package provides python3 modules.
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python3-dnaio
Python 3 library for fast parsing of FASTQ and FASTA files
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Versions of package python3-dnaio |
Release | Version | Architectures |
sid | 1.2.3-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
trixie | 1.2.3-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
bookworm | 0.10.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 0.5.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
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License: DFSG free
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dnaio is a Python 3 library for fast parsing of FASTQ and also FASTA files.
The code was previously part of the cutadapt tool and has been improved
since it has been split out.
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python3-ete3
Python Environment for (phylogenetic) Tree Exploration - Python 3.X
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Versions of package python3-ete3 |
Release | Version | Architectures |
bullseye | 3.1.2+dfsg-2 | all |
sid | 3.1.3+dfsg-3 | all |
trixie | 3.1.3+dfsg-3 | all |
bookworm | 3.1.2+dfsg-3 | all |
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License: DFSG free
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The Environment for Tree Exploration (ETE) is a Python programming
toolkit that assists in the recontruction, manipulation, analysis and
visualization of phylogenetic trees (although clustering trees or any
other tree-like data structure are also supported).
ETE is currently developed as a tool for researchers working in
phylogenetics and genomics. If you use ETE for a published work,
please cite:
Visit http://etetoolkit.org for more info.
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python3-fast5
library for reading Oxford Nanopore Fast5 files -- Python 3
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Versions of package python3-fast5 |
Release | Version | Architectures |
stretch | 0.5.8-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
sid | 0.6.5-8 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 0.6.5-8 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch-backports | 0.6.5-1~bpo9+1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
bookworm | 0.6.5-7 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 0.6.5-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 0.6.5-2 | amd64,arm64,armhf,i386 |
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License: DFSG free
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A lightweight C++11 library to read raw signal data from Oxford
Nanopore's FAST5 files.
This package provides the Python 3 library
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python3-freecontact
fast protein contact predictor - binding for Python3
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Versions of package python3-freecontact |
Release | Version | Architectures |
bookworm | 1.1-6 | amd64,arm64,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.1-8 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 1.1-8 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster | 1.1-4 | amd64,arm64,armhf,i386 |
bullseye | 1.1-5 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
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License: DFSG free
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FreeContact is a protein residue contact predictor optimized for speed.
Its input is a multiple sequence alignment. FreeContact can function as an
accelerated drop-in for the published contact predictors
EVfold-mfDCA of DS. Marks (2011) and
PSICOV of D. Jones (2011).
FreeContact is accelerated by a combination of vector instructions, multiple
threads, and faster implementation of key parts.
Depending on the alignment, 8-fold or higher speedups are possible.
A sufficiently large alignment is required for meaningful results.
As a minimum, an alignment with an effective (after-weighting) sequence count
bigger than the length of the query sequence should be used. Alignments with
tens of thousands of (effective) sequences are considered good input.
jackhmmer(1) from the hmmer package, or hhblits(1) from hhsuite
can be used to generate the alignments, for example.
This package contains the Python3 binding.
Please cite:
László Kaján, Thomas A. Hopf, Matúš Kalaš, Debora S. Marks and Burkhard Rost:
FreeContact: ...
BMC Bioinformatics
(201?)
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python3-gfapy
flexible and extensible software library for handling sequence graphs
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Versions of package python3-gfapy |
Release | Version | Architectures |
bullseye | 1.1.0+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 1.0.0+dfsg-3 | amd64,arm64,armhf,i386 |
bookworm | 1.2.3+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.2.3+dfsg-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 1.2.3+dfsg-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
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License: DFSG free
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The Graphical Fragment Assembly (GFA) are formats for the representation of
sequence graphs, including assembly, variation and splicing graphs. Two
versions of GFA have been defined (GFA1 and GFA2) and several sequence
analysis programs have been adopting the formats as an interchange format,
which allow the user to easily combine different sequence analysis tools.
This library implements the GFA1 and GFA2 specification. It is possible to
create a Gfa object from a file in the GFA format or from scratch, to
enumerate the graph elements (segments, links, containments, paths and header
lines), to traverse the graph (by traversing all links outgoing from or
incoming to a segment), to search for elements (e.g. which links connect two
segments) and to manipulate the graph (e.g. to eliminate a link or a segment
or to duplicate a segment distributing the read counts evenly on the copies).
The GFA format can be easily extended by users by defining own custom tags
and record types. In Gfapy, it is easy to write extensions modules, which
allow one to define custom record types and datatypes for the parsing and
validation of custom fields. The custom lines can be connected, using
references, to each other and to lines of the standard record types.
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python3-gffutils
Work with GFF and GTF files in a flexible database framework
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Versions of package python3-gffutils |
Release | Version | Architectures |
bullseye | 0.10.1-2 | all |
buster | 0.9-1 | all |
sid | 0.13-1 | all |
trixie | 0.13-1 | all |
bookworm | 0.11.1-3 | all |
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License: DFSG free
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A Python package for working with and manipulating the GFF and GTF format
files typically used for genomic annotations. Files are loaded into a
sqlite3 database, allowing much more complex manipulation of hierarchical
features (e.g., genes, transcripts, and exons) than is possible with
plain-text methods alone.
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python3-gtfparse
parser for gene transfer format (aka GFF2)
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Versions of package python3-gtfparse |
Release | Version | Architectures |
sid | 1.3.0+ds-1 | all |
trixie | 1.3.0+ds-1 | all |
bookworm | 1.3.0+ds-1 | all |
upstream | 2.5.0 |
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License: DFSG free
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You find a gene in the genome? Or a feature about it?
The gene transfer format (GTF, identical to GFF2)
allows your program or your database to exchange
this information so it can be presented with genome
browsers or used e.g. as a selection for other features
like nucleotide variants.
This package provides a parser for GTF/GFF2 files, i.e.
sets of routines that read that file and support the
computational interpretation of these data.
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python3-htseq
Python3 high-throughput genome sequencing read analysis utilities
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Versions of package python3-htseq |
Release | Version | Architectures |
bullseye | 0.13.5-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
trixie | 2.0.9+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
sid | 2.0.9+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
bookworm | 1.99.2-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
buster | 0.11.2-1 | amd64,arm64 |
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License: DFSG free
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HTSeq can be used to performing a number of common analysis tasks
when working with high-throughput genome sequencing reads:
- Getting statistical summaries about the base-call quality scores to
study the data quality.
- Calculating a coverage vector and exporting it for visualization in
a genome browser.
- Reading in annotation data from a GFF file.
- Assigning aligned reads from an RNA-Seq experiments to exons and
genes.
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python3-intervaltree-bio
Interval tree convenience classes for genomic data -- Python 3 library
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Versions of package python3-intervaltree-bio |
Release | Version | Architectures |
sid | 1.0.1-4 | all |
trixie | 1.0.1-4 | all |
stretch | 1.0.1-1 | all |
buster | 1.0.1-3 | all |
bookworm | 1.0.1-4 | all |
bullseye | 1.0.1-4 | all |
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License: DFSG free
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Convenience classes for loading UCSC genomic annotation records into
a set of interval tree data structures.
This package provides the Python 3 library.
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python3-kineticstools
detection of DNA modifications (Python 3 library)
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Versions of package python3-kineticstools |
Release | Version | Architectures |
trixie | 0.6.1+git20220223.1326a4d+dfsg-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
sid | 0.6.1+git20220223.1326a4d+dfsg-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
bullseye | 0.6.1+git20200729.e3723e0+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
bookworm | 0.6.1+git20220223.1326a4d+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
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License: DFSG free
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Tools for detecting DNA modifications from single molecule, real-time (SMRT®)
sequencing data. This tool implements the P_ModificationDetection module in
SMRT® Portal, used by the RS_Modification_Detection and
RS_Modifications_and_Motif_Detection protocol. Researchers interested in
understanding or extending the modification detection algorithms can use these
tools as a starting point.
This package is part of the SMRTAnalysis suite and contains the backend
Python 3 library.
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python3-loompy
access loom formatted files for bioinformatics
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Versions of package python3-loompy |
Release | Version | Architectures |
bookworm | 3.0.7+dfsg-2 | amd64,arm64,mips64el,ppc64el,s390x |
sid | 3.0.7+dfsg-3 | amd64,arm64,mips64el,ppc64el,s390x |
upstream | 3.0.8 |
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License: DFSG free
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Loom is an efficient file format for very large omics datasets,
consisting of a main matrix, optional additional layers, a variable
number of row and column annotations. Loom also supports sparse
graphs. Loom files are used to store single-cell gene expression data:
the main matrix contains the actual expression values (one column per
cell, one row per gene); row and column annotations contain metadata
for genes and cells, such as Name, Chromosome, Position (for genes),
and Strain, Sex, Age (for cells).
Loom files (.loom) are created in the HDF5 file format, which supports
an internal collection of numerical multidimensional datasets. HDF5
is supported by many computer languages, including Java, MATLAB,
Mathematica, Python, R, and Julia. .loom files are accessible from any
language that supports HDF5.
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python3-mirtop
annotate miRNAs with a standard mirna/isomir naming (Python 3)
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Versions of package python3-mirtop |
Release | Version | Architectures |
trixie | 0.4.28-2 | all |
bullseye | 0.4.23-2 | all |
bookworm | 0.4.25-2 | all |
sid | 0.4.28-2 | all |
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License: DFSG free
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The main goal of this project is to create a reflection group on metazoan
microRNAs (miRNAs), open to all interested researchers, to identify blockages
and develop standards and guidelines to improve miRNA research, resources and
communication. This can go through the use of standardized file formats, gene
and variants nomenclature guidelines, and advancements in miRNA biology
understanding. The group will eventually also aim at expanding its breadth to
the development of novel tools, data resources, and best-practices guidelines
to benefit the scientific community by providing high confidence validated
research and analysis strategies, regardless the expertise in this field.
This package provides the Python modules for mirtop to execute correctly.
Please cite:
Thomas Desvignes, Karen Eilbeck, Ioannis S. Vlachos, Bastian Fromm, Yin Lu, Marc K. Halushka, Michael Hackenberg, Gianvito Urgese, Elisa Ficarra, Shruthi Bandyadka, Jason Sydes, Peter Batzel, John H. Postlethwait, Phillipe Loher, Eric Londin, Aristeidis G. Telonis, Isidore Rigoutsos and Lorena Pantano Rubino:
miRTOP: An open source community project for the development of a unified format file for miRNA data [version 1; not peer reviewed].
(eprint)
F1000Research
7(ISCB Comm. J.):953 (Slides)
(2018)
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python3-nanoget
extract information from Oxford Nanopore sequencing data and alignments
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Versions of package python3-nanoget |
Release | Version | Architectures |
trixie | 1.19.3-1 | all |
bullseye | 1.12.2-4 | all |
sid | 1.19.3-1 | all |
bookworm | 1.16.1-2 | all |
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License: DFSG free
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The Python3 module nanoget provides functions to extract useful metrics
from Oxford Nanopore sequencing reads and alignments.
Data can be presented in the following formats, using the following functions:
- sorted bam file process_bam(bamfile, threads)
- standard fastq file process_fastq_plain(fastqfile, 'threads')
- fastq file with metadata from MinKNOW or Albacore
process_fastq_rich(fastqfile)
- sequencing_summary file generated by Albacore
process_summary(sequencing_summary.txt, 'readtype')
Fastq files can be compressed using gzip, bzip2 or bgzip. The data is
returned as a pandas DataFrame with standardized headernames for
convenient extraction. The functions perform logging while being called
and extracting data.
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python3-ngs
Next Generation Sequencing language Bindings (Python3 bindings)
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Versions of package python3-ngs |
Release | Version | Architectures |
trixie | 3.0.9+dfsg-7 | all |
stretch | 1.3.0-2 | amd64,i386 |
buster | 2.9.3-1 | amd64,i386 |
bullseye | 2.10.9-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 3.0.3+dfsg-6~deb12u1 | all |
sid | 3.0.9+dfsg-7 | all |
upstream | 3.1.1 |
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License: DFSG free
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NGS is a new, domain-specific API for accessing reads, alignments and
pileups produced from Next Generation Sequencing. The API itself is
independent from any particular back-end implementation, and supports
use of multiple back-ends simultaneously. It also provides a library for
building new back-end "engines". The engine for accessing SRA data is
contained within the sister repository ncbi-vdb.
The API is currently expressed in C++, Java and Python languages. The
design makes it possible to maintain a high degree of similarity between
the code in one language and code in another - especially between C++
and Java.
Python3 bindings.
Please cite:
Rasko Leinonen, Ruth Akhtar, Ewan Birney, James Bonfield, Lawrence Bower, Matt Corbett, Ying Cheng, Fehmi Demiralp, Nadeem Faruque, Neil Goodgame, Richard Gibson, Gemma Hoad, Christopher Hunter, Mikyung Jang, Steven Leonard, Quan Lin, Rodrigo Lopez, Michael Maguire, Hamish McWilliam, Sheila Plaister, Rajesh Radhakrishnan, Siamak Sobhany, Guy Slater, Petra Ten Hoopen, Franck Valentin, Robert Vaughan, Vadim Zalunin, Daniel Zerbino and Guy Cochrane:
Improvements to services at the European Nucleotide Archive.
(PubMed,eprint)
Nucleic Acids Research
38(Database issue):D39-45
(2010)
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python3-pairix
1D/2D indexing and querying with a pair of genomic coordinates
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Versions of package python3-pairix |
Release | Version | Architectures |
sid | 0.3.8-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
bookworm | 0.3.7-6 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
trixie | 0.3.8-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
bullseye | 0.3.7-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
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License: DFSG free
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Pairix is a tool for indexing and querying on a block-compressed text
file containing pairs of genomic coordinates.
Pairix is a stand-alone C program that was written on top of tabix as a
tool for the 4DN-standard pairs file format describing Hi-C data:
pairs_format_specification.md
However, Pairix can be used as a generic tool for indexing and querying
any bgzipped text file containing genomic coordinates, for either 2D- or
1D- indexing and querying.
For example: given the custom text file below, you want to extract
specific lines from the Pairs file further below. An awk command would
read the Pairs file from beginning to end. Pairix creates an index and
uses it to access the file from a relevant position by taking advantage
of bgzf compression, allowing for a fast query on large files.
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python3-pangolearn
store of the trained model for pangolin to access
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Versions of package python3-pangolearn |
Release | Version | Architectures |
sid | 2022-07-09+dfsg-2 | all |
bookworm | 2022-07-09+dfsg-2 | all |
trixie | 2022-07-09+dfsg-2 | all |
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License: DFSG free
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Pangolin runs a multinomial logistic regression model trained against
lineage assignments based on GISAID data.
Legacy pangolin runs using a guide tree and alignment hosted at
cov-lineages/lineages. Some of this data is sourced from GISAID, but
anonymised and encrypted to fit with guidelines. Appropriate permissions
have been given and acknowledgements for the teams that have worked to
provide the original SARS-CoV-2 genome sequences to GISAID are also
hosted here.
This package contains the store of the trained model for pangolin.
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python3-parasail
Python3 bindings for the parasail C library
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Versions of package python3-parasail |
Release | Version | Architectures |
trixie | 1.3.3-1 | all |
bookworm | 1.3.3-1 | all |
bullseye | 1.2.3-1 | all |
sid | 1.3.3-1 | all |
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License: DFSG free
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This package provides the Python3 bindings for parasail.
Parasail is a SIMD C library containing implementations of the
Smith-Waterman, Needleman-Wunsch, and various semi-global pairwise
sequence alignment algorithm.
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python3-pbcommand
common command-line interface for Pacific Biosciences analysis modules
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Versions of package python3-pbcommand |
Release | Version | Architectures |
trixie | 2.1.1+git20220616.3f2e6c2-3 | all |
bookworm | 2.1.1+git20220616.3f2e6c2-2 | all |
bullseye | 2.1.1+git20201023.cc0ed3d-1 | all |
sid | 2.1.1+git20220616.3f2e6c2-3 | all |
upstream | 2.1.1+git20231020.28d1635 |
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License: DFSG free
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To integrate with the pbsmrtpipe workflow engine, one must to be able to
generate a Tool Contract and to be able to run from a Resolved Tool Contract.
A Tool Contract contains the metadata of the exe, such as the file types of
inputs, outputs and options.
There are two principal use cases, first wrapping/calling Python functions that
have been defined in external Python 3 packages, or scripts. Second, creating a
CLI tool that supports emitting tool contracts, running resolved tool contracts
and complete argparse-style CLI.
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python3-pbconsensuscore
algorithms for PacBio multiple sequence consensus -- Python 3
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Versions of package python3-pbconsensuscore |
Release | Version | Architectures |
sid | 1.1.1+dfsg-7 | amd64,arm64,i386,mips64el,ppc64el,riscv64 |
bullseye | 1.1.1+dfsg-2 | amd64,i386 |
buster | 1.1.1+dfsg-1 | amd64,i386 |
bookworm | 1.1.1+dfsg-4 | amd64,i386 |
stretch | 1.0.2-2 | amd64,i386 |
trixie | 1.1.1+dfsg-7 | amd64,arm64,i386,mips64el,ppc64el,riscv64 |
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License: DFSG free
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ConsensusCore is a library of C++ algorithms for Pacific Biosciences
multiple sequence consensus that powers Quiver (Python) and ConsensusTools
(.NET). This library primarily exists as the backend for GenomicConsensus,
which implements Quiver.
This package is part of the SMRT Analysis suite.
It provides the Python3 bindings.
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python3-pbcore
Python 3 library for processing PacBio data files
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Versions of package python3-pbcore |
Release | Version | Architectures |
bullseye | 1.7.1+git20200430.a127b1e+dfsg-1 | all |
bookworm | 2.1.2+dfsg-5 | all |
trixie | 2.1.2+dfsg-9 | all |
sid | 2.1.2+dfsg-10 | all |
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License: DFSG free
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The pbcore package provides Python modules for processing Pacific Biosciences
data files and building PacBio bioinformatics applications. These modules
include tools to read/write PacBio data formats, sample data files for
testing and debugging, base classes, and utilities for building bioinformatics
applications.
This package is part of the SMRTAnalysis suite.
This is the Python 3 module.
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python3-peptidebuilder
generate atomic oligopeptide 3D structure from sequence
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Versions of package python3-peptidebuilder |
Release | Version | Architectures |
sid | 1.1.0-3 | all |
bullseye | 1.1.0-2 | all |
bookworm | 1.1.0-3 | all |
trixie | 1.1.0-3 | all |
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License: DFSG free
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PeptideBuilder is a simple Python library to generate model peptides.
Typically on daisychains a few residues in e.g. biopython, and so
does PeptideBuilder, but it does it right.
Parameters like the backbone formation can be specified ab initio,
rotamers/energy minimisation is left to respective specialist tools.
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python3-presto
toolkit for processing B and T cell sequences (Python3 module)
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Versions of package python3-presto |
Release | Version | Architectures |
bookworm | 0.7.1-1 | all |
bullseye | 0.6.2-1 | all |
sid | 0.7.2-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 0.7.2-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster | 0.5.10-1 | all |
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License: DFSG free
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pRESTO is a toolkit for processing raw reads from high-throughput
sequencing of B cell and T cell repertoires.
Dramatic improvements in high-throughput sequencing technologies now
enable large-scale characterization of lymphocyte repertoires, defined
as the collection of trans-membrane antigen-receptor proteins located on
the surface of B cells and T cells. The REpertoire Sequencing TOolkit
(pRESTO) is composed of a suite of utilities to handle all stages
of sequence processing prior to germline segment assignment. pRESTO
is designed to handle either single reads or paired-end reads. It
includes features for quality control, primer masking, annotation of
reads with sequence embedded barcodes, generation of unique molecular
identifier (UMI) consensus sequences, assembly of paired-end reads and
identification of duplicate sequences. Numerous options for sequence
sorting, sampling and conversion operations are also included.
This package provides the presto Python3 module.
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python3-propka
heuristic pKa calculations with ligands (Python 3)
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Versions of package python3-propka |
Release | Version | Architectures |
trixie | 3.5.1-2 | all |
bookworm | 3.5.0-1 | all |
sid | 3.5.1-2 | all |
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License: DFSG free
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PROPKA predicts the pKa values of ionizable groups in proteins (version 3.0)
and protein-ligand complexes (version 3.1 and later) based on the 3D structure.
For proteins without ligands both versions should produce the same result.
This package installs the library for Python 3.
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python3-py2bit
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Versions of package python3-py2bit |
Release | Version | Architectures |
bullseye | 0.3.0-6 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
trixie | 0.3.2-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
sid | 0.3.2-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
bookworm | 0.3.1-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
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License: DFSG free
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From https://genome.ucsc.edu/FAQ/FAQformat.html#format7:
A .2bit file stores multiple DNA sequences (up to 4 Gb total) in a
compact randomly-accessible format. The file contains masking information
as well as the DNA itself.
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python3-pyabpoa
adaptive banded Partial Order Alignment - python3 module
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Versions of package python3-pyabpoa |
Release | Version | Architectures |
sid | 1.5.3-1 | amd64,arm64,ppc64el |
bookworm | 1.4.1-3 | amd64,arm64,ppc64el |
trixie | 1.5.3-1 | amd64,arm64,ppc64el |
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License: DFSG free
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abPOA is an extended version of Partial Order Alignment (POA) that performs
adaptive banded dynamic programming (DP) with an SIMD implementation. abPOA
can perform multiple sequence alignment (MSA) on a set of input sequences and
generate a consensus sequence by applying the heaviest bundling algorithm to
the final alignment graph.
abPOA can generate high-quality consensus sequences from error-prone long
reads and offer significant speed improvement over existing tools.
abPOA supports three alignment modes (global, local, extension) and flexible
scoring schemes that allow linear, affine and convex gap penalties. It right
now supports SSE2/SSE4.1/AVX2 vectorization.
This package provides the python3 module of abPOA.
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python3-pyani
Python3 module for average nucleotide identity analyses
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Versions of package python3-pyani |
Release | Version | Architectures |
sid | 0.2.12-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 0.2.12-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 0.2.10-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 0.2.12-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
upstream | 0.2.13.1 |
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License: DFSG free
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Pyani is a Python3 module and script that provides support for
calculating average nucleotide identity (ANI) and related measures for
whole genome comparisons, and rendering relevant graphical summary
output. Where available, it takes advantage of multicore systems, and
can integrate with SGE/OGE-type job schedulers for the sequence
comparisons.
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python3-pybedtools
Python 3 wrapper around BEDTools for bioinformatics work
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Versions of package python3-pybedtools |
Release | Version | Architectures |
bookworm | 0.9.0-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
sid | 0.10.0-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
trixie | 0.10.0-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
bullseye | 0.8.0-5 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
buster | 0.8.0-1 | amd64,arm64 |
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License: DFSG free
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The BEDTools suite of programs is widely used for genomic interval
manipulation or “genome algebra”. pybedtools wraps and extends BEDTools and
offers feature-level manipulations from within Python.
This is the Python 3 version.
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python3-pybel
Biological Expression Language
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Versions of package python3-pybel |
Release | Version | Architectures |
bullseye | 0.14.10-1 | all |
sid | 0.15.5-1 | all |
trixie | 0.15.5-1 | all |
bookworm | 0.14.10-1 | all |
buster | 0.12.1-1 | all |
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License: DFSG free
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PyBEL is a pure Python package for parsing and handling biological
networks encoded in the Biological Expression Language (BEL) version
2. It also facilitates data interchange between common formats and
databases such as NetworkX, JSON, CSV, SIF, Cytoscape, CX, NDEx, SQL,
and Neo4J.
This package installs the library for Python 3.
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python3-pybigwig
Python 3 module for quick access to bigBed and bigWig files
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Versions of package python3-pybigwig |
Release | Version | Architectures |
stretch | 0.3.2-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 0.3.12-1 | amd64,arm64,armhf,i386 |
trixie | 0.3.23+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 0.3.23+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 0.3.17-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 0.3.18+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
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License: DFSG free
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This is a Python extension, written in C, for quick access to bigBed files,
and access to and creation of bigWig files.
The bigWig format was originally created in the context of genome
browsers. There, computing exact summary statistics for a given interval
is less important than quickly being able to compute an approximate
statistic. Because of this, bigWig files contain not only interval-value
associations, but also sum of values /sum of squared values /minimum
value /maximum value /number of bases covered for equally sized
bins of various sizes. These different sizes are referred to as "zoom
levels". The smallest zoom level has bins that are 16 times the mean
interval size in the file and each subsequent zoom level has bins 4 times
larger than the previous. This methodology is used in Kent's tools and,
therefore, likely used in almost every currently existing bigWig file.
When a bigWig file is queried for a summary statistic, the size of the
interval is used to determine whether to use a zoom level and, if so,
which one. The optimal zoom level is that which has the largest bins no
more than half the width of the desired interval. If no such zoom level
exists, the original intervals are instead used for the calculation.
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python3-pyfaidx
efficient random access to fasta subsequences for Python 3
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Versions of package python3-pyfaidx |
Release | Version | Architectures |
trixie | 0.8.1.3-1 | all |
bullseye | 0.5.9.2-1 | all |
stretch | 0.4.8.1-1 | all |
sid | 0.8.1.3-1 | all |
buster | 0.5.5.2-1 | all |
bookworm | 0.7.1-2 | all |
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License: DFSG free
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Samtools provides a function "faidx" (FAsta InDeX), which creates a
small flat index file ".fai" allowing for fast random access to any
subsequence in the indexed FASTA file, while loading a minimal amount of
the file in to memory. This Python module implements pure Python classes
for indexing, retrieval, and in-place modification of FASTA files using
a samtools compatible index. The pyfaidx module is API compatible with
the pygr seqdb module. A command-line script "faidx" is installed
alongside the pyfaidx module, and facilitates complex manipulation of
FASTA files without any programming knowledge.
This package provides the Python 3 modules to access fasta files.
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python3-pyfastx
fast random access to sequences from FASTA/Q file - python3 module
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Versions of package python3-pyfastx |
Release | Version | Architectures |
sid | 2.1.0-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 2.1.0-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 0.8.4-2 | amd64,arm64,i386,mips64el,ppc64el,s390x |
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License: DFSG free
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The pyfastx is a lightweight Python C extension that enables users to randomly
access to sequences from plain and gzipped FASTA/Q files. This module aims to
provide simple APIs for users to extract sequence from FASTA and reads from
FASTQ by identifier and index number. The pyfastx will build indexes stored in
a sqlite3 database file for random access to avoid consuming excessive amount
of memory. In addition, the pyfastx can parse standard (sequence is spread
into multiple lines with same length) and nonstandard (sequence is spread into
one or more lines with different length) FASTA format.
It features:
- a single file for the Python extension;
- lightweight, memory efficient FASTA/Q file parsing;
- fast random access to sequences from gzipped FASTA/Q file;
- sequences reading from FASTA file line by line;
- N50 and L50 calculation of sequences in FASTA file;
- GC content and nucleotides composition calculation;
- reverse, complement and antisense sequences extraction;
- excellent compatibility: support for parsing nonstandard FASTA file;
- support for FASTQ quality score conversion;
- a command line interface for splitting FASTA/Q file.
This package provides the python3 module.
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python3-pymummer
Python 3 interface to MUMmer
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Versions of package python3-pymummer |
Release | Version | Architectures |
stretch | 0.10.1-1 | all |
sid | 0.11.0-4 | all |
trixie | 0.11.0-4 | all |
bookworm | 0.11.0-3 | all |
bullseye | 0.11.0-2 | all |
buster | 0.10.3-2 | all |
stretch-backports | 0.10.3-1~bpo9+1 | all |
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License: DFSG free
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pymummer is a Python wrapper for running the programs of the MUMmer
sequence alignment suite and parsing their output.
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python3-pyranges
2D representation of genomic intervals and their annotations
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Versions of package python3-pyranges |
Release | Version | Architectures |
bullseye | 0.0.85+ds-1 | all |
trixie | 0.0.111+ds-8 | all |
sid | 0.0.111+ds-8 | all |
bookworm | 0.0.111+ds-4 | all |
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License: DFSG free
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A PyRanges object must have the columns Chromosome, Start and
End. These describe the genomic position and function as implicit row
labels. A Strand column is optional and adds strand information to the
intervals. Any other columns are allowed and are considered metadata.
The structure can be filled from .bed, .bam or .gff files, also from
tabular or textual representations.
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python3-pysam
interface for the SAM/BAM sequence alignment and mapping format (Python 3)
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Versions of package python3-pysam |
Release | Version | Architectures |
bookworm | 0.20.0+ds-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
stretch | 0.10.0+ds-2 | amd64,arm64,mips64el,ppc64el |
trixie | 0.22.1+ds-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
bullseye | 0.15.4+ds-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
buster | 0.15.2+ds-2 | amd64,arm64 |
sid | 0.22.1+ds-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
stretch-backports | 0.14+ds-2~bpo9+1 | amd64,arm64,mips64el,ppc64el |
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License: DFSG free
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Pysam is a Python module for reading and manipulating Samfiles. It's a
lightweight wrapper of the samtools C-API. Pysam also includes an interface
for tabix.
This package installs the module for Python 3.
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python3-pyspoa
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Versions of package python3-pyspoa |
Release | Version | Architectures |
bookworm | 0.0.8-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 0.0.10-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 0.0.10-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
upstream | 0.2.1 |
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License: DFSG free
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Spoa (SIMD POA) is a c++ implementation of the partial order alignment
(POA) algorithm (as described in 10.1093/bioinformatics/18.3.452) which
is used to generate consensus sequences (as described in
10.1093/bioinformatics/btg109). It supports three alignment modes: local
(Smith-Waterman), global (Needleman-Wunsch) and semi-global alignment
(overlap).
This package presents Python bindings for the spoa library
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python3-pyvcf
Variant Call Format (VCF) parser for Python 3
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Versions of package python3-pyvcf |
Release | Version | Architectures |
buster | 0.6.8+git20170215.476169c-1 | amd64,arm64,armhf,i386 |
stretch | 0.6.8-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
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License: DFSG free
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The Variant Call Format (VCF) specifies the format of a text file used
in bioinformatics for storing gene sequence variations. The format has
been developed with the advent of large-scale genotyping and DNA
sequencing projects, such as the 1000 Genomes Project.
The intent of this module is to mimic the csv module in the Python
stdlib, as opposed to more flexible serialization formats like JSON or
YAML. vcf will attempt to parse the content of each record based on
the data types specified in the meta-information lines -- specifically
the ##INFO and
##FORMAT lines. If these lines are missing or incomplete, it will check
against the reserved types mentioned in the spec. Failing that, it will
just return strings.
This package provides the Python 3 modules.
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python3-rdkit
Collection of cheminformatics and machine-learning software
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Versions of package python3-rdkit |
Release | Version | Architectures |
bookworm | 202209.3-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 202409.2-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 202009.4-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
upstream | 202409.4 |
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License: DFSG free
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RDKit is a Python/C++ based cheminformatics and machine-learning software
environment. Features Include:
- Chemical reaction handling and transforms
- Substructure searching with SMARTS
- Canonical SMILES
- Molecule-molecule alignment
- Large number of molecular descriptors, including topological,
compositional, EState, SlogP/SMR, VSA and Feature-map vectors
- Fragmentation using RECAP rules
- 2D coordinate generation and depiction, including constrained depiction
- 3D coordinate generation using geometry embedding
- UFF and MMFF94 forcefields
- Chirality support, including calculation of (R/S) stereochemistry codes
- 2D pharmacophore searching
- Fingerprinting, including Daylight-like, atom pairs, topological
torsions, Morgan algorithm and MACCS keys
- Calculation of shape similarity
- Multi-molecule maximum common substructure
- Machine-learning via clustering and information theory algorithms
- Gasteiger-Marsili partial charge calculation
File formats RDKit supports include MDL Mol, PDB, SDF, TDT, SMILES and RDKit
binary format.
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python3-ruffus
Python3 computation pipeline library widely used in bioinformatics
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Versions of package python3-ruffus |
Release | Version | Architectures |
bookworm | 2.8.4-5 | all |
sid | 2.8.4-7 | all |
trixie | 2.8.4-7 | all |
buster | 2.8.1-4 | all |
bullseye | 2.8.4-2 | all |
stretch | 2.6.3+dfsg-4 | all |
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License: DFSG free
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Ruffus is designed to allow scientific and other analyses to be automated
with the minimum of fuss and the least effort.
- Lightweight: Suitable for the simplest of tasks
- Scalable: Handles even fiendishly complicated pipelines which would cause
make or scons to go cross-eyed and recursive.
- Standard Python: No "clever magic", no pre-processing.
- Unintrusive: Unambitious, lightweight syntax which tries to do this one
small thing well.
This package provides python3 modules.
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python3-screed
short nucleotide read sequence utils in Python 3
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Versions of package python3-screed |
Release | Version | Architectures |
trixie | 1.1.3-1 | all |
buster | 1.0-3 | all |
stretch | 0.9-2 | all |
bullseye | 1.0.5-1 | all |
bookworm | 1.0.5-4 | all |
sid | 1.1.3-1 | all |
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License: DFSG free
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Screed parses FASTA and FASTQ files, generates databases, and lets you query
these databases. Values such as sequence name, sequence description, sequence
quality, and the sequence itself can be retrieved from these databases.
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python3-shasta
nanopore whole genome assembly (dynamic library)
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Versions of package python3-shasta |
Release | Version | Architectures |
trixie | 0.12.0-1 | amd64,arm64 |
sid | 0.12.0-1 | amd64,arm64 |
experimental | 0.12.0-2 | amd64,arm64 |
bullseye | 0.7.0-3 | amd64,arm64 |
bookworm | 0.11.1-1 | amd64,arm64 |
upstream | 0.13.0 |
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License: DFSG free
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De novo assembly from Oxford Nanopore reads. The goal of the Shasta long
read assembler is to rapidly produce accurate assembled sequence using
as input DNA reads generated by Oxford Nanopore flow cells.
Computational methods used by the Shasta assembler include:
-
Using a run-length representation of the read sequence. This makes
the assembly process more resilient to errors in homopolymer
repeat counts, which are the most common type of errors in Oxford
Nanopore reads.
-
Using in some phases of the computation a representation of the read
sequence based on markers, a fixed subset of short k-mers (k ≈ 10).
Shasta assembly quality is comparable or better than assembly quality
achieved by other long read assemblers.
This package contains the dynamic library that can be interfaced and
imported within Python.
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|
python3-skbio
Python3 data structures, algorithms, educational resources for bioinformatic
|
Versions of package python3-skbio |
Release | Version | Architectures |
bookworm | 0.5.8-4 | amd64,arm64,mips64el,ppc64el |
sid | 0.6.2-4 | amd64,arm64,mips64el,ppc64el,riscv64 |
trixie | 0.6.2-4 | amd64,arm64,mips64el,ppc64el,riscv64 |
stretch | 0.5.1-2 | amd64 |
bullseye | 0.5.6-4 | amd64,arm64,mips64el,ppc64el |
|
License: DFSG free
|
Scikit-bio is a Python package providing data structures, algorithms, and
educational resources for bioinformatics.
This is the package for Python3
|
|
python3-slow5
Python3 modul for reading & writing SLOW5 files
|
Versions of package python3-slow5 |
Release | Version | Architectures |
trixie | 0.7.0+dfsg-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
bookworm | 0.7.0+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
sid | 0.7.0+dfsg-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
upstream | 1.3.0 |
|
License: DFSG free
|
Slow5lib is a software library for reading & writing SLOW5 files.
Slow5lib is designed to facilitate use of data in SLOW5 format by third-
party software packages. Existing packages that read/write data in FAST5
format can be easily modified to support SLOW5.
SLOW5 is a new file format for storing signal data from Oxford Nanopore
Technologies (ONT) devices. SLOW5 was developed to overcome inherent
limitations in the standard FAST5 signal data format that prevent
efficient, scalable analysis and cause many headaches for developers.
SLOW5 can be encoded in human-readable ASCII format, or a more compact
and efficient binary format (BLOW5) - this is analogous to the seminal
SAM/BAM format for storing DNA sequence alignments. The BLOW5 binary
format supports zlib (DEFLATE) compression, or other compression
methods, thereby minimising the data storage footprint while still
permitting efficient parallel access. Detailed benchmarking experiments
have shown that SLOW5 format is an order of magnitude faster and
significantly smaller than FAST5.
This is the Python3 module.
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python3-sqt
SeQuencing Tools for biological DNA/RNA high-throughput data
|
Versions of package python3-sqt |
Release | Version | Architectures |
buster | 0.8.0-3 | amd64,arm64 |
bullseye | 0.8.0-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
sid | 0.8.0-8 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
trixie | 0.8.0-8 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
bookworm | 0.8.0-6 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
|
License: DFSG free
|
sqt is a collection of command-line tools for working with
high-throughput sequencing data. Conceptionally not fixed to use any
particular language, many sqt subcommands are currently implemented
in Python. For them, a Python package is available with functions for
reading and writing FASTA/FASTQ files, computing alignments, quality
trimming, etc.
The following tools are offered:
- sqt-coverage -- Compute per-reference statistics such as coverage
and GC content
- sqt-fastqmod -- FASTQ modifications: shorten, subset, reverse
complement, quality trimming.
- sqt-fastastats -- Compute N50, min/max length, GC content etc. of
a FASTA file
- sqt-qualityguess -- Guess quality encoding of one or more FASTA files.
- sqt-globalalign -- Compute a global or semiglobal alignment of two strings.
- sqt-chars -- Count length of the first word given on the command line.
- sqt-sam-cscq -- Add the CS and CQ tags to a SAM file with colorspace reads.
- sqt-fastamutate -- Add substitutions and indels to sequences in a
FASTA file.
- sqt-fastaextract -- Efficiently extract one or more regions from an
indexed FASTA file.
- sqt-translate -- Replace characters in FASTA files (like the 'tr'
command).
- sqt-sam-fixn -- Replace all non-ACGT characters within reads in a
SAM file.
- sqt-sam-insertsize -- Mean and standard deviation of paired-end
insert sizes.
- sqt-sam-set-op -- Set operations (union, intersection, ...) on
SAM/BAM files.
- sqt-bam-eof -- Check for the End-Of-File marker in compressed
BAM files.
- sqt-checkfastqpe -- Check whether two FASTQ files contain correctly
paired paired-end data.
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python3-streamz
build pipelines to manage continuous streams of data
|
Versions of package python3-streamz |
Release | Version | Architectures |
trixie | 0.6.4-2 | all |
bookworm | 0.6.4-1 | all |
sid | 0.6.4-2 | all |
bullseye | 0.6.2-1 | all |
|
License: DFSG free
|
It is simple to use in simple cases, but also supports complex pipelines that
involve branching, joining, flow control, feedback, back pressure, and so on.
Optionally, Streamz can also work with both Pandas and cuDF dataframes,
to provide sensible streaming operations on continuous tabular data.
|
|
python3-tinyalign
numerical representation of differences between strings
|
Versions of package python3-tinyalign |
Release | Version | Architectures |
bookworm | 0.2.1-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 0.2.2-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 0.2.2-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 0.2-5 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
|
License: DFSG free
|
A small Python module providing edit distance (aka Levenshtein distance,
that is, counting insertions, deletions and substitutions) and Hamming
distance computation.
Its main purpose is to speed up computation of edit distance by allowing
to specify a maximum number of differences maxdiff (banding). If that
parameter is provided, the returned edit distance is anly accurate up
to maxdiff. That is, if the actual edit distance is higher than maxdiff,
a value larger than maxdiff is returned, but not necessarily the actual
edit distance.
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python3-torch
Tensors and Dynamic neural networks in Python (Python Interface)
|
Versions of package python3-torch |
Release | Version | Architectures |
bookworm | 1.13.1+dfsg-4 | amd64,arm64,ppc64el,s390x |
sid | 2.5.1+dfsg-1 | amd64,arm64,ppc64el,riscv64,s390x |
bullseye | 1.7.1-7 | amd64,arm64,armhf,ppc64el,s390x |
|
License: DFSG free
|
PyTorch is a Python package that provides two high-level features:
(1) Tensor computation (like NumPy) with strong GPU acceleration
(2) Deep neural networks built on a tape-based autograd system
You can reuse your favorite Python packages such as NumPy, SciPy and Cython
to extend PyTorch when needed.
This is the CPU-only version of PyTorch (Python interface).
Please cite:
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai and Soumith Chintala:
|
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python3-treetime
inference of time stamped phylogenies and ancestral reconstruction (Python 3)
|
Versions of package python3-treetime |
Release | Version | Architectures |
buster | 0.5.3-1 | all |
trixie | 0.11.4-1 | all |
sid | 0.11.4-1 | all |
bookworm | 0.9.4-1 | all |
bullseye | 0.8.1-1 | all |
|
License: DFSG free
|
TreeTime provides routines for ancestral sequence reconstruction and the
maximum likelihoo inference of molecular-clock phylogenies, i.e., a tree
where all branches are scaled such that the locations of terminal nodes
correspond to their sampling times and internal nodes are placed at the
most likely time of divergence.
TreeTime aims at striking a compromise between sophisticated
probabilistic models of evolution and fast heuristics. It implements GTR
models of ancestral inference and branch length optimization, but takes
the tree topology as given. To optimize the likelihood of time-scaled
phylogenies, treetime uses an iterative approach that first infers
ancestral sequences given the branch length of the tree, then optimizes
the positions of unconstraine d nodes on the time axis, and then repeats
this cycle. The only topology optimization are (optional) resolution of
polytomies in a way that is most (approximately) consistent with the
sampling time constraints on the tree. The package is designed to be
used as a stand-alone tool or as a library used in larger phylogenetic
analysis workflows.
Features
- ancestral sequence reconstruction (marginal and joint maximum
likelihood)
- molecular clock tree inference (marginal and joint maximum
likelihood)
- inference of GTR models
- rerooting to obtain best root-to-tip regression
- auto-correlated relaxed molecular clock (with normal prior)
This package provides the Python 3 module.
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|
python3-unifrac
high-performance phylogenetic diversity calculations
|
Versions of package python3-unifrac |
Release | Version | Architectures |
sid | 1.3-4 | amd64,arm64,mips64el,ppc64el,riscv64 |
bookworm | 1.2-3 | amd64,arm64,mips64el,ppc64el |
trixie | 1.3-4 | amd64,arm64,mips64el,ppc64el,riscv64 |
|
License: DFSG free
|
The de facto repository for high-performance phylogenetic diversity
calculations. The methods in this repository are based on an
implementation of the Strided State UniFrac algorithm which is faster,
and uses less memory than Fast UniFrac. Strided State UniFrac supports
Unweighted UniFrac, Weighted UniFrac, Generalized UniFrac, Variance
Adjusted UniFrac and meta UniFrac. This repository also includes Stacked
Faith (manuscript in preparation), a method for calculating Faith's PD
that is faster and uses less memory than the Fast UniFrac-based
reference implementation.
This package contains the Python3 module.
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|
python3-wdlparse
Workflow Description Language (WDL) parser for Python
|
Versions of package python3-wdlparse |
Release | Version | Architectures |
sid | 0.1.0-3 | all |
bullseye | 0.1.0-2 | all |
bookworm | 0.1.0-3 | all |
trixie | 0.1.0-3 | all |
|
License: DFSG free
|
A Python package that provides the generated Hermes and Antlr4 WDL parsers for
Python.
|
|
r-bioc-biobase
base functions for Bioconductor
|
Versions of package r-bioc-biobase |
Release | Version | Architectures |
buster | 2.42.0-1 | amd64,arm64,armhf,i386 |
bookworm | 2.58.0-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 2.64.0-4 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
experimental | 2.66.0-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 2.50.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
stretch | 2.34.0-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
sid | 2.64.0-4 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
jessie | 2.24.0-1 | amd64,armel,armhf,i386 |
upstream | 2.66.0 |
|
License: DFSG free
|
Biobase is part of the Bioconductor project, and is used by many other
packages. Biobase contains standardized data structures to represent genomic
data, and functions that are needed by many other packages or which replace R
functions.
Bioconductor is a project to develop innovative software tools for use in
computational biology. It is based on the R language. You should already be
quite familiar with R before using Bioconductor. Bioconductor packages provide
flexible interactive tools for carrying out a number of different computational
tasks.
Please cite:
Robert C Gentleman, Vincent J Carey, Douglas M Bates, Ben Bolstad, Marcel Dettling, Sandrine Dudoit, Byron Ellis, Laurent Gautier, Yongchao Ge, Jeff Gentry, Kurt Hornik, Torsten Hothorn, Wolfgang Huber, Stefano Iacus, Rafael Irizarry, Friedrich Leisch, Cheng Li, Martin Maechler, Anthony J Rossini, Gunther Sawitzki, Colin Smith, Gordon Smyth, Luke Tierney, Jean Y H Yang and Jianhua Zhang:
Bioconductor: Open software development for computational biology and bioinformatics.
(PubMed,eprint)
Genome Biology
5(10):R80
(2004)
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|
r-cran-boolnet
assembling, analyzing and visualizing Boolean networks
|
Versions of package r-cran-boolnet |
Release | Version | Architectures |
jessie | 2.0-1 | amd64,armel,armhf,i386 |
trixie | 2.1.9-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 2.1.9-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 2.1.7-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 2.1.5-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 2.1.4-1 | amd64,arm64,armhf,i386 |
stretch | 2.1.3-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
|
License: DFSG free
|
BoolNet is an R package that provides tools for assembling, analyzing and
visualizing synchronous and asynchronous Boolean networks as well as
probabilistic Boolean networks.
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r-cran-corrplot
Visualization of a Correlation Matrix
|
Versions of package r-cran-corrplot |
Release | Version | Architectures |
bullseye | 0.84-3 | all |
sid | 0.94-1 | all |
trixie | 0.94-1 | all |
bookworm | 0.92-1 | all |
buster-backports | 0.84-3~bpo10+1 | all |
upstream | 0.95 |
|
License: DFSG free
|
A graphical display of a correlation matrix or general matrix.
It also contains some algorithms to do matrix reordering. In addition,
corrplot is good at details, including choosing color, text labels,
color labels, layout, etc.
|
|
r-cran-distory
GNU R distance between phylogenetic histories
|
Versions of package r-cran-distory |
Release | Version | Architectures |
buster | 1.4.3-2 | amd64,arm64,armhf,i386 |
bookworm | 1.4.4-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.4.4-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch | 1.4.2-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
trixie | 1.4.4-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.4.4-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
upstream | 1.4.5 |
|
License: DFSG free
|
This GNU R package enables calculation of geodesic distance between
phylogenetic trees and associated functions.
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r-cran-fitdistrplus
support fit of parametric distribution
|
Versions of package r-cran-fitdistrplus |
Release | Version | Architectures |
trixie | 1.2-1-1 | all |
bullseye | 1.1-3-1 | all |
buster-backports | 1.1-3-1~bpo10+1 | all |
stretch-backports-sloppy | 1.1-1-1~bpo9+1 | all |
sid | 1.2-1-1 | all |
bookworm | 1.1-8-1 | all |
|
License: DFSG free
|
Extends the fitdistr() function (of the MASS package) with several
functions to help the fit of a parametric distribution to non-censored
or censored data. Censored data may contain left censored, right
censored and interval censored values, with several lower and upper
bounds. In addition to maximum likelihood estimation (MLE), the package
provides moment matching (MME), quantile matching (QME) and maximum
goodness-of-fit estimation (MGE) methods (available only for non-censored
data). Weighted versions of MLE, MME and QME are available. See
e.g. Casella & Berger (2002). Statistical inference. Pacific Grove.
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|
r-cran-forecast
GNU R forecasting functions for time series and linear models
|
Versions of package r-cran-forecast |
Release | Version | Architectures |
bullseye | 8.13-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 8.23.0-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 8.23.0-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 8.20-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
|
License: DFSG free
|
Methods and tools for displaying and analysing
univariate time series forecasts including exponential smoothing
via state space models and automatic ARIMA modelling.
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r-cran-genetics
GNU R package for population genetics
|
Versions of package r-cran-genetics |
Release | Version | Architectures |
buster | 1.3.8.1.1-1 | all |
sid | 1.3.8.1.3-1 | all |
stretch | 1.3.8.1-1 | all |
trixie | 1.3.8.1.3-1 | all |
bookworm | 1.3.8.1.3-1 | all |
jessie | 1.3.8.1-1 | all |
bullseye | 1.3.8.1.2-2 | all |
Debtags of package r-cran-genetics: |
devel | lang:r |
field | biology, biology:bioinformatics, biology:molecular, biology:structural |
use | analysing |
|
License: DFSG free
|
Classes and methods for handling genetic data. Includes
The package provides a library for the statistics environment R that
contains classes to represent genotypes and haplotypes at single markers up
to multiple markers on multiple chromosomes. Function include
allele frequencies, flagging homo/heterozygotes, flagging carriers
of certain alleles, estimating and testing for Hardy-Weinberg
disequilibrium, estimating and testing for linkage disequilibrium,
and more.
NOTE: THIS PACKAGE IS NOW OBSOLETE.
The R-Genetics project has developed an set of enhanced genetics
packages to replace 'genetics'. Please visit the project homepage
at http://rgenetics.org for information.
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r-cran-gprofiler2
Interface to the 'g:Profiler' Toolset
|
Versions of package r-cran-gprofiler2 |
Release | Version | Architectures |
bookworm | 0.2.1+dfsg-1 | all |
trixie | 0.2.3+dfsg-1 | all |
sid | 0.2.3+dfsg-1 | all |
|
License: DFSG free
|
A toolset for functional enrichment analysis and visualization,
gene/protein/SNP identifier conversion and mapping orthologous genes
across species via 'g:Profiler' (https://biit.cs.ut.ee/gprofiler). The
main tools are:
(1) 'g:GOSt' - functional enrichment analysis and visualization of
gene lists;
(2) 'g:Convert' - gene/protein/transcript identifier conversion across
various namespaces;
(3) 'g:Orth' - orthology search across species;
(4) 'g:SNPense' - mapping SNP rs identifiers to chromosome positions,
genes and variant effects This package is an R interface
corresponding to the 2019 update of 'g:Profiler' and provides access
to 'g:Profiler' for versions 'e94_eg41_p11' and higher. See the
package 'gProfileR' for accessing older versions from the
'g:Profiler' toolset.
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r-cran-haplo.stats
GNU R package for haplotype analysis
|
Versions of package r-cran-haplo.stats |
Release | Version | Architectures |
stretch | 1.7.7-1 | amd64,arm64,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 1.7.9-2 | amd64,arm64,armhf,i386 |
sid | 1.9.5.1-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 1.9.5.1-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 1.9.3-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
jessie | 1.6.11-1 | amd64,armel,armhf,i386 |
bullseye | 1.8.6-2 | amd64,arm64,armhf,i386,mips64el,mipsel,ppc64el,s390x |
upstream | 1.9.7 |
Debtags of package r-cran-haplo.stats: |
devel | lang:r |
field | biology, biology:bioinformatics |
use | analysing |
|
License: DFSG free
|
The package provides routines for the GNU R statistics environment
for statistical Analysis of indirectly measured Haplotypes with Traits
and Covariates when Linkage Phase is Ambiguous. The statistical methods
assume that all subjects are unrelated and that haplotypes are ambiguous
(due to unknown linkage phase of the genetic markers). The main functions
are: haplo.em, haplo.glm, haplo.score, haplo.power, and seqhap.
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r-cran-phangorn
GNU R package for phylogenetic analysis
|
Versions of package r-cran-phangorn |
Release | Version | Architectures |
bullseye | 2.5.5-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 2.11.1+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch | 2.1.1-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
trixie | 2.11.1+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster | 2.4.0-2 | amd64,arm64,armhf,i386 |
bookworm | 2.11.1+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
upstream | 2.12.1 |
|
License: DFSG free
|
phangorn is a tool for reconstructing phylogenies, using distance-based
methods, maximum parsimony or maximum likelihood, and performing Hadamard
conjugation. It also offers functions for comparing trees, phylogenetic models
or splits, simulating character data and performing congruence analysis.
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|
r-cran-pheatmap
GNU R package to create pretty heatmaps
|
Versions of package r-cran-pheatmap |
Release | Version | Architectures |
stretch | 1.0.8-1 | all |
buster | 1.0.12-1 | all |
bullseye | 1.0.12-2 | all |
bookworm | 1.0.12-2 | all |
trixie | 1.0.12-2 | all |
sid | 1.0.12-2 | all |
|
License: DFSG free
|
GNU R implementation of heatmaps that offers more control over dimensions and
appearance.
|
|
r-cran-phylobase
GNU R base package for phylogenetic structures and comparative data
|
Versions of package r-cran-phylobase |
Release | Version | Architectures |
trixie | 0.8.12-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 0.8.12-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster | 0.8.6-1 | amd64,arm64,armhf,i386 |
bookworm | 0.8.10-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 0.8.10-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
stretch | 0.8.2-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
|
License: DFSG free
|
This R package provides a base S4 class for comparative methods,
incorporating one or more trees and trait data as these are used in
other packages dealing with phylogenetic structures and comparative data.
|
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r-cran-pscbs
R package: Analysis of Parent-Specific DNA Copy Numbers
|
Versions of package r-cran-pscbs |
Release | Version | Architectures |
bullseye | 0.65.0-3 | all |
buster | 0.64.0-1 | all |
stretch | 0.62.0-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
bookworm | 0.66.0-2 | all |
sid | 0.67.0-3 | all |
trixie | 0.67.0-3 | all |
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License: DFSG free
|
Segmentation of allele-specific DNA copy number data and detection of regions
with abnormal copy number within each parental chromosome. Both tumor-normal
paired and tumoronly analyses are supported.
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r-cran-qqman
R package for visualizing GWAS results using Q-Q and manhattan plots
|
Versions of package r-cran-qqman |
Release | Version | Architectures |
stretch | 0.1.2-1 | all |
bullseye | 0.1.4-7 | all |
sid | 0.1.9+dfsg-1 | all |
trixie | 0.1.9+dfsg-1 | all |
bookworm | 0.1.8+dfsg-1 | all |
buster | 0.1.4-6 | all |
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License: DFSG free
|
qqman is an add-on package for the R statistical environment. This package
provides functions for visualizing Genome-Wide Association Studies (GWAS)
results using Manhattan plots and Quantile-Quantile plots.
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r-cran-rentrez
GNU R interface to the NCBI's EUtils API
|
Versions of package r-cran-rentrez |
Release | Version | Architectures |
buster | 1.2.1-2 | all |
bullseye | 1.2.3+dfsg-1 | all |
bookworm | 1.2.3+dfsg-1 | all |
trixie | 1.2.3+dfsg-1 | all |
sid | 1.2.3+dfsg-1 | all |
stretch | 1.0.4-1 | all |
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License: DFSG free
|
Provides an R interface to the NCBI's EUtils API allowing users to
search databases like GenBank and PubMed, process the results of those
searches and pull data into their R sessions.
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r-cran-rncl
GNU R interface to the Nexus Class Library
|
Versions of package r-cran-rncl |
Release | Version | Architectures |
trixie | 0.8.7-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 0.8.7-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 0.8.3-1 | amd64,arm64,armhf,i386 |
sid | 0.8.7-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 0.8.4-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
stretch | 0.8.2-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
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License: DFSG free
|
This R package provides an interface to the Nexus Class Library which
allows parsing of NEXUS, Newick and other phylogenetic tree file
formats. It provides elements of the file that can be used to build
phylogenetic objects such as ape's 'phylo' or phylobase's 'phylo4(d)'.
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r-cran-rnexml
GNU R package for semantically rich I/O for the 'NeXML' format
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Versions of package r-cran-rnexml |
Release | Version | Architectures |
bullseye | 2.4.5+ds-1 | all |
trixie | 2.4.11+ds-1 | all |
bookworm | 2.4.11+ds-1 | all |
stretch | 2.0.7-1 | all |
buster | 2.3.0-1 | all |
sid | 2.4.11+ds-1 | all |
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License: DFSG free
|
Provides access to phyloinformatic data in 'NeXML' format. The package
should add new functionality to R such as the possibility to manipulate
'NeXML' objects in more various and refined way and compatibility with
'ape' objects.
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r-cran-rotl
GNU R interface to the 'Open Tree of Life' API
|
Versions of package r-cran-rotl |
Release | Version | Architectures |
bookworm | 3.0.14-1 | all |
buster | 3.0.6-1 | all |
stretch | 3.0.1-1 | all |
bullseye | 3.0.11-1 | all |
sid | 3.1.0-1 | all |
trixie | 3.1.0-1 | all |
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License: DFSG free
|
An interface to the 'Open Tree of Life' API to retrieve phylogenetic
trees, information about studies used to assemble the synthetic tree,
and utilities to match taxonomic names to 'Open Tree identifiers'. The
'Open Tree of Life' aims at assembling a comprehensive phylogenetic tree
for all named species.
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r-cran-samr
GNU R significance analysis of microarrays
|
Versions of package r-cran-samr |
Release | Version | Architectures |
sid | 3.0-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 3.0-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 3.0-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 3.0-1 | amd64,arm64,armhf,i386 |
trixie | 3.0-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
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License: DFSG free
|
This GNU R package provides significance analysis of microarrays.
A microarray is a multiplex lab-on-a-chip. It is a 2D array on a solid
substrate (usually a glass slide or silicon thin-film cell) that assays
large amounts of biological material using high-throughput screening
miniaturized, multiplexed and parallel processing and detection methods.
This package helps analysing this kind of microarrays.
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r-cran-sctransform
Variance Stabilizing Transformations for Single Cell UMI Data
|
Versions of package r-cran-sctransform |
Release | Version | Architectures |
bullseye | 0.3.2-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 0.4.1-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 0.3.5-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 0.4.1-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
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License: DFSG free
|
A normalization method for single-cell UMI count data using a
variance stabilizing transformation. The transformation is based on a
negative binomial regression model with regularized parameters. As part of the
same regression framework, this package also provides functions for
batch correction, and data correction. See Hafemeister and Satija 2019
for more details.
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r-cran-seqinr
GNU R biological sequences retrieval and analysis
|
Versions of package r-cran-seqinr |
Release | Version | Architectures |
buster | 3.4-5-2 | amd64,arm64,armhf,i386 |
bullseye | 4.2-5-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 4.2-23-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 4.2-36-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 4.2-36-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch | 3.3-3-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
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License: DFSG free
|
Exploratory data analysis and data visualization for biological sequence
(DNA and protein) data. Includes also utilities for sequence data
management under the ACNUC system.
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r-cran-seurat
Tools for Single Cell Genomics
|
Versions of package r-cran-seurat |
Release | Version | Architectures |
bookworm | 4.3.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 4.0.0-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 5.1.0-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
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License: DFSG free
|
A toolkit for quality control, analysis, and exploration of single cell
RNA sequencing data. 'Seurat' aims to enable users to identify and
interpret sources of heterogeneity from single cell transcriptomic
measurements, and to integrate diverse types of single cell data. See
Satija R, Farrell J, Gennert D, et al (2015) ,
Macosko E, Basu A, Satija R, et al (2015)
, and Butler A and Satija R (2017)
for more details.
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r-cran-tsne
t-distributed stochastic neighbor embedding for R (t-SNE)
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Versions of package r-cran-tsne |
Release | Version | Architectures |
bookworm | 0.1-3.1-1 | all |
trixie | 0.1-3.1-1 | all |
bullseye | 0.1-3-3 | all |
sid | 0.1-3.1-1 | all |
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License: DFSG free
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A "pure R" implementation of the t-SNE algorithm.
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r-cran-vegan
Community Ecology Package for R
|
Versions of package r-cran-vegan |
Release | Version | Architectures |
stretch | 2.4-2-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 2.5-4+dfsg-3 | amd64,arm64,armhf,i386 |
bullseye | 2.5-7+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 2.6-4+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 2.6-8+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 2.6-8+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
jessie | 2.0-10-1 | amd64,armel,armhf,i386 |
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License: DFSG free
|
R package for community ecologists. It contains most multivariate analysis
needed in analysing ecological communities, and tools for diversity analysis.
Most diversity methods assume that data are counts of individuals.
These tools are sometimes used outside the field of ecology, for instance to
study populations of white blood cells or RNA molecules.
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r-cran-webgestaltr
find over-represented properties in gene lists
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Versions of package r-cran-webgestaltr |
Release | Version | Architectures |
bookworm | 0.4.5-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 0.4.6-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 0.4.4-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 0.4.6-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
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License: DFSG free
|
The web version WebGestalt http://www.webgestalt.org supports 12
organisms, 354 gene identifiers and 321,251 function categories. Users
can upload the data and functional categories with their own gene
identifiers. In addition to the Over-Representation Analysis, WebGestalt
also supports Gene Set Enrichment Analysis and Network Topology
Analysis. The user-friendly output report allows interactive and
efficient exploration of enrichment results. The WebGestaltR package not
only supports all above functions but also can be integrated into other
pipeline or simultaneously analyze multiple gene lists.
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ruby-bio
Ruby tools for computational molecular biology
|
Versions of package ruby-bio |
Release | Version | Architectures |
sid | 2.0.5-1 | all |
trixie | 2.0.5-1 | all |
bookworm | 2.0.4-1 | all |
jessie | 1.4.3.0001-2 | all |
bullseye | 2.0.1-2 | all |
buster | 1.5.2-1 | all |
stretch | 1.5.0-2 | all |
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License: DFSG free
|
BioRuby project aims to implement an integrated environment for
Bioinformatics with Ruby language. Design philosophy of the BioRuby library
is KISS (keep it simple, stupid) to maximize the usability and the
efficiency for biologists as a daily tool. The project was started in Japan
and supported by University of Tokyo (Human Genome Center), Kyoto University
(Bioinformatics Center) and the Open Bio Foundation.
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ruby-crb-blast
Run conditional reciprocal best blast
|
Versions of package ruby-crb-blast |
Release | Version | Architectures |
bookworm | 0.6.9-4 | all |
stretch | 0.6.8-1 | all |
sid | 0.6.9-5 | all |
trixie | 0.6.9-5 | all |
bullseye | 0.6.9-4 | all |
buster | 0.6.9-2 | all |
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License: DFSG free
|
CRB-BLAST is a novel method for finding orthologs between one set of sequences
and another. This is particularly useful in genome and transcriptome
annotation.
CRB-BLAST initially performs a standard reciprocal best BLAST. It does this by
performing BLAST alignments of query->target and target->query. Reciprocal
best BLAST hits are those where the best match for any given query sequence in
the query->target alignment is also the best hit of the match in the reverse
(target->query) alignment.
Reciprocal best BLAST is a very conservative way to assign orthologs. The main
innovation in CRB-BLAST is to learn an appropriate e-value cutoff to apply to
each pairwise alignment by taking into account the overall relatedness of the
two datasets being compared. This is done by fitting a function to the
distribution of alignment e-values over sequence lengths. The function
provides the e-value cutoff for a sequence of given length.
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sbmltoolbox
libsbml toolbox for octave and matlab
|
Versions of package sbmltoolbox |
Release | Version | Architectures |
sid | 4.1.0-5.1 | all |
jessie | 4.1.0-1 | all |
bookworm | 4.1.0-5 | all |
bullseye | 4.1.0-5 | all |
buster | 4.1.0-4 | all |
stretch | 4.1.0-3 | all |
trixie | 4.1.0-5.1 | all |
|
License: DFSG free
|
The SBMLToolbox provides a set of basic functions for reading, writing,
manipulating, and simulating SBML (System Biology Meta Language)
models. It is a free Open Source package on top of the libSBML with
full compatibility to work with MATLAB and Octave alike and share models
between the two systems.
The toolbox is not a complete turn key solution for Systems Biology.
It has its emphasis on easing the handling of SBML data and serves
as a starting point for users and developers to establish their own
methods.
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snakemake
pythonic workflow management system
|
Versions of package snakemake |
Release | Version | Architectures |
stretch | 3.10.0-1 | all |
bullseye | 5.24.1-2 | all |
bookworm | 7.21.0-1 | all |
sid | 7.32.4-6 | all |
buster | 5.4.0-1 | all |
trixie | 7.32.4-6 | all |
upstream | 8.25.5 |
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License: DFSG free
|
Build systems like GNU Make are frequently used to create complicated
workflows, e.g. in bioinformatics. This project aims to reduce the
complexity of creating workflows by providing a clean and modern domain
specific language (DSL) in Python style, together with a fast and
comfortable execution environment.
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toil
cross-platform workflow engine
|
Versions of package toil |
Release | Version | Architectures |
buster | 3.18.0-2 | all |
bullseye | 5.2.0-5 | all |
sid | 6.1.0-4 | all |
bookworm | 5.9.2-2+deb12u1 | all |
upstream | 7.0.0 |
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License: DFSG free
|
Toil is a scalable, efficient, cross-platform and easy-to-use workflow
engine in pure Python. It works with several well established load
balancers like Slurm or the Sun Grid Engine. Toil is also compatible with
the Common Workflow Language (CWL) via the "toil-cwl-runner" interface, which
this package make available via the Debian alternativess system under the
alias "cwl-runner".
Please cite:
John Vivian, Arjun Arkal Rao, Frank Austin Nothaft, Christopher Ketchum, Joel Armstrong, Adam Novak, Jacob Pfeil, Jake Narkizian Alden D. Deran, Audrey Musselman-Brown, Hannes Schmidt, Peter Amstutz, Brian Craft, Mary Goldman, Kate Rosenbloom, Melissa Cline, Brian O'Connor, Megan Hanna, Chet Birger, W. James Kent David A. Patterson, Anthony D. Joseph, Jingchun Zhu, Sasha Zaranek, Gad Getz, David Haussler and Benedict Paten:
Toil enables reproducible, open source, big biomedical data analyses.
Nature Biotechnology
35(4):314–316
(2017)
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|
Official Debian packages with lower relevance
capsule-nextflow
packaging and deployment tool for Java applications
|
Versions of package capsule-nextflow |
Release | Version | Architectures |
trixie | 1.1.1+dfsg-1 | all |
sid | 1.1.1+dfsg-1 | all |
bookworm | 1.1.1+dfsg-1 | all |
|
License: DFSG free
|
A capsule is a single executable JAR that contains everything an application
needs to run either in the form of embedded files or as declarative metadata.
It can contain JAR artifacts, dependencies and resources, native libraries,
the required Java Runtime Environment version, the Java Virtual Machine flags
required to run the application well, Java or native agents and more. In
short, a capsule is a self-contained JAR that knows everything there is to
know about how to run the application the way it is meant to run.
One way of thinking about a capsule is as a fat JAR on steroids (that also
allows native libraries and never interferes with your dependencies) and a
declarative startup script rolled into one; another, is to see it is as the
deploy-time counterpart to your build tool. Just as a build tool manages your
build, Capsule manages the launching of your application.
This package contains a fork of the original capsule project. This fork is
suited as a dependency of nextflow.
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conda-package-handling
create and extract conda packages of various formats
|
Versions of package conda-package-handling |
Release | Version | Architectures |
bookworm | 2.0.1-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 2.3.0-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 2.3.0-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.7.2-2+deb11u1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
upstream | 2.4.0 |
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License: DFSG free
|
Cph is an abstraction of conda package handling and a tool for
extracting, creating, and converting between formats.
At the time of writing, the standard conda package format is a .tar.bz2
file. That will need to be maintained for quite a long time, thanks to
the long tail of people using old conda versions. There is a new conda
format, described at https://docs.google.com/document/d/1HGKsbg_j69rKXP-
ihhpCb1kNQSE8Iy3yOsUU2x68x8uw/edit?usp=sharing. This new format is
designed to have much faster metadata access and utilize more modern
compression algorithms, while also facilitating package signing without
adding sidecar files.
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ctdconverter
Convert CTD files into Galaxy tool and CWL CommandLineTool files
|
Versions of package ctdconverter |
Release | Version | Architectures |
buster | 2.0-4 | all |
trixie | 2.1-8 | all |
sid | 2.1-8 | all |
bookworm | 2.1-5 | all |
stretch-backports | 2.0-4~bpo9+1 | all |
bullseye | 2.1-3 | all |
upstream | 3.0a1 |
|
License: DFSG free
|
Common Tool Descriptors (CTDs) are XML documents that represent the inputs,
outputs, parameters of command line tools in a platform-independent way.
CTDConverter, given one or more Common Tool Descriptors (CTD) XML files,
generates Galaxy tool wrappers and Common Workflow Language (CWL) Command
Line Tool v1.0 standard descriptions from CTD files.
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cthreadpool-dev
minimal ANSI C thread pool - development files
|
Versions of package cthreadpool-dev |
Release | Version | Architectures |
bookworm | 0.0+git20201207.b259a6e-1 | all |
sid | 0.0+git20231218.4eb5a69-1 | all |
bullseye | 0.0+git20170424-2 | all |
trixie | 0.0+git20231218.4eb5a69-1 | all |
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License: DFSG free
|
These are C development files for the C-Thread-Pool library.
This is a minimal but advanced threadpool implementation.
- ANCI C and POSIX compliant
- Pause/resume/wait as you like
- Simple easy-to-digest API
- Well tested
This software does not ship as a shared library since it is
very small and there is a technical difficulty with this
implementation.
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cwlformat
code formatter for Common Workflow Language
|
Versions of package cwlformat |
Release | Version | Architectures |
bookworm | 2022.02.18-2 | all |
sid | 2022.02.18-3 | all |
trixie | 2022.02.18-3 | all |
bullseye | 2021.01.05-1 | all |
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License: DFSG free
|
CWL Format is a specification and a reference implementation
for a very opinionated CWL code formatter.
It outputs Common Workflow Language(CWL) in a standardized YAML
format. It has no settings or options because you have better
things to do with your time. And because CWL Format is always correct.
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cwltest
Common Workflow Language testing framework
|
Versions of package cwltest |
Release | Version | Architectures |
trixie | 2.5.20241122133319-1 | all |
sid | 2.5.20241122133319-1 | all |
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License: DFSG free
|
This is a testing tool for checking the output of Tools and Workflows described
with the Common Workflow Language. Among other uses, it is used to run the CWL
conformance tests.
Please cite:
Peter Amstutz, Michael R. Crusoe, Nebojša Tijanić, Brad Chapman, John Chilton, Michael Heuer, Andrey Kartashov, Dan Leehr, Hervé Ménager, Maya Nedeljkovich, Matt Scales, Stian Soiland-Reyes and Luka Stojanovic:
Common Workflow Language, v1.0.
(2016)
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libargs-dev
simple header-only C++ argument parser library
|
Versions of package libargs-dev |
Release | Version | Architectures |
bullseye | 6.2.4-1 | all |
sid | 6.4.1-1 | all |
trixie | 6.4.1-1 | all |
bookworm | 6.4.1-1 | all |
upstream | 6.4.6 |
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License: DFSG free
|
Args is a simple, small, flexible, header-only C++ argument
parssing library.
This is designed to appear somewhat similar to Python's argparse, but in
C++, with static type checking, and hopefully a lot faster (also
allowing fully nestable group logic, where Python's argparse does not).
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libbam-dev
manipulates nucleotide sequence alignments in BAM or SAM format
|
Versions of package libbam-dev |
Release | Version | Architectures |
sid | 0.1.19+dfsg-6 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
jessie | 0.1.19-2 | amd64,armel,armhf,i386 |
stretch | 0.1.19-2 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 0.1.19-4 | amd64,arm64,armhf,i386 |
bullseye | 0.1.19+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 0.1.19+dfsg-6 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 0.1.19+dfsg-6 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
Debtags of package libbam-dev: |
devel | library |
role | devel-lib |
|
License: DFSG free
|
The BAM library provides I/O and various operations on manipulating nucleotide
sequence alignments in the BAM (Binary Alignment/Mapping) or SAM (Sequence
Alignment/Map) format. It now supports importing from or exporting to SAM,
sorting, merging, generating pileup, and quickly retrieval of reads overlapped
with a specified region.
This library is part of SAMtools version 0.1.19. It is obsolete and provided
only to build software that has not yet transitioned to the HTSlib, which
replaces this library.
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libbbhash-dev
bloom-filter based minimal perfect hash function library
|
Versions of package libbbhash-dev |
Release | Version | Architectures |
bookworm | 1.0.0-5 | amd64,arm64,mips64el,ppc64el,s390x |
trixie | 1.0.0-6 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.0.0-3 | amd64,arm64,mips64el,ppc64el,s390x |
sid | 1.0.0-6 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
|
License: DFSG free
|
BBHash is a simple library for building minimal perfect hash
function. It is designed to handle large scale datasets. The function
is just a little bit larger than other state-of-the-art libraries, it
takes approximately 3 bits / elements (compared to 2.62 bits/elem for
the emphf lib), but construction is faster and does not require
additional memory.
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|
libbifrost-dev
static library and header files for libbifrost
|
Versions of package libbifrost-dev |
Release | Version | Architectures |
trixie | 1.3.1-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
sid | 1.3.1-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
upstream | 1.3.5 |
|
License: DFSG free
|
Libbifrost-dev is the development library for the command-line tool
bifrost for sequencing that features a broad range of functions, such as
indexing, editing, and querying the graph, and includes a graph coloring
method that maps each k-mer of the graph to the genomes it occurs in.
- Build, index, color and query the compacted de Bruijn graph
- No need to build the uncompacted de Bruijn graph
- Reads or assembled genomes as input
- Output graph in GFA (can be visualized with Bandage), FASTA or binary
- Graph cleaning: short tip clipping, etc.
- Multi-threaded
- No parameters to estimate with other tools
- Exact or approximate k-mer search of queries
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|
libbiojava4-java
Java API to biological data and applications (default version)
|
Versions of package libbiojava4-java |
Release | Version | Architectures |
bullseye | 4.2.12+dfsg-3.1 | all |
bookworm | 4.2.12+dfsg-8 | all |
trixie | 4.2.12+dfsg-8 | all |
sid | 4.2.12+dfsg-8 | all |
stretch | 4.2.5+dfsg-1 | all |
buster | 4.2.12+dfsg-2 | all |
|
License: DFSG free
|
BioJava is an open-source project dedicated to providing a Java framework
for processing biological data. It includes objects for manipulating
sequences, file parsers, server support, access to BioSQL
and Ensembl databases, and powerful analysis and statistical routines
including a dynamic programming toolkit.
BioJava is provided by a vibrant community which meets annually at
the Bioinformatics Open Source Conference (BOSC) that traditionally
accompanies the Intelligent Systems in Molecular Biology (ISMB)
meeting. Much like BioPerl, the employment of this library is valuable
for everybody active in the field because of the many tricks of the
trade one learns just by communicating on the mailing list.
This is a wrapper package which should enable smooth upgrades to new
versions.
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|
libbiosoup-dev
C++ header-only support library for bioinformatics tools
|
Versions of package libbiosoup-dev |
Release | Version | Architectures |
trixie | 0.11.0-2 | all |
bookworm | 0.10.0-4 | all |
sid | 0.11.0-2 | all |
|
License: DFSG free
|
Biosoup is a c++ collection of header only data structures used for storage
and logging in bioinformatics tools.
|
|
libbtllib-dev
Bioinformatics Technology Lab common code library
|
Versions of package libbtllib-dev |
Release | Version | Architectures |
sid | 1.4.10+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64 |
trixie | 1.4.10+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64 |
bookworm | 1.4.10+dfsg-1 | amd64,arm64,mips64el,ppc64el |
upstream | 1.7.5 |
|
License: DFSG free
|
Bioinformatics Technology Lab common code library in C++ with
Python wrappers.
This package contains the header files and the static library.
|
|
libcapsule-maven-nextflow-java
packaging tool for Java applications with Maven coordinates
|
Versions of package libcapsule-maven-nextflow-java |
Release | Version | Architectures |
trixie | 1.0.3.1+dfsg-5 | all |
bookworm | 1.0.3.1+dfsg-5 | all |
sid | 1.0.3.1+dfsg-5 | all |
|
License: DFSG free
|
A capsule is a single executable JAR that contains everything an application
needs to run either in the form of embedded files or as declarative metadata.
Maven Capsule is a capsule that allows the creations of capsules that, instead
of embedding their dependencies, download all or some of them from a Maven
repository. The dependencies are downloaded, cached locally, and shared among
other capsules that also depend on them. In addition, this capsule allows
specifying capsule metadata in a POM file in addition to the manifest.
A capsule with the Maven caplet that has all (or almost all) of its
dependencies downloaded rather than embedded is known as a "thin" capsule (as
opposed to a "fat" capsule, which embeds all of its dependencies). In fact, a
capsule may not contain any of the application's classes/JARs at all. Instead,
the capsule's manifest may contain these attributes alone (and no files in the
capsule JAR besides the manifest). When the capsule is launched, the newest
available version of the application will be downloaded, cached and launched.
This package contains a fork of the original capsule-maven project. This fork
is suited as a dependency of nextflow.
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|
libconcurrentqueue-dev
industrial-strength lock-free queue for C++
|
Versions of package libconcurrentqueue-dev |
Release | Version | Architectures |
bullseye | 1.0.2+ds-3 | all |
bookworm | 1.0.3+ds-1 | all |
sid | 1.0.4+ds-2 | amd64,arm64,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 1.0.4+ds-1 | amd64,arm64,armhf,i386,mips64el,ppc64el,riscv64,s390x |
|
License: DFSG free
|
Features
- Knock-your-socks-off blazing fast performance.
- Single-header implementation. Just drop it in your project.
- Fully thread-safe lock-free queue. Use concurrently from any number
of threads.
- C++11 implementation -- elements are moved (instead of copied)
where possible.
- Templated, obviating the need to deal exclusively with pointers --
memory is managed for you.
- No artificial limitations on element types or maximum count.
Memory can be allocated once up-front, or dynamically as needed.
- Fully portable (no assembly; all is done through standard C++11
primitives).
- Supports super-fast bulk operations.
- Includes a low-overhead blocking version (BlockingConcurrentQueue).
- Exception safe.
Reasons to use
There are not that many full-fledged lock-free queues for C++. Boost has
one, but it's limited to objects with trivial assignment operators and
trivial destructors, for example. Intel's TBB queue isn't lock-free,
and requires trivial constructors too. There're many academic papers
that implement lock-free queues in C++, but usable source code is hard
to find, and tests even more so.
This queue not only has less limitations than others (for the most part),
but it's also faster. It's been fairly well-tested, and offers advanced
features like bulk enqueueing/dequeueing (which, with the new design, is
much faster than one element at a time, approaching and even surpassing
the speed of a non-concurrent queue even under heavy contention).
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|
libdisorder-dev
library for entropy measurement of byte streams (devel)
|
Versions of package libdisorder-dev |
Release | Version | Architectures |
bullseye | 0.0.2+git20130809.8062ee1-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 0.0.2+git20130809.8062ee1-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
stretch | 0.0.2-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el |
buster | 0.0.2+git20130809.8062ee1-1 | amd64,arm64,armhf,i386 |
sid | 0.0.2+git20130809.8062ee1-4 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 0.0.2+git20130809.8062ee1-4 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
|
License: DFSG free
|
This library provides a function to calculate the Shannon index (H)
of byte streams.
This is the development package containing the statically linked
library and the header files.
|
|
libfreecontact-dev
fast protein contact predictor library - development files
|
Versions of package libfreecontact-dev |
Release | Version | Architectures |
bookworm | 1.0.21-13 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.0.21-14 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.0.21-9 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
stretch | 1.0.21-5 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
trixie | 1.0.21-14 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster | 1.0.21-7 | amd64,arm64,armhf,i386 |
|
License: DFSG free
|
FreeContact is a protein residue contact predictor optimized for speed.
Its input is a multiple sequence alignment. FreeContact can function as an
accelerated drop-in for the published contact predictors
EVfold-mfDCA of DS. Marks (2011) and
PSICOV of D. Jones (2011).
FreeContact is accelerated by a combination of vector instructions, multiple
threads, and faster implementation of key parts.
Depending on the alignment, 8-fold or higher speedups are possible.
A sufficiently large alignment is required for meaningful results.
As a minimum, an alignment with an effective (after-weighting) sequence count
bigger than the length of the query sequence should be used. Alignments with
tens of thousands of (effective) sequences are considered good input.
jackhmmer(1) from the hmmer package, or hhblits(1) from hhsuite
can be used to generate the alignments, for example.
This package contains files necessary for developing applications with
libfreecontact.
|
|
libfreecontact-doc
documentation for libfreecontact
|
Versions of package libfreecontact-doc |
Release | Version | Architectures |
bookworm | 1.0.21-13 | all |
buster | 1.0.21-7 | all |
stretch | 1.0.21-5 | all |
jessie | 1.0.21-3 | all |
sid | 1.0.21-14 | all |
trixie | 1.0.21-14 | all |
bullseye | 1.0.21-9 | all |
|
License: DFSG free
|
FreeContact is a protein residue contact predictor optimized for speed.
Its input is a multiple sequence alignment. FreeContact can function as an
accelerated drop-in for the published contact predictors
EVfold-mfDCA of DS. Marks (2011) and
PSICOV of D. Jones (2011).
FreeContact is accelerated by a combination of vector instructions, multiple
threads, and faster implementation of key parts.
Depending on the alignment, 8-fold or higher speedups are possible.
A sufficiently large alignment is required for meaningful results.
As a minimum, an alignment with an effective (after-weighting) sequence count
bigger than the length of the query sequence should be used. Alignments with
tens of thousands of (effective) sequences are considered good input.
jackhmmer(1) from the hmmer package, or hhblits(1) from hhsuite
can be used to generate the alignments, for example.
This package contains HTML documentation for libfreecontact.
|
|
libfreecontact-perl
fast protein contact predictor - binding for Perl
|
Versions of package libfreecontact-perl |
Release | Version | Architectures |
jessie | 0.08-2 | amd64,armel,armhf,i386 |
sid | 0.08-9 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch | 0.08-5 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 0.08-7 | amd64,arm64,armhf,i386 |
bullseye | 0.08-8 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 0.08-9 | amd64,arm64,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 0.08-9 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
Debtags of package libfreecontact-perl: |
devel | lang:perl, library |
|
License: DFSG free
|
FreeContact is a protein residue contact predictor optimized for speed.
Its input is a multiple sequence alignment. FreeContact can function as an
accelerated drop-in for the published contact predictors
EVfold-mfDCA of DS. Marks (2011) and
PSICOV of D. Jones (2011).
FreeContact is accelerated by a combination of vector instructions, multiple
threads, and faster implementation of key parts.
Depending on the alignment, 8-fold or higher speedups are possible.
A sufficiently large alignment is required for meaningful results.
As a minimum, an alignment with an effective (after-weighting) sequence count
bigger than the length of the query sequence should be used. Alignments with
tens of thousands of (effective) sequences are considered good input.
jackhmmer(1) from the hmmer package, or hhblits(1) from hhsuite
can be used to generate the alignments, for example.
This package contains the Perl binding.
|
|
libgatk-bwamem-java
interface to call Heng Li's bwa mem aligner from Java code
|
Versions of package libgatk-bwamem-java |
Release | Version | Architectures |
bookworm | 1.0.4+dfsg2-2 | all |
sid | 1.0.4+dfsg2-3 | all |
trixie | 1.0.4+dfsg2-3 | all |
|
License: DFSG free
|
BWA (Burrows-Wheeler Aligner) is a software package for mapping low-divergent
sequences against a large reference genome, such as the human genome. It is
written in C.
gatk-bwamem provides a Java library and a shared library to allow one to use
BWA from Java code.
This package contains the Java library.
|
|
libgatk-bwamem-jni
interface to call Heng Li's bwa mem aligner from Java code (jni)
|
Versions of package libgatk-bwamem-jni |
Release | Version | Architectures |
sid | 1.0.4+dfsg2-3 | amd64,arm64,armel,armhf,mips64el,ppc64el,riscv64 |
bookworm | 1.0.4+dfsg2-2 | amd64,arm64,armel,armhf,mips64el,mipsel,ppc64el |
trixie | 1.0.4+dfsg2-3 | amd64,arm64,armel,armhf,mips64el,ppc64el,riscv64 |
|
License: DFSG free
|
BWA (Burrows-Wheeler Aligner) is a software package for mapping low-divergent
sequences against a large reference genome, such as the human genome. It is
written in C.
gatk-bwamem provides a Java library and a shared library to allow one to use
BWA from Java code.
This package contains the native library.
|
|
libgatk-fermilite-java
interface to call Heng Li's fermi-lite assembler from Java code
|
Versions of package libgatk-fermilite-java |
Release | Version | Architectures |
sid | 1.2.1+dfsg-2 | all |
bookworm | 1.2.1+dfsg-2 | all |
trixie | 1.2.1+dfsg-2 | all |
|
License: DFSG free
|
Fml-asm (fermi-lite assembler) is a command-line tool for assembling Illumina
short reads in regions from 100bp to 10 million bp in size, based on the
fermi-lite library.
gatk-fermilite provides a Java library and a shared library to allow one to use
fermilite from Java code.
This package contains the Java library.
|
|
libgatk-fermilite-jni
interface to call Heng Li's fermi-lite assembler from Java code (jni)
|
Versions of package libgatk-fermilite-jni |
Release | Version | Architectures |
trixie | 1.2.1+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
sid | 1.2.1+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
bookworm | 1.2.1+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
|
License: DFSG free
|
Fml-asm (fermi-lite assembler) is a command-line tool for assembling Illumina
short reads in regions from 100bp to 10 million bp in size, based on the
fermi-lite library.
gatk-fermilite provides a Java library and a shared library to allow one to use
fermilite from Java code.
This package contains the JNI.
|
|
libgatk-native-bindings-java
library of native bindings for gatk and picard-tools
|
Versions of package libgatk-native-bindings-java |
Release | Version | Architectures |
trixie | 1.0.0+dfsg-2 | all |
bullseye | 1.0.0-2.1 | all |
buster | 1.0.0-2 | all |
bookworm | 1.0.0+dfsg-2 | all |
sid | 1.0.0+dfsg-2 | all |
|
License: DFSG free
|
Utilitary library for gatk and picard-tools, bringing in pairhmm and
smithwaterman classes.
|
|
libgenomicsdb-dev
sparse array storage library for genomics (development files)
|
Versions of package libgenomicsdb-dev |
Release | Version | Architectures |
bookworm | 1.4.4-3 | amd64,mips64el |
sid | 1.5.4-2 | amd64,mips64el |
|
License: DFSG free
|
GenomicsDB is built on top of a htslib fork and an internal array storage
system for importing, querying and transforming variant data. Variant data is
sparse by nature (sparse relative to the whole genome) and using sparse array
data stores is a perfect fit for storing such data.
The GenomicsDB stores variant data in a 2D array where:
- Each column corresponds to a genomic position (chromosome + position);
- Each row corresponds to a sample in a VCF (or CallSet in the GA4GH
terminology);
- Each cell contains data for a given sample/CallSet at a given position;
data is stored in the form of cell attributes;
- Cells are stored in column major order - this makes accessing cells with
the same column index (i.e. data for a given genomic position over all
samples) fast.
- Variant interval/gVCF interval data is stored in a cell at the start of the
interval. The END is stored as a cell attribute. For variant intervals
(such as deletions and gVCF REF blocks), an additional cell is stored at
the END value of the variant interval. When queried for a given genomic
position, the query library performs an efficient sweep to determine all
intervals that intersect with the queried position.
This package contains the development files and the static library.
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|
libgenomicsdb-java
sparse array storage library for genomics (Java library)
|
Versions of package libgenomicsdb-java |
Release | Version | Architectures |
sid | 1.5.4-2 | all |
bookworm | 1.4.4-3 | all |
|
License: DFSG free
|
GenomicsDB is built on top of a htslib fork and an internal array storage
system for importing, querying and transforming variant data. Variant data is
sparse by nature (sparse relative to the whole genome) and using sparse array
data stores is a perfect fit for storing such data.
The GenomicsDB stores variant data in a 2D array where:
- Each column corresponds to a genomic position (chromosome + position);
- Each row corresponds to a sample in a VCF (or CallSet in the GA4GH
terminology);
- Each cell contains data for a given sample/CallSet at a given position;
data is stored in the form of cell attributes;
- Cells are stored in column major order - this makes accessing cells with
the same column index (i.e. data for a given genomic position over all
samples) fast.
- Variant interval/gVCF interval data is stored in a cell at the start of the
interval. The END is stored as a cell attribute. For variant intervals
(such as deletions and gVCF REF blocks), an additional cell is stored at
the END value of the variant interval. When queried for a given genomic
position, the query library performs an efficient sweep to determine all
intervals that intersect with the queried position.
This package contains the Java library.
|
|
libicb-utils-java
Java library of utilities to manage files and compute statistics
|
Versions of package libicb-utils-java |
Release | Version | Architectures |
bookworm | 2.0.1+git20161002.afee1d9-5 | all |
trixie | 2.0.1+git20161002.afee1d9-5 | all |
sid | 2.0.1+git20161002.afee1d9-5 | all |
bullseye | 2.0.1+git20161002.afee1d9-4 | all |
|
License: DFSG free
|
icb-utils is a group of tools originally designed by the Campagne laboratory
for computational biomedicine software.
They include extensions of standard Java to manage io, extended iterator
classes, hashtables, network-related classes, as well as a set of classes
allowing for the computation of statistics.
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|
libmaus2-dev
collection of data structures and algorithms for biobambam (devel)
|
Versions of package libmaus2-dev |
Release | Version | Architectures |
bookworm | 2.0.813+ds-1 | amd64,arm64,i386,ppc64el |
sid | 2.0.813+ds-3 | amd64,i386,mips64el,ppc64el,riscv64 |
trixie | 2.0.813+ds-3 | amd64,i386,mips64el,ppc64el,riscv64 |
bullseye | 2.0.768+dfsg-2 | amd64,arm64,i386,ppc64el |
|
License: DFSG free
|
Libmaus2 is a collection of data structures and algorithms. It contains
- I/O classes (single byte and UTF-8)
- bitio classes (input, output and various forms of bit level manipulation)
- text indexing classes (suffix and LCP array, fulltext and minute (FM), ...)
- BAM sequence alignment files input/output (simple and collating)
and many lower level support classes.
This package contains header files and static libraries.
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|
libmilib-java
library for Next Generation Sequencing (NGS) data processing
|
Versions of package libmilib-java |
Release | Version | Architectures |
bullseye | 1.13-1 | all |
sid | 2.2.0+dfsg-1 | all |
trixie | 2.2.0+dfsg-1 | all |
buster | 1.10-2 | all |
bookworm | 2.2.0+dfsg-1 | all |
|
License: DFSG free
|
A helping Java package adopted by a range of Open Source tools for the
analysis of B and T cell repertoires.
|
|
libminimap-dev
development headers for libminimap
|
Versions of package libminimap-dev |
Release | Version | Architectures |
bookworm | 0.2-7 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 0.2-8 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster | 0.2-4 | amd64,arm64,armhf,i386 |
stretch | 0.2-3 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
trixie | 0.2-8 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 0.2-5 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
|
License: DFSG free
|
Minimap is an experimental tool to efficiently find multiple approximate
mapping positions between two sets of long sequences, such as between
DNA reads and reference genomes, between genomes and between long noisy reads.
This package contains the C library headers for using minimap in custom tools,
along with a static library.
|
|
libmodhmm-dev
library for constructing, training and scoring hidden Markov models (dev)
|
Versions of package libmodhmm-dev |
Release | Version | Architectures |
bookworm | 1.0+dfsg-5 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.0+dfsg-7 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.0+dfsg-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 1.0+dfsg-3 | amd64,arm64,armhf,i386 |
trixie | 1.0+dfsg-7 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch-backports | 1.0+dfsg-2~bpo9+1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
|
License: DFSG free
|
Library for constructing, training and scoring hidden Markov models. It
is provided with PSORTb but might be used separately.
PSORTb enables prediction of bacterial protein subcellular localization
(SCL) and provides a quick and inexpensive means for gaining insight
into protein function, verifying experimental results, annotating newly
sequenced bacterial genomes, detecting potential cell surface/secreted
drug targets, as well as identifying biomarkers for microbes.
This library needed by PSORTb is distributed separately by upstream.
This package contains the static library which is needed to link PSORTb.
|
|
libpbcopper-dev
data structures, algorithms, and utilities for C++ applications -- header files
|
Versions of package libpbcopper-dev |
Release | Version | Architectures |
bookworm | 2.0.0+dfsg-2 | amd64,arm64,mips64el,ppc64el,s390x |
trixie | 2.3.0+dfsg-2 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
sid | 2.3.0+dfsg-2 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.8.0+dfsg-2 | amd64,arm64,mips64el,ppc64el,s390x |
buster | 0.4.1+dfsg-2 | amd64,arm64,armhf,i386 |
|
License: DFSG free
|
pbcopper provides general tools for C++ applications. It is developed
for use by applications of the Pacific Biosciences SMRT Analysis
suite.
This package contains the header files and static library
|
|
librostlab-blast-doc
very fast C++ library for parsing the output of NCBI BLAST programs (doc)
|
Versions of package librostlab-blast-doc |
Release | Version | Architectures |
bullseye | 1.0.1-10 | all |
trixie | 1.0.1-14 | all |
sid | 1.0.1-14 | all |
buster | 1.0.1-10 | all |
stretch | 1.0.1-7 | all |
jessie | 1.0.1-3 | all |
bookworm | 1.0.1-13 | all |
|
License: DFSG free
|
This package provides a very fast library for parsing the default output of
NCBI BLAST programs into a C++ structure.
libzerg is faster, but it provides only lexing (i.e. it only returns pairs
of token identifiers and token string values). librostlab-blast uses a
parser generated with bison on top of a flex-generated lexer very similar to
that of libzerg.
This package contains html and pdf documentation.
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librostlab-doc
C++ library for computational biology (documentation)
|
Versions of package librostlab-doc |
Release | Version | Architectures |
bookworm | 1.0.20-12 | all |
trixie | 1.0.20-13.1 | all |
sid | 1.0.20-13.1 | all |
buster | 1.0.20-8 | all |
stretch | 1.0.20-6 | all |
jessie | 1.0.20-4 | all |
bullseye | 1.0.20-10 | all |
|
License: DFSG free
|
This library was developed by the Rost Lab. The lab's research is
driven by a conviction that protein and DNA sequences encode a
significant core of information about the ultimate structure and
function of genetic material and its gene products.
The library provides the following facilities:
- current working directory resource
- exception with stack backtrace
- file lock resource
- passwd and group structures for C++
- effective uid and gid resource
- rostlab::bio::seq class with stream input operator for FASTA format
- umask resource
This package contains html documentation.
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libsavvy-dev
C++ interface for the SAV file format
|
Versions of package libsavvy-dev |
Release | Version | Architectures |
bookworm | 2.1.0-2 | all |
sid | 2.1.0-3 | all |
trixie | 2.1.0-3 | all |
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License: DFSG free
|
Savvy is the official C++ interface for the SAV file format and offers
seamless support for BCF and VCF files.
This package contains the header files for development.
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libsuma-dev
headers and static library for sumatra and sumaclust
|
Versions of package libsuma-dev |
Release | Version | Architectures |
bullseye | 1.0.36-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.0.36-4 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 1.0.36-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
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License: DFSG free
|
Sumatra is a tool for fast and exact comparison and clustering of sequences
and sumaclust can be used for fast and exact clustering of genomic sequences.
Both tools are using this common library.
This package provides the static library and header files.
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libsvmloc-dev
PSORTb adapted library for svm machine-learning library (dev)
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Versions of package libsvmloc-dev |
Release | Version | Architectures |
stretch-backports | 1.0+dfsg-2~bpo9+1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
bullseye | 1.0+dfsg-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.0+dfsg-5 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.0+dfsg-7 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 1.0+dfsg-7 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster | 1.0+dfsg-3 | amd64,arm64,armhf,i386 |
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License: DFSG free
|
Libsvm is a machine-learning library which is an easy-to-use package
for support vector classification, regression and one-class SVM. It
supports multi-class classification, probability outputs, and
parameter selection.
PSORTb was featuring a code copy plus some local additions. This
library is linked against the Debian packaged libsvn and just contains
the PSORTb extensions.
PSORTb enables prediction of bacterial protein subcellular localization
(SCL) and provides a quick and inexpensive means for gaining insight
into protein function, verifying experimental results, annotating newly
sequenced bacterial genomes, detecting potential cell surface/secreted
drug targets, as well as identifying biomarkers for microbes.
This library needed by PSORTb is distributed separately by upstream.
This package contains the static library which is needed to link PSORTb.
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libterraces-dev
enumerate terraces in phylogenetic tree space (development lib)
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Versions of package libterraces-dev |
Release | Version | Architectures |
trixie | 0.0+git20200413.8af2e4c+dfsg-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 0.0+git20200413.8af2e4c+dfsg-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 0.0+git20200413.8af2e4c+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
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License: DFSG free
|
Terraphast takes a .nkw file in Newick format and a genes/sites file,
which denotes whether (1) or not (0) gene i is present in species j.
Program output states some imput data properties, the species whose leaf
edge is used as a new tree root, and the resulting supertree in
compressed newick format.
This package contains a library to use the terraphast algorithm in own
projects.
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libtfbs-perl
scanning DNA sequence with a position weight matrix
|
Versions of package libtfbs-perl |
Release | Version | Architectures |
trixie | 0.7.1+ds-4 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 0.7.1+ds-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
jessie | 0.6.1+dfsg-1 | amd64,armel,armhf,i386 |
stretch | 0.7.0+dfsg-4 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
bullseye | 0.7.1-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 0.7.1-2 | amd64,arm64,armhf,i386 |
sid | 0.7.1+ds-4 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
Debtags of package libtfbs-perl: |
field | biology, biology:bioinformatics |
role | devel-lib |
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License: DFSG free
|
The TFBS perl modules comprise a set of routines to interact with the
Transfac and Jaspar databases that describe a special family of proteins,
the transcription factors. These bind to genomic DNA to initiate (or
prevent) the readout of a gene. Once multiple binding sites are known
for a transcription factor, these are gathered in a single file and are
aligned in order to find position-specific characteristica that might
be used to predict such binding events in novel DNA sequences.
If you use TFBS in your work, please cite "Lenhard B., Wasserman W.W. (2002)
TFBS: Computational framework for transcription factor binding site analysis.
Bioinformatics 18:1135-1136".
Note: the TFBS perl module is no longer under active development. All the
functionality can be found in the TFBSTools Bioconductor package; users are
highly encouraged to switch. http://bioconductor.org/packages/TFBSTools/
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libvbz-hdf-plugin-dev
VBZ compression plugin for nanopore signal data (devel)
|
Versions of package libvbz-hdf-plugin-dev |
Release | Version | Architectures |
trixie | 1.0.2-3.1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
bookworm | 1.0.2-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
sid | 1.0.2-3.1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
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License: DFSG free
|
VBZ Compression uses variable byte integer encoding to compress nanopore
signal data.
The performance of VBZ is achieved by taking advantage of the properties
of the raw signal and therefore is most effective when applied to the
signal dataset. Other datasets you may have in your Fast5 files will not
be able to take advantage of the default VBZ settings for compression.
VBZ will be used as the default compression scheme in a future release
of MinKNOW.
This package contains the header files.
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libxxsds-dynamic-dev
succinct and compressed fully-dynamic data structures library
|
Versions of package libxxsds-dynamic-dev |
Release | Version | Architectures |
bookworm | 1.0~alpha.1+git20210426.548c6f7-1 | all |
sid | 1.0~alpha.1+git20210426.548c6f7-2 | all |
trixie | 1.0~alpha.1+git20210426.548c6f7-2 | all |
bullseye | 1.0~alpha.1+2020072524git5390b6c-3 | all |
upstream | 1.0~alpha.1+git20240520.0540076 |
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License: DFSG free
|
This library offers space- and time-efficient implementations of some
basic succinct/compressed dynamic data structures. It only ships header
files, i.e. is inclusion only.
DYNAMIC features:
- A succinct Searchable Partial Sums with Indels (SPSI) structure
representing a list of integers s_1, s_2, ..., s_m. Space: about
1.2 * m * ( log(M/m) + log log m )
bits, where
M = m + s_1 + s_2 + ... + s_m.
The structure supports also update operations (i.e. s_i = s_i + delta).
- A Succinct dynamic bitvector supporting rank/select/access/Indel
(RSAI) operations. Space: about 1.2 * n bits.
- A gap-compressed dynamic bitvector supporting rank/select/access/Indel
operations. Space: about 1.2 * b * ( log(n/b) + log log b ) bits,
b being the number of bits set and n being the bitvector length. All
operations take log(b) time.
- A dynamic sparse vector (of integers) with access/Indel operations.
- A dynamic string supporting rank/select/access/Indel operations. The
user can choose at construction time between
fixed-length/gamma/Huffman encoding of the alphabet. All operations
take log(n) * log(sigma) time (or log(n) * H0 with Huffman encoding).
- A run-length encoded dynamic string supporting
rank/select/access/insert operations (removes are not yet
implemented). Space: approximately
R*(1.2 * log(sigma) + 2.4 * (log(n/R)+log log R) )
bits, where R is the number of runs in the string. All operations
take log(R) time.
- A dynamic (left-extend only) entropy/run-length compressed BWT
- A dynamic (left-extend only) entropy/run-length compressed
FM-index. This structure consists in the above BWT + a dynamic suffix
array sampling
Algorithms
- Two algorithms to build LZ77 in repetition-aware RAM working
space. Both algorithms use a run-length encoded BWT with sparse
Suffix array sampling. The first algorithm stores 2 SA samples per
BWT run. The second algorithm (much more space efficient) stores
1 SA sample per LZ factor. From the papers "Computing LZ77 in
Run-Compressed Space", Alberto Policriti and Nicola Prezza, DCC2016
and " LZ77 Computation Based on the Run-Length Encoded BWT", Alberto
Policriti and Nicola Prezza (Algorithmica)
- An algorithm to build the BWT in run-compressed space
- An algorithm to build LZ77 in nH0(2+o(1)) space and n * log n *
H0 time. From the paper "Fast Online Lempel-Ziv Factorization in
Compressed Space", Alberto Policriti and Nicola Prezza, SPIRE2015
- An algorithm to build the BWT in high-order compressed space. The
algorithm runs in O(n * H_k * log log n) average-case time (e.g. good
for DNA) and O(n * H_k * log n) worst-case time. From the paper
"Average linear time and compressed space construction of the
Burrows-Wheeler transform" Policriti A., Gigante N. and Prezza N.,
LATA 2015 (the paper discusses a theoretically faster variant)
The SPSI structure is the building block on which all other structures
are based. This structure is implemented with cache-efficient B-trees.
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python-biopython-doc
Documentation for the Biopython library
|
Versions of package python-biopython-doc |
Release | Version | Architectures |
trixie | 1.84+dfsg-4 | all |
bookworm | 1.80+dfsg-4 | all |
stretch | 1.68+dfsg-3 | all |
sid | 1.84+dfsg-4 | all |
jessie | 1.64+dfsg-5 | all |
bullseye | 1.78+dfsg-4 | all |
buster | 1.73+dfsg-1 | all |
Debtags of package python-biopython-doc: |
devel | doc, lang:python |
field | biology, biology:bioinformatics |
role | documentation |
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License: DFSG free
|
Documentation and examples about how to use the Biopython
library.
This package also contains the unit tests of the test suite
to enable reproducing the test results.
Please cite:
Peter J. A. Cock, Tiago Antao, Jeffrey T. Chang, Brad A. Chapman, Cymon J. Cox, Andrew Dalke, Iddo Friedberg, Thomas Hamelryck, Frank Kauff, Bartek Wilczynski and Michiel J. L. de Hoon:
Biopython: freely available Python tools for computational molecular biology and bioinformatics.
(PubMed,eprint)
Bioinformatics
25(11):1422-1423
(2009)
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python3-alignlib
edit and Hamming distances for biological sequences
|
Versions of package python3-alignlib |
Release | Version | Architectures |
bookworm | 0.1.1+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 0.1.1+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 0.1.1+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 0.1.1+dfsg-1.1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
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License: DFSG free
|
A small Python module providing edit distance and Hamming distance
computation. It is a dependency for the IgDiscover package and
likely future others.
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python3-bel-resources
Python3 utilities for BEL resource files
|
Versions of package python3-bel-resources |
Release | Version | Architectures |
bullseye | 0.0.3-2 | all |
sid | 0.0.3-4 | all |
trixie | 0.0.3-4 | all |
bookworm | 0.0.3-4 | all |
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License: DFSG free
|
This package provides a Python3 interface and utilities
for BEL resource files.
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python3-bioblend
CloudMan and Galaxy API library (Python 3)
|
Versions of package python3-bioblend |
Release | Version | Architectures |
sid | 1.2.0-2 | all |
bookworm | 1.0.0-1 | all |
trixie | 1.2.0-2 | all |
stretch | 0.7.0-2 | all |
buster | 0.7.0-2 | all |
bullseye | 0.7.0-3 | all |
upstream | 1.4.0 |
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License: DFSG free
|
BioBlend is a Python library for interacting with CloudMan and Galaxy's API.
BioBlend is supported and tested on:
· Python 2.6, 2.7, 3.3 and 3.4
· Galaxy release_14.02 and later.
Conceptually, it makes it possible to script and automate the process
of cloud infrastructure provisioning and scaling via CloudMan, and run‐
ning of analyses via Galaxy. In reality, it makes it possible to do
things like this:
· Create a CloudMan compute cluster, via an API and directly from your
local machine:
· Reconnect to an existing CloudMan instance and manipulate it
· Interact with Galaxy via a straightforward API
Although this library allows you to blend these two services into a
cohesive unit, the library itself can be used with either service
irrespective of the other. For example, you can use it to just
manipulate CloudMan clusters or to script the interactions with an
instance of Galaxy running on your laptop.
This package installs the library for Python 3.
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python3-biopython-sql
Biopython support for the BioSQL database schema (Python 3)
|
Versions of package python3-biopython-sql |
Release | Version | Architectures |
stretch | 1.68+dfsg-3 | all |
bookworm | 1.80+dfsg-4 | all |
trixie | 1.84+dfsg-4 | all |
buster | 1.73+dfsg-1 | all |
jessie | 1.64+dfsg-5 | all |
sid | 1.84+dfsg-4 | all |
bullseye | 1.78+dfsg-4 | all |
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License: DFSG free
|
This is the Biopython interface to a BioSQL database (see www.biosql.org
for details). BioPerl, BioJava and BioRuby also provide their own BioSQL
interfaces onto the same shared SQL schema.
Please cite:
Peter J. A. Cock, Tiago Antao, Jeffrey T. Chang, Brad A. Chapman, Cymon J. Cox, Andrew Dalke, Iddo Friedberg, Thomas Hamelryck, Frank Kauff, Bartek Wilczynski and Michiel J. L. de Hoon:
Biopython: freely available Python tools for computational molecular biology and bioinformatics.
(PubMed,eprint)
Bioinformatics
25(11):1422-1423
(2009)
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python3-cgelib
Python3 code to be utilized across the CGE tools
|
Versions of package python3-cgelib |
Release | Version | Architectures |
trixie | 0.7.3-3 | all |
sid | 0.7.3-3 | all |
bookworm | 0.7.3-2 | all |
upstream | 0.7.5 |
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License: DFSG free
|
This package will in time replace the cgecore package. The package
contains classes and functions intended to be utilized across the tools
provide by the Center for Genomic Epidemiology. It is for instance
needed by resfinder package.
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python3-conda-package-streaming
|
Versions of package python3-conda-package-streaming |
Release | Version | Architectures |
sid | 0.10.0-1 | all |
bookworm | 0.7.0-4 | all |
trixie | 0.10.0-1 | all |
upstream | 0.11.0 |
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License: DFSG free
|
Download conda metadata from packages without transferring entire file.
Get metadata from local .tar.bz2 packages without reading entire files.
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python3-ctdopts
Gives your Python tools a CTD-compatible interface
|
Versions of package python3-ctdopts |
Release | Version | Architectures |
bullseye | 1.4-2 | all |
bookworm | 1.5-2 | all |
sid | 1.5-5 | all |
buster | 1.2-3 | all |
trixie | 1.5-5 | all |
stretch-backports | 1.2-3~bpo9+1 | all |
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License: DFSG free
|
Common Tool Descriptors (CTDs) are XML documents that represent the inputs,
outputs, parameters of command line tools in a platform-independent way.
CTDopts is a module for enabling tools with CTD reading/writing, argument
parsing, validating and manipulating capabilities.
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python3-intake
lightweight package for finding and investigating data
|
Versions of package python3-intake |
Release | Version | Architectures |
sid | 0.6.6-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 0.6.6-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
upstream | 2.0.7 |
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License: DFSG free
|
Intake is a lightweight set of tools for loading and sharing data in
data science projects. Intake helps you:
1. Load data from a variety of formats into containers you already know,
like Pandas dataframes, Python lists, NumPy arrays and more.
2. Convert boilerplate data loading code into reusable intake plugins.
3. Describe data sets in catalog files for easy reuse and sharing
between projects and with others.
4. Share catalog information (and data sets) over the network with the
Intake server.
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python3-joypy
ridgeline-/joyplots plotting routine
|
Versions of package python3-joypy |
Release | Version | Architectures |
bullseye | 0.2.2-2 | all |
trixie | 0.2.6-1 | all |
sid | 0.2.6-1 | all |
bookworm | 0.2.6-1 | all |
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License: DFSG free
|
JoyPy is a one-function Python package based on matplotlib + pandas
with a single purpose: drawing joyplots (a.k.a. ridgeline plots).
Joyplots are stacked, partially overlapping density plots.
They are a nice way to plot data to visually compare distributions,
especially those that change across one dimension (e.g., over time).
Though hardly a new technique, they have become very popular lately
thanks to the R packages ggridges and ggjoy.
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python3-ncls
datastructure for interval overlap queries
|
Versions of package python3-ncls |
Release | Version | Architectures |
bookworm | 0.0.63-hotfix+ds-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 0.0.57+ds-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 0.0.63-hotfix+ds-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 0.0.63-hotfix+ds-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
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License: DFSG free
|
The Nested Containment List is a datastructure for interval overlap
queries, like the interval tree. It is usually an order of magnitude
faster than the interval tree both for building and query lookups.
The implementation here is a revived version of the one used in the
now defunct PyGr library, which died of bitrot. It was now made less
memory-consuming and wrapper functions allow batch-querying
the NCLS for further speed gains.
This package was implemented to be the cornerstone of the PyRanges project,
but was made available to the Python community as a stand-alone library.
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python3-networkx
tool to create, manipulate and study complex networks (Python3)
|
Versions of package python3-networkx |
Release | Version | Architectures |
sid | 3.2.1-5 | all |
trixie | 3.2.1-5 | all |
buster | 2.2-1 | all |
stretch | 1.11-2 | all |
bullseye | 2.5+ds-2 | all |
bookworm | 2.8.8-1 | all |
jessie | 1.9+dfsg1-1 | all |
upstream | 3.4.2 |
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License: DFSG free
|
NetworkX is a Python-based package for the creation, manipulation, and
study of the structure, dynamics, and functions of complex networks.
The structure of a graph or network is encoded in the edges (connections,
links, ties, arcs, bonds) between nodes (vertices, sites, actors). If
unqualified, by graph it's meant a simple undirected graph, i.e. no
self-loops and no multiple edges are allowed. By a network it's usually
meant a graph with weights (fields, properties) on nodes and/or edges.
The potential audience for NetworkX includes: mathematicians, physicists,
biologists, computer scientists, social scientists.
This package contains the Python 3 version of NetworkX.
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python3-pycosat
Python bindings to picosat
|
Versions of package python3-pycosat |
Release | Version | Architectures |
bookworm | 0.6.4+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 0.6.6+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 0.6.6+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 0.6.3+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
|
License: DFSG free
|
PicoSAT is a popular SAT solver written by Armin Biere in pure C. This
package provides efficient Python bindings to picosat on the C level,
i.e. when importing pycosat, the picosat solver becomes part of the
Python process itself.
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python3-pyflow
??? missing short description for package python3-pyflow :-(
|
Versions of package python3-pyflow |
Release | Version | Architectures |
bookworm | 1.1.20-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 1.1.20-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
|
License: DFSG free
|
|
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q2-alignment
QIIME 2 plugin for generating and manipulating alignments
|
Versions of package q2-alignment |
Release | Version | Architectures |
sid | 2024.5.0-1 | all |
bookworm | 2022.11.1-2 | all |
bullseye | 2020.11.1-2 | all |
upstream | 2024.10.0 |
|
License: DFSG free
|
QIIME 2 is a powerful, extensible, and decentralized microbiome analysis
package with a focus on data and analysis transparency. QIIME 2 enables
researchers to start an analysis with raw DNA sequence data and finish with
publication-quality figures and statistical results.
Key features:
- Integrated and automatic tracking of data provenance
- Semantic type system
- Plugin system for extending microbiome analysis functionality
- Support for multiple types of user interfaces (e.g. API, command line,
graphical)
QIIME 2 is a complete redesign and rewrite of the QIIME 1 microbiome analysis
pipeline. QIIME 2 will address many of the limitations of QIIME 1, while
retaining the features that makes QIIME 1 a powerful and widely-used analysis
pipeline.
QIIME 2 currently supports an initial end-to-end microbiome analysis pipeline.
New functionality will regularly become available through QIIME 2 plugins. You
can view a list of plugins that are currently available on the QIIME 2 plugin
availability page. The future plugins page lists plugins that are being
developed.
Please cite:
Evan Bolyen, Jai Ram Rideout, Matthew R Dillon, Nicholas A Bokulich, Christian Abnet, Gabriel A Al-Ghalith, Harriet Alexander, Eric J Alm, Manimozhiyan Arumugam, Francesco Asnicar, Yang Bai, Jordan E Bisanz, Kyle Bittinger, Asker Brejnrod, Colin J Brislawn, C Titus Brown, Benjamin J Callahan, Andrés Mauricio Caraballo-Rodríguez, John Chase, Emily Cope, Ricardo Da Silva, Pieter C Dorrestein, Gavin M Douglas, Daniel M Durall, Claire Duvallet, Christian F Edwardson, Madeleine Ernst, Mehrbod Estaki, Jennifer Fouquier, Julia M Gauglitz, Deanna L Gibson, Antonio Gonzalez, Kestrel Gorlick, Jiarong Guo, Benjamin Hillmann, Susan Holmes, Hannes Holste, Curtis Huttenhower, Gavin Huttley, Stefan Janssen, Alan K Jarmusch, Lingjing Jiang, Benjamin Kaehler, Kyo Bin Kang, Christopher R Keefe, Paul Keim, Scott T Kelley, Dan Knights, Irina Koester, Tomasz Kosciolek, Jorden Kreps, Morgan GI Langille, Joslynn Lee, Ruth Ley, Yong-Xin Liu, Erikka Loftfield, Catherine Lozupone, Massoud Maher, Clarisse Marotz, Bryan D Martin, Daniel McDonald, Lauren J McIver, Alexey V Melnik, Jessica L Metcalf, Sydney C Morgan, Jamie Morton, Ahmad Turan Naimey, Jose A Navas-Molina, Louis Felix Nothias, Stephanie B Orchanian, Talima Pearson, Samuel L Peoples, Daniel Petras, Mary Lai Preuss, Elmar Pruesse, Lasse Buur Rasmussen, Adam Rivers, Michael S Robeson, Patrick Rosenthal, Nicola Segata, Michael Shaffer, Arron Shiffer, Rashmi Sinha, Se Jin Song, John R Spear, Austin D Swafford, Luke R Thompson, Pedro J Torres, Pauline Trinh, Anupriya Tripathi, Peter J Turnbaugh, Sabah Ul-Hasan, Justin JJ van der Hooft, Fernando Vargas, Yoshiki Vázquez-Baeza, Emily Vogtmann, Max von Hippel, William Walters, Yunhu Wan, Mingxun Wang, Jonathan Warren, Kyle C Weber, Chase HD Williamson, Amy D Willis, Zhenjiang Zech Xu, Jesse R Zaneveld, Yilong Zhang, Qiyun Zhu, Rob Knight and J Gregory Caporaso:
Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2.
(eprint)
Nature Biotechnology
37
(2019)
|
|
q2-cutadapt
QIIME 2 plugin to work with adapters in sequence data
|
Versions of package q2-cutadapt |
Release | Version | Architectures |
sid | 2024.5.0-1 | amd64,arm64,mips64el,ppc64el,riscv64 |
bookworm | 2022.11.1-2 | amd64,arm64,mips64el,ppc64el |
bullseye | 2020.11.1-1 | amd64,arm64,mips64el,ppc64el |
upstream | 2024.10.0 |
|
License: DFSG free
|
QIIME 2 is a powerful, extensible, and decentralized microbiome analysis
package with a focus on data and analysis transparency. QIIME 2 enables
researchers to start an analysis with raw DNA sequence data and finish with
publication-quality figures and statistical results.
Key features:
- Integrated and automatic tracking of data provenance
- Semantic type system
- Plugin system for extending microbiome analysis functionality
- Support for multiple types of user interfaces (e.g. API, command line,
graphical)
QIIME 2 is a complete redesign and rewrite of the QIIME 1 microbiome analysis
pipeline. QIIME 2 will address many of the limitations of QIIME 1, while
retaining the features that makes QIIME 1 a powerful and widely-used analysis
pipeline.
QIIME 2 currently supports an initial end-to-end microbiome analysis pipeline.
New functionality will regularly become available through QIIME 2 plugins. You
can view a list of plugins that are currently available on the QIIME 2 plugin
availability page. The future plugins page lists plugins that are being
developed.
Please cite:
Evan Bolyen, Jai Ram Rideout, Matthew R Dillon, Nicholas A Bokulich, Christian Abnet, Gabriel A Al-Ghalith, Harriet Alexander, Eric J Alm, Manimozhiyan Arumugam, Francesco Asnicar, Yang Bai, Jordan E Bisanz, Kyle Bittinger, Asker Brejnrod, Colin J Brislawn, C Titus Brown, Benjamin J Callahan, Andrés Mauricio Caraballo-Rodríguez, John Chase, Emily Cope, Ricardo Da Silva, Pieter C Dorrestein, Gavin M Douglas, Daniel M Durall, Claire Duvallet, Christian F Edwardson, Madeleine Ernst, Mehrbod Estaki, Jennifer Fouquier, Julia M Gauglitz, Deanna L Gibson, Antonio Gonzalez, Kestrel Gorlick, Jiarong Guo, Benjamin Hillmann, Susan Holmes, Hannes Holste, Curtis Huttenhower, Gavin Huttley, Stefan Janssen, Alan K Jarmusch, Lingjing Jiang, Benjamin Kaehler, Kyo Bin Kang, Christopher R Keefe, Paul Keim, Scott T Kelley, Dan Knights, Irina Koester, Tomasz Kosciolek, Jorden Kreps, Morgan GI Langille, Joslynn Lee, Ruth Ley, Yong-Xin Liu, Erikka Loftfield, Catherine Lozupone, Massoud Maher, Clarisse Marotz, Bryan D Martin, Daniel McDonald, Lauren J McIver, Alexey V Melnik, Jessica L Metcalf, Sydney C Morgan, Jamie Morton, Ahmad Turan Naimey, Jose A Navas-Molina, Louis Felix Nothias, Stephanie B Orchanian, Talima Pearson, Samuel L Peoples, Daniel Petras, Mary Lai Preuss, Elmar Pruesse, Lasse Buur Rasmussen, Adam Rivers, Michael S Robeson, Patrick Rosenthal, Nicola Segata, Michael Shaffer, Arron Shiffer, Rashmi Sinha, Se Jin Song, John R Spear, Austin D Swafford, Luke R Thompson, Pedro J Torres, Pauline Trinh, Anupriya Tripathi, Peter J Turnbaugh, Sabah Ul-Hasan, Justin JJ van der Hooft, Fernando Vargas, Yoshiki Vázquez-Baeza, Emily Vogtmann, Max von Hippel, William Walters, Yunhu Wan, Mingxun Wang, Jonathan Warren, Kyle C Weber, Chase HD Williamson, Amy D Willis, Zhenjiang Zech Xu, Jesse R Zaneveld, Yilong Zhang, Qiyun Zhu, Rob Knight and J Gregory Caporaso:
Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2.
(eprint)
Nature Biotechnology
37
(2019)
|
|
q2-dada2
QIIME 2 plugin to work with adapters in sequence data
|
Versions of package q2-dada2 |
Release | Version | Architectures |
bullseye | 2020.11.1-3 | amd64 |
bookworm | 2022.11.2-2 | amd64 |
sid | 2024.5.0-1 | amd64 |
upstream | 2024.10.0 |
|
License: DFSG free
|
QIIME 2 is a powerful, extensible, and decentralized microbiome analysis
package with a focus on data and analysis transparency. QIIME 2 enables
researchers to start an analysis with raw DNA sequence data and finish with
publication-quality figures and statistical results.
Key features:
- Integrated and automatic tracking of data provenance
- Semantic type system
- Plugin system for extending microbiome analysis functionality
- Support for multiple types of user interfaces (e.g. API, command line,
graphical)
QIIME 2 is a complete redesign and rewrite of the QIIME 1 microbiome analysis
pipeline. QIIME 2 will address many of the limitations of QIIME 1, while
retaining the features that makes QIIME 1 a powerful and widely-used analysis
pipeline.
QIIME 2 currently supports an initial end-to-end microbiome analysis pipeline.
New functionality will regularly become available through QIIME 2 plugins. You
can view a list of plugins that are currently available on the QIIME 2 plugin
availability page. The future plugins page lists plugins that are being
developed.
This package wraps the dada2 R package in BioConductor for modeling and
correcting Illumina-sequenced amplicon errors. This was shown to improve the
sensitivity of diversity analyses.
Please cite:
Evan Bolyen, Jai Ram Rideout, Matthew R Dillon, Nicholas A Bokulich, Christian Abnet, Gabriel A Al-Ghalith, Harriet Alexander, Eric J Alm, Manimozhiyan Arumugam, Francesco Asnicar, Yang Bai, Jordan E Bisanz, Kyle Bittinger, Asker Brejnrod, Colin J Brislawn, C Titus Brown, Benjamin J Callahan, Andrés Mauricio Caraballo-Rodríguez, John Chase, Emily Cope, Ricardo Da Silva, Pieter C Dorrestein, Gavin M Douglas, Daniel M Durall, Claire Duvallet, Christian F Edwardson, Madeleine Ernst, Mehrbod Estaki, Jennifer Fouquier, Julia M Gauglitz, Deanna L Gibson, Antonio Gonzalez, Kestrel Gorlick, Jiarong Guo, Benjamin Hillmann, Susan Holmes, Hannes Holste, Curtis Huttenhower, Gavin Huttley, Stefan Janssen, Alan K Jarmusch, Lingjing Jiang, Benjamin Kaehler, Kyo Bin Kang, Christopher R Keefe, Paul Keim, Scott T Kelley, Dan Knights, Irina Koester, Tomasz Kosciolek, Jorden Kreps, Morgan GI Langille, Joslynn Lee, Ruth Ley, Yong-Xin Liu, Erikka Loftfield, Catherine Lozupone, Massoud Maher, Clarisse Marotz, Bryan D Martin, Daniel McDonald, Lauren J McIver, Alexey V Melnik, Jessica L Metcalf, Sydney C Morgan, Jamie Morton, Ahmad Turan Naimey, Jose A Navas-Molina, Louis Felix Nothias, Stephanie B Orchanian, Talima Pearson, Samuel L Peoples, Daniel Petras, Mary Lai Preuss, Elmar Pruesse, Lasse Buur Rasmussen, Adam Rivers, Michael S Robeson, Patrick Rosenthal, Nicola Segata, Michael Shaffer, Arron Shiffer, Rashmi Sinha, Se Jin Song, John R Spear, Austin D Swafford, Luke R Thompson, Pedro J Torres, Pauline Trinh, Anupriya Tripathi, Peter J Turnbaugh, Sabah Ul-Hasan, Justin JJ van der Hooft, Fernando Vargas, Yoshiki Vázquez-Baeza, Emily Vogtmann, Max von Hippel, William Walters, Yunhu Wan, Mingxun Wang, Jonathan Warren, Kyle C Weber, Chase HD Williamson, Amy D Willis, Zhenjiang Zech Xu, Jesse R Zaneveld, Yilong Zhang, Qiyun Zhu, Rob Knight and J Gregory Caporaso:
Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2.
(eprint)
Nature Biotechnology
37
(2019)
|
|
q2-demux
QIIME 2 plugin for demultiplexing of sequence reads
|
Versions of package q2-demux |
Release | Version | Architectures |
sid | 2024.5.0+dfsg-1 | all |
bullseye | 2020.11.1-1 | all |
bookworm | 2022.11.1+dfsg-2 | all |
upstream | 2024.10.0 |
|
License: DFSG free
|
QIIME 2 is a powerful, extensible, and decentralized microbiome analysis
package with a focus on data and analysis transparency. QIIME 2 enables
researchers to start an analysis with raw DNA sequence data and finish with
publication-quality figures and statistical results.
Key features:
- Integrated and automatic tracking of data provenance
- Semantic type system
- Plugin system for extending microbiome analysis functionality
- Support for multiple types of user interfaces (e.g. API, command line,
graphical)
QIIME 2 is a complete redesign and rewrite of the QIIME 1 microbiome analysis
pipeline. QIIME 2 will address many of the limitations of QIIME 1, while
retaining the features that makes QIIME 1 a powerful and widely-used analysis
pipeline.
QIIME 2 currently supports an initial end-to-end microbiome analysis pipeline.
New functionality will regularly become available through QIIME 2 plugins. You
can view a list of plugins that are currently available on the QIIME 2 plugin
availability page. The future plugins page lists plugins that are being
developed.
Please cite:
Evan Bolyen, Jai Ram Rideout, Matthew R Dillon, Nicholas A Bokulich, Christian Abnet, Gabriel A Al-Ghalith, Harriet Alexander, Eric J Alm, Manimozhiyan Arumugam, Francesco Asnicar, Yang Bai, Jordan E Bisanz, Kyle Bittinger, Asker Brejnrod, Colin J Brislawn, C Titus Brown, Benjamin J Callahan, Andrés Mauricio Caraballo-Rodríguez, John Chase, Emily Cope, Ricardo Da Silva, Pieter C Dorrestein, Gavin M Douglas, Daniel M Durall, Claire Duvallet, Christian F Edwardson, Madeleine Ernst, Mehrbod Estaki, Jennifer Fouquier, Julia M Gauglitz, Deanna L Gibson, Antonio Gonzalez, Kestrel Gorlick, Jiarong Guo, Benjamin Hillmann, Susan Holmes, Hannes Holste, Curtis Huttenhower, Gavin Huttley, Stefan Janssen, Alan K Jarmusch, Lingjing Jiang, Benjamin Kaehler, Kyo Bin Kang, Christopher R Keefe, Paul Keim, Scott T Kelley, Dan Knights, Irina Koester, Tomasz Kosciolek, Jorden Kreps, Morgan GI Langille, Joslynn Lee, Ruth Ley, Yong-Xin Liu, Erikka Loftfield, Catherine Lozupone, Massoud Maher, Clarisse Marotz, Bryan D Martin, Daniel McDonald, Lauren J McIver, Alexey V Melnik, Jessica L Metcalf, Sydney C Morgan, Jamie Morton, Ahmad Turan Naimey, Jose A Navas-Molina, Louis Felix Nothias, Stephanie B Orchanian, Talima Pearson, Samuel L Peoples, Daniel Petras, Mary Lai Preuss, Elmar Pruesse, Lasse Buur Rasmussen, Adam Rivers, Michael S Robeson, Patrick Rosenthal, Nicola Segata, Michael Shaffer, Arron Shiffer, Rashmi Sinha, Se Jin Song, John R Spear, Austin D Swafford, Luke R Thompson, Pedro J Torres, Pauline Trinh, Anupriya Tripathi, Peter J Turnbaugh, Sabah Ul-Hasan, Justin JJ van der Hooft, Fernando Vargas, Yoshiki Vázquez-Baeza, Emily Vogtmann, Max von Hippel, William Walters, Yunhu Wan, Mingxun Wang, Jonathan Warren, Kyle C Weber, Chase HD Williamson, Amy D Willis, Zhenjiang Zech Xu, Jesse R Zaneveld, Yilong Zhang, Qiyun Zhu, Rob Knight and J Gregory Caporaso:
Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2.
(eprint)
Nature Biotechnology
37
(2019)
|
|
q2-emperor
QIIME2 plugin for display of ordination plots
|
Versions of package q2-emperor |
Release | Version | Architectures |
bookworm | 2022.11.1-2 | all |
sid | 2024.5.0-2 | all |
upstream | 2024.10.0 |
|
License: DFSG free
|
QIIME 2 is a powerful, extensible, and decentralized microbiome analysis
package with a focus on data and analysis transparency. QIIME 2 enables
researchers to start an analysis with raw DNA sequence data and finish with
publication-quality figures and statistical results.
Key features:
- Integrated and automatic tracking of data provenance
- Semantic type system
- Plugin system for extending microbiome analysis functionality
- Support for multiple types of user interfaces (e.g. API, command line,
graphical)
QIIME 2 is a complete redesign and rewrite of the QIIME 1 microbiome analysis
pipeline. QIIME 2 will address many of the limitations of QIIME 1, while
retaining the features that makes QIIME 1 a powerful and widely-used analysis
pipeline.
QIIME 2 currently supports an initial end-to-end microbiome analysis pipeline.
New functionality will regularly become available through QIIME 2 plugins. You
can view a list of plugins that are currently available on the QIIME 2 plugin
availability page. The future plugins page lists plugins that are being
developed.
Please cite:
Evan Bolyen, Jai Ram Rideout, Matthew R Dillon, Nicholas A Bokulich, Christian Abnet, Gabriel A Al-Ghalith, Harriet Alexander, Eric J Alm, Manimozhiyan Arumugam, Francesco Asnicar, Yang Bai, Jordan E Bisanz, Kyle Bittinger, Asker Brejnrod, Colin J Brislawn, C Titus Brown, Benjamin J Callahan, Andrés Mauricio Caraballo-Rodríguez, John Chase, Emily Cope, Ricardo Da Silva, Pieter C Dorrestein, Gavin M Douglas, Daniel M Durall, Claire Duvallet, Christian F Edwardson, Madeleine Ernst, Mehrbod Estaki, Jennifer Fouquier, Julia M Gauglitz, Deanna L Gibson, Antonio Gonzalez, Kestrel Gorlick, Jiarong Guo, Benjamin Hillmann, Susan Holmes, Hannes Holste, Curtis Huttenhower, Gavin Huttley, Stefan Janssen, Alan K Jarmusch, Lingjing Jiang, Benjamin Kaehler, Kyo Bin Kang, Christopher R Keefe, Paul Keim, Scott T Kelley, Dan Knights, Irina Koester, Tomasz Kosciolek, Jorden Kreps, Morgan GI Langille, Joslynn Lee, Ruth Ley, Yong-Xin Liu, Erikka Loftfield, Catherine Lozupone, Massoud Maher, Clarisse Marotz, Bryan D Martin, Daniel McDonald, Lauren J McIver, Alexey V Melnik, Jessica L Metcalf, Sydney C Morgan, Jamie Morton, Ahmad Turan Naimey, Jose A Navas-Molina, Louis Felix Nothias, Stephanie B Orchanian, Talima Pearson, Samuel L Peoples, Daniel Petras, Mary Lai Preuss, Elmar Pruesse, Lasse Buur Rasmussen, Adam Rivers, Michael S Robeson, Patrick Rosenthal, Nicola Segata, Michael Shaffer, Arron Shiffer, Rashmi Sinha, Se Jin Song, John R Spear, Austin D Swafford, Luke R Thompson, Pedro J Torres, Pauline Trinh, Anupriya Tripathi, Peter J Turnbaugh, Sabah Ul-Hasan, Justin JJ van der Hooft, Fernando Vargas, Yoshiki Vázquez-Baeza, Emily Vogtmann, Max von Hippel, William Walters, Yunhu Wan, Mingxun Wang, Jonathan Warren, Kyle C Weber, Chase HD Williamson, Amy D Willis, Zhenjiang Zech Xu, Jesse R Zaneveld, Yilong Zhang, Qiyun Zhu, Rob Knight and J Gregory Caporaso:
Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2.
(eprint)
Nature Biotechnology
37
(2019)
|
|
q2-feature-classifier
QIIME 2 plugin supporting taxonomic classification
|
Versions of package q2-feature-classifier |
Release | Version | Architectures |
bullseye | 2020.11.1-2 | all |
bookworm | 2022.11.1-2 | all |
sid | 2024.2.0-1 | all |
upstream | 2024.10.0 |
|
License: DFSG free
|
QIIME 2 is a powerful, extensible, and decentralized microbiome analysis
package with a focus on data and analysis transparency. QIIME 2 enables
researchers to start an analysis with raw DNA sequence data and finish with
publication-quality figures and statistical results.
Key features:
- Integrated and automatic tracking of data provenance
- Semantic type system
- Plugin system for extending microbiome analysis functionality
- Support for multiple types of user interfaces (e.g. API, command line,
graphical)
QIIME 2 is a complete redesign and rewrite of the QIIME 1 microbiome analysis
pipeline. QIIME 2 will address many of the limitations of QIIME 1, while
retaining the features that makes QIIME 1 a powerful and widely-used analysis
pipeline.
QIIME 2 currently supports an initial end-to-end microbiome analysis pipeline.
New functionality will regularly become available through QIIME 2 plugins. You
can view a list of plugins that are currently available on the QIIME 2 plugin
availability page. The future plugins page lists plugins that are being
developed.
Please cite:
Evan Bolyen, Jai Ram Rideout, Matthew R Dillon, Nicholas A Bokulich, Christian Abnet, Gabriel A Al-Ghalith, Harriet Alexander, Eric J Alm, Manimozhiyan Arumugam, Francesco Asnicar, Yang Bai, Jordan E Bisanz, Kyle Bittinger, Asker Brejnrod, Colin J Brislawn, C Titus Brown, Benjamin J Callahan, Andrés Mauricio Caraballo-Rodríguez, John Chase, Emily Cope, Ricardo Da Silva, Pieter C Dorrestein, Gavin M Douglas, Daniel M Durall, Claire Duvallet, Christian F Edwardson, Madeleine Ernst, Mehrbod Estaki, Jennifer Fouquier, Julia M Gauglitz, Deanna L Gibson, Antonio Gonzalez, Kestrel Gorlick, Jiarong Guo, Benjamin Hillmann, Susan Holmes, Hannes Holste, Curtis Huttenhower, Gavin Huttley, Stefan Janssen, Alan K Jarmusch, Lingjing Jiang, Benjamin Kaehler, Kyo Bin Kang, Christopher R Keefe, Paul Keim, Scott T Kelley, Dan Knights, Irina Koester, Tomasz Kosciolek, Jorden Kreps, Morgan GI Langille, Joslynn Lee, Ruth Ley, Yong-Xin Liu, Erikka Loftfield, Catherine Lozupone, Massoud Maher, Clarisse Marotz, Bryan D Martin, Daniel McDonald, Lauren J McIver, Alexey V Melnik, Jessica L Metcalf, Sydney C Morgan, Jamie Morton, Ahmad Turan Naimey, Jose A Navas-Molina, Louis Felix Nothias, Stephanie B Orchanian, Talima Pearson, Samuel L Peoples, Daniel Petras, Mary Lai Preuss, Elmar Pruesse, Lasse Buur Rasmussen, Adam Rivers, Michael S Robeson, Patrick Rosenthal, Nicola Segata, Michael Shaffer, Arron Shiffer, Rashmi Sinha, Se Jin Song, John R Spear, Austin D Swafford, Luke R Thompson, Pedro J Torres, Pauline Trinh, Anupriya Tripathi, Peter J Turnbaugh, Sabah Ul-Hasan, Justin JJ van der Hooft, Fernando Vargas, Yoshiki Vázquez-Baeza, Emily Vogtmann, Max von Hippel, William Walters, Yunhu Wan, Mingxun Wang, Jonathan Warren, Kyle C Weber, Chase HD Williamson, Amy D Willis, Zhenjiang Zech Xu, Jesse R Zaneveld, Yilong Zhang, Qiyun Zhu, Rob Knight and J Gregory Caporaso:
Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2.
(eprint)
Nature Biotechnology
37
(2019)
|
|
q2-feature-table
QIIME 2 plugin supporting operations on feature tables
|
Versions of package q2-feature-table |
Release | Version | Architectures |
bookworm | 2022.11.1+dfsg-2 | all |
bullseye | 2020.11.1+dfsg-1 | all |
sid | 2024.5.0+dfsg-1 | all |
upstream | 2024.10.0 |
|
License: DFSG free
|
QIIME 2 is a powerful, extensible, and decentralized microbiome analysis
package with a focus on data and analysis transparency. QIIME 2 enables
researchers to start an analysis with raw DNA sequence data and finish with
publication-quality figures and statistical results.
Key features:
- Integrated and automatic tracking of data provenance
- Semantic type system
- Plugin system for extending microbiome analysis functionality
- Support for multiple types of user interfaces (e.g. API, command line,
graphical)
QIIME 2 is a complete redesign and rewrite of the QIIME 1 microbiome analysis
pipeline. QIIME 2 will address many of the limitations of QIIME 1, while
retaining the features that makes QIIME 1 a powerful and widely-used analysis
pipeline.
QIIME 2 currently supports an initial end-to-end microbiome analysis pipeline.
New functionality will regularly become available through QIIME 2 plugins. You
can view a list of plugins that are currently available on the QIIME 2 plugin
availability page. The future plugins page lists plugins that are being
developed.
Please cite:
Evan Bolyen, Jai Ram Rideout, Matthew R Dillon, Nicholas A Bokulich, Christian Abnet, Gabriel A Al-Ghalith, Harriet Alexander, Eric J Alm, Manimozhiyan Arumugam, Francesco Asnicar, Yang Bai, Jordan E Bisanz, Kyle Bittinger, Asker Brejnrod, Colin J Brislawn, C Titus Brown, Benjamin J Callahan, Andrés Mauricio Caraballo-Rodríguez, John Chase, Emily Cope, Ricardo Da Silva, Pieter C Dorrestein, Gavin M Douglas, Daniel M Durall, Claire Duvallet, Christian F Edwardson, Madeleine Ernst, Mehrbod Estaki, Jennifer Fouquier, Julia M Gauglitz, Deanna L Gibson, Antonio Gonzalez, Kestrel Gorlick, Jiarong Guo, Benjamin Hillmann, Susan Holmes, Hannes Holste, Curtis Huttenhower, Gavin Huttley, Stefan Janssen, Alan K Jarmusch, Lingjing Jiang, Benjamin Kaehler, Kyo Bin Kang, Christopher R Keefe, Paul Keim, Scott T Kelley, Dan Knights, Irina Koester, Tomasz Kosciolek, Jorden Kreps, Morgan GI Langille, Joslynn Lee, Ruth Ley, Yong-Xin Liu, Erikka Loftfield, Catherine Lozupone, Massoud Maher, Clarisse Marotz, Bryan D Martin, Daniel McDonald, Lauren J McIver, Alexey V Melnik, Jessica L Metcalf, Sydney C Morgan, Jamie Morton, Ahmad Turan Naimey, Jose A Navas-Molina, Louis Felix Nothias, Stephanie B Orchanian, Talima Pearson, Samuel L Peoples, Daniel Petras, Mary Lai Preuss, Elmar Pruesse, Lasse Buur Rasmussen, Adam Rivers, Michael S Robeson, Patrick Rosenthal, Nicola Segata, Michael Shaffer, Arron Shiffer, Rashmi Sinha, Se Jin Song, John R Spear, Austin D Swafford, Luke R Thompson, Pedro J Torres, Pauline Trinh, Anupriya Tripathi, Peter J Turnbaugh, Sabah Ul-Hasan, Justin JJ van der Hooft, Fernando Vargas, Yoshiki Vázquez-Baeza, Emily Vogtmann, Max von Hippel, William Walters, Yunhu Wan, Mingxun Wang, Jonathan Warren, Kyle C Weber, Chase HD Williamson, Amy D Willis, Zhenjiang Zech Xu, Jesse R Zaneveld, Yilong Zhang, Qiyun Zhu, Rob Knight and J Gregory Caporaso:
Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2.
(eprint)
Nature Biotechnology
37
(2019)
|
|
q2-fragment-insertion
QIIME 2 plugin for fragment insertion
|
Versions of package q2-fragment-insertion |
Release | Version | Architectures |
bookworm | 2022.11.1-3 | amd64,arm64,mips64el,ppc64el |
sid | 2024.5.0-1 | amd64,arm64,mips64el,ppc64el,riscv64 |
upstream | 2024.10.0 |
|
License: DFSG free
|
QIIME 2 is a powerful, extensible, and decentralized microbiome analysis
package with a focus on data and analysis transparency. QIIME 2 enables
researchers to start an analysis with raw DNA sequence data and finish with
publication-quality figures and statistical results.
Key features:
- Integrated and automatic tracking of data provenance
- Semantic type system
- Plugin system for extending microbiome analysis functionality
- Support for multiple types of user interfaces (e.g. API, command line,
graphical)
QIIME 2 is a complete redesign and rewrite of the QIIME 1 microbiome analysis
pipeline. QIIME 2 will address many of the limitations of QIIME 1, while
retaining the features that makes QIIME 1 a powerful and widely-used analysis
pipeline.
QIIME 2 currently supports an initial end-to-end microbiome analysis pipeline.
New functionality will regularly become available through QIIME 2 plugins. You
can view a list of plugins that are currently available on the QIIME 2 plugin
availability page. The future plugins page lists plugins that are being
developed.
Please cite:
Evan Bolyen, Jai Ram Rideout, Matthew R Dillon, Nicholas A Bokulich, Christian Abnet, Gabriel A Al-Ghalith, Harriet Alexander, Eric J Alm, Manimozhiyan Arumugam, Francesco Asnicar, Yang Bai, Jordan E Bisanz, Kyle Bittinger, Asker Brejnrod, Colin J Brislawn, C Titus Brown, Benjamin J Callahan, Andrés Mauricio Caraballo-Rodríguez, John Chase, Emily Cope, Ricardo Da Silva, Pieter C Dorrestein, Gavin M Douglas, Daniel M Durall, Claire Duvallet, Christian F Edwardson, Madeleine Ernst, Mehrbod Estaki, Jennifer Fouquier, Julia M Gauglitz, Deanna L Gibson, Antonio Gonzalez, Kestrel Gorlick, Jiarong Guo, Benjamin Hillmann, Susan Holmes, Hannes Holste, Curtis Huttenhower, Gavin Huttley, Stefan Janssen, Alan K Jarmusch, Lingjing Jiang, Benjamin Kaehler, Kyo Bin Kang, Christopher R Keefe, Paul Keim, Scott T Kelley, Dan Knights, Irina Koester, Tomasz Kosciolek, Jorden Kreps, Morgan GI Langille, Joslynn Lee, Ruth Ley, Yong-Xin Liu, Erikka Loftfield, Catherine Lozupone, Massoud Maher, Clarisse Marotz, Bryan D Martin, Daniel McDonald, Lauren J McIver, Alexey V Melnik, Jessica L Metcalf, Sydney C Morgan, Jamie Morton, Ahmad Turan Naimey, Jose A Navas-Molina, Louis Felix Nothias, Stephanie B Orchanian, Talima Pearson, Samuel L Peoples, Daniel Petras, Mary Lai Preuss, Elmar Pruesse, Lasse Buur Rasmussen, Adam Rivers, Michael S Robeson, Patrick Rosenthal, Nicola Segata, Michael Shaffer, Arron Shiffer, Rashmi Sinha, Se Jin Song, John R Spear, Austin D Swafford, Luke R Thompson, Pedro J Torres, Pauline Trinh, Anupriya Tripathi, Peter J Turnbaugh, Sabah Ul-Hasan, Justin JJ van der Hooft, Fernando Vargas, Yoshiki Vázquez-Baeza, Emily Vogtmann, Max von Hippel, William Walters, Yunhu Wan, Mingxun Wang, Jonathan Warren, Kyle C Weber, Chase HD Williamson, Amy D Willis, Zhenjiang Zech Xu, Jesse R Zaneveld, Yilong Zhang, Qiyun Zhu, Rob Knight and J Gregory Caporaso:
Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2.
(eprint)
Nature Biotechnology
37
(2019)
|
|
q2-metadata
QIIME 2 plugin for working with and visualizing Metadata
|
Versions of package q2-metadata |
Release | Version | Architectures |
sid | 2024.5.0+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64 |
bookworm | 2022.8.0-1 | amd64,arm64,mips64el,ppc64el |
bullseye | 2020.11.1+dfsg-1 | amd64,arm64,mips64el,ppc64el |
upstream | 2024.10.0 |
|
License: DFSG free
|
QIIME 2 is a powerful, extensible, and decentralized microbiome analysis
package with a focus on data and analysis transparency. QIIME 2 enables
researchers to start an analysis with raw DNA sequence data and finish with
publication-quality figures and statistical results.
Key features:
- Integrated and automatic tracking of data provenance
- Semantic type system
- Plugin system for extending microbiome analysis functionality
- Support for multiple types of user interfaces (e.g. API, command line,
graphical)
QIIME 2 is a complete redesign and rewrite of the QIIME 1 microbiome analysis
pipeline. QIIME 2 will address many of the limitations of QIIME 1, while
retaining the features that makes QIIME 1 a powerful and widely-used analysis
pipeline.
QIIME 2 currently supports an initial end-to-end microbiome analysis pipeline.
New functionality will regularly become available through QIIME 2 plugins. You
can view a list of plugins that are currently available on the QIIME 2 plugin
availability page. The future plugins page lists plugins that are being
developed.
Please cite:
Evan Bolyen, Jai Ram Rideout, Matthew R Dillon, Nicholas A Bokulich, Christian Abnet, Gabriel A Al-Ghalith, Harriet Alexander, Eric J Alm, Manimozhiyan Arumugam, Francesco Asnicar, Yang Bai, Jordan E Bisanz, Kyle Bittinger, Asker Brejnrod, Colin J Brislawn, C Titus Brown, Benjamin J Callahan, Andrés Mauricio Caraballo-Rodríguez, John Chase, Emily Cope, Ricardo Da Silva, Pieter C Dorrestein, Gavin M Douglas, Daniel M Durall, Claire Duvallet, Christian F Edwardson, Madeleine Ernst, Mehrbod Estaki, Jennifer Fouquier, Julia M Gauglitz, Deanna L Gibson, Antonio Gonzalez, Kestrel Gorlick, Jiarong Guo, Benjamin Hillmann, Susan Holmes, Hannes Holste, Curtis Huttenhower, Gavin Huttley, Stefan Janssen, Alan K Jarmusch, Lingjing Jiang, Benjamin Kaehler, Kyo Bin Kang, Christopher R Keefe, Paul Keim, Scott T Kelley, Dan Knights, Irina Koester, Tomasz Kosciolek, Jorden Kreps, Morgan GI Langille, Joslynn Lee, Ruth Ley, Yong-Xin Liu, Erikka Loftfield, Catherine Lozupone, Massoud Maher, Clarisse Marotz, Bryan D Martin, Daniel McDonald, Lauren J McIver, Alexey V Melnik, Jessica L Metcalf, Sydney C Morgan, Jamie Morton, Ahmad Turan Naimey, Jose A Navas-Molina, Louis Felix Nothias, Stephanie B Orchanian, Talima Pearson, Samuel L Peoples, Daniel Petras, Mary Lai Preuss, Elmar Pruesse, Lasse Buur Rasmussen, Adam Rivers, Michael S Robeson, Patrick Rosenthal, Nicola Segata, Michael Shaffer, Arron Shiffer, Rashmi Sinha, Se Jin Song, John R Spear, Austin D Swafford, Luke R Thompson, Pedro J Torres, Pauline Trinh, Anupriya Tripathi, Peter J Turnbaugh, Sabah Ul-Hasan, Justin JJ van der Hooft, Fernando Vargas, Yoshiki Vázquez-Baeza, Emily Vogtmann, Max von Hippel, William Walters, Yunhu Wan, Mingxun Wang, Jonathan Warren, Kyle C Weber, Chase HD Williamson, Amy D Willis, Zhenjiang Zech Xu, Jesse R Zaneveld, Yilong Zhang, Qiyun Zhu, Rob Knight and J Gregory Caporaso:
Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2.
(eprint)
Nature Biotechnology
37
(2019)
|
|
q2-phylogeny
QIIME 2 plugin for phylogeny
|
Versions of package q2-phylogeny |
Release | Version | Architectures |
bookworm | 2022.11.1-3 | amd64 |
sid | 2024.5.0-1 | amd64 |
experimental | 2022.11.1-1 | all |
upstream | 2024.10.0 |
|
License: DFSG free
|
QIIME 2 plugin for phylogenetic reconstruction, and operations on
phylogenetic trees.
|
|
q2-quality-control
QIIME 2 plugin for quality assurance of feature and sequence data
|
Versions of package q2-quality-control |
Release | Version | Architectures |
bookworm | 2022.11.1-2 | all |
bullseye | 2020.11.1-3 | all |
sid | 2024.5.0-1 | all |
upstream | 2024.10.0 |
|
License: DFSG free
|
QIIME 2 is a powerful, extensible, and decentralized microbiome analysis
package with a focus on data and analysis transparency. QIIME 2 enables
researchers to start an analysis with raw DNA sequence data and finish with
publication-quality figures and statistical results.
Key features:
- Integrated and automatic tracking of data provenance
- Semantic type system
- Plugin system for extending microbiome analysis functionality
- Support for multiple types of user interfaces (e.g. API, command line,
graphical)
QIIME 2 is a complete redesign and rewrite of the QIIME 1 microbiome analysis
pipeline. QIIME 2 will address many of the limitations of QIIME 1, while
retaining the features that makes QIIME 1 a powerful and widely-used analysis
pipeline.
QIIME 2 currently supports an initial end-to-end microbiome analysis pipeline.
New functionality will regularly become available through QIIME 2 plugins. You
can view a list of plugins that are currently available on the QIIME 2 plugin
availability page. The future plugins page lists plugins that are being
developed.
Please cite:
Evan Bolyen, Jai Ram Rideout, Matthew R Dillon, Nicholas A Bokulich, Christian Abnet, Gabriel A Al-Ghalith, Harriet Alexander, Eric J Alm, Manimozhiyan Arumugam, Francesco Asnicar, Yang Bai, Jordan E Bisanz, Kyle Bittinger, Asker Brejnrod, Colin J Brislawn, C Titus Brown, Benjamin J Callahan, Andrés Mauricio Caraballo-Rodríguez, John Chase, Emily Cope, Ricardo Da Silva, Pieter C Dorrestein, Gavin M Douglas, Daniel M Durall, Claire Duvallet, Christian F Edwardson, Madeleine Ernst, Mehrbod Estaki, Jennifer Fouquier, Julia M Gauglitz, Deanna L Gibson, Antonio Gonzalez, Kestrel Gorlick, Jiarong Guo, Benjamin Hillmann, Susan Holmes, Hannes Holste, Curtis Huttenhower, Gavin Huttley, Stefan Janssen, Alan K Jarmusch, Lingjing Jiang, Benjamin Kaehler, Kyo Bin Kang, Christopher R Keefe, Paul Keim, Scott T Kelley, Dan Knights, Irina Koester, Tomasz Kosciolek, Jorden Kreps, Morgan GI Langille, Joslynn Lee, Ruth Ley, Yong-Xin Liu, Erikka Loftfield, Catherine Lozupone, Massoud Maher, Clarisse Marotz, Bryan D Martin, Daniel McDonald, Lauren J McIver, Alexey V Melnik, Jessica L Metcalf, Sydney C Morgan, Jamie Morton, Ahmad Turan Naimey, Jose A Navas-Molina, Louis Felix Nothias, Stephanie B Orchanian, Talima Pearson, Samuel L Peoples, Daniel Petras, Mary Lai Preuss, Elmar Pruesse, Lasse Buur Rasmussen, Adam Rivers, Michael S Robeson, Patrick Rosenthal, Nicola Segata, Michael Shaffer, Arron Shiffer, Rashmi Sinha, Se Jin Song, John R Spear, Austin D Swafford, Luke R Thompson, Pedro J Torres, Pauline Trinh, Anupriya Tripathi, Peter J Turnbaugh, Sabah Ul-Hasan, Justin JJ van der Hooft, Fernando Vargas, Yoshiki Vázquez-Baeza, Emily Vogtmann, Max von Hippel, William Walters, Yunhu Wan, Mingxun Wang, Jonathan Warren, Kyle C Weber, Chase HD Williamson, Amy D Willis, Zhenjiang Zech Xu, Jesse R Zaneveld, Yilong Zhang, Qiyun Zhu, Rob Knight and J Gregory Caporaso:
Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2.
(eprint)
Nature Biotechnology
37
(2019)
|
|
q2-quality-filter
QIIME2 plugin for PHRED-based filtering and trimming
|
Versions of package q2-quality-filter |
Release | Version | Architectures |
bullseye | 2020.11.1-2 | all |
sid | 2024.5.0-1 | all |
bookworm | 2022.11.1-2 | all |
upstream | 2024.10.0 |
|
License: DFSG free
|
QIIME 2 is a powerful, extensible, and decentralized microbiome analysis
package with a focus on data and analysis transparency. QIIME 2 enables
researchers to start an analysis with raw DNA sequence data and finish with
publication-quality figures and statistical results.
Key features:
- Integrated and automatic tracking of data provenance
- Semantic type system
- Plugin system for extending microbiome analysis functionality
- Support for multiple types of user interfaces (e.g. API, command line,
graphical)
QIIME 2 is a complete redesign and rewrite of the QIIME 1 microbiome analysis
pipeline. QIIME 2 will address many of the limitations of QIIME 1, while
retaining the features that makes QIIME 1 a powerful and widely-used analysis
pipeline.
QIIME 2 currently supports an initial end-to-end microbiome analysis pipeline.
New functionality will regularly become available through QIIME 2 plugins. You
can view a list of plugins that are currently available on the QIIME 2 plugin
availability page. The future plugins page lists plugins that are being
developed.
Please cite:
Evan Bolyen, Jai Ram Rideout, Matthew R Dillon, Nicholas A Bokulich, Christian Abnet, Gabriel A Al-Ghalith, Harriet Alexander, Eric J Alm, Manimozhiyan Arumugam, Francesco Asnicar, Yang Bai, Jordan E Bisanz, Kyle Bittinger, Asker Brejnrod, Colin J Brislawn, C Titus Brown, Benjamin J Callahan, Andrés Mauricio Caraballo-Rodríguez, John Chase, Emily Cope, Ricardo Da Silva, Pieter C Dorrestein, Gavin M Douglas, Daniel M Durall, Claire Duvallet, Christian F Edwardson, Madeleine Ernst, Mehrbod Estaki, Jennifer Fouquier, Julia M Gauglitz, Deanna L Gibson, Antonio Gonzalez, Kestrel Gorlick, Jiarong Guo, Benjamin Hillmann, Susan Holmes, Hannes Holste, Curtis Huttenhower, Gavin Huttley, Stefan Janssen, Alan K Jarmusch, Lingjing Jiang, Benjamin Kaehler, Kyo Bin Kang, Christopher R Keefe, Paul Keim, Scott T Kelley, Dan Knights, Irina Koester, Tomasz Kosciolek, Jorden Kreps, Morgan GI Langille, Joslynn Lee, Ruth Ley, Yong-Xin Liu, Erikka Loftfield, Catherine Lozupone, Massoud Maher, Clarisse Marotz, Bryan D Martin, Daniel McDonald, Lauren J McIver, Alexey V Melnik, Jessica L Metcalf, Sydney C Morgan, Jamie Morton, Ahmad Turan Naimey, Jose A Navas-Molina, Louis Felix Nothias, Stephanie B Orchanian, Talima Pearson, Samuel L Peoples, Daniel Petras, Mary Lai Preuss, Elmar Pruesse, Lasse Buur Rasmussen, Adam Rivers, Michael S Robeson, Patrick Rosenthal, Nicola Segata, Michael Shaffer, Arron Shiffer, Rashmi Sinha, Se Jin Song, John R Spear, Austin D Swafford, Luke R Thompson, Pedro J Torres, Pauline Trinh, Anupriya Tripathi, Peter J Turnbaugh, Sabah Ul-Hasan, Justin JJ van der Hooft, Fernando Vargas, Yoshiki Vázquez-Baeza, Emily Vogtmann, Max von Hippel, William Walters, Yunhu Wan, Mingxun Wang, Jonathan Warren, Kyle C Weber, Chase HD Williamson, Amy D Willis, Zhenjiang Zech Xu, Jesse R Zaneveld, Yilong Zhang, Qiyun Zhu, Rob Knight and J Gregory Caporaso:
Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2.
(eprint)
Nature Biotechnology
37
(2019)
|
|
q2-sample-classifier
QIIME 2 plugin for machine learning prediction of sample data
|
Versions of package q2-sample-classifier |
Release | Version | Architectures |
sid | 2024.5.0-2 | all |
bookworm | 2022.11.1-3 | all |
bullseye | 2020.11.1-3 | all |
upstream | 2024.10.0 |
|
License: DFSG free
|
QIIME 2 is a powerful, extensible, and decentralized microbiome analysis
package with a focus on data and analysis transparency. QIIME 2 enables
researchers to start an analysis with raw DNA sequence data and finish with
publication-quality figures and statistical results.
Key features:
- Integrated and automatic tracking of data provenance
- Semantic type system
- Plugin system for extending microbiome analysis functionality
- Support for multiple types of user interfaces (e.g. API, command line,
graphical)
QIIME 2 is a complete redesign and rewrite of the QIIME 1 microbiome analysis
pipeline. QIIME 2 will address many of the limitations of QIIME 1, while
retaining the features that makes QIIME 1 a powerful and widely-used analysis
pipeline.
QIIME 2 currently supports an initial end-to-end microbiome analysis pipeline.
New functionality will regularly become available through QIIME 2 plugins. You
can view a list of plugins that are currently available on the QIIME 2 plugin
availability page. The future plugins page lists plugins that are being
developed.
Microbiome studies often aim to predict outcomes or differentiate samples
based on their microbial compositions, tasks that can be efficiently
performed by supervised learning methods. The q2-sample-classifier plugin
makes these methods more accessible, reproducible, and interpretable to
a broad audience of microbiologists, clinicians, and others who wish to
utilize supervised learning methods for predicting sample characteristics
based on microbiome composition or other "omics" data
|
|
q2-taxa
QIIME 2 plugin for working with feature taxonomy annotations
|
Versions of package q2-taxa |
Release | Version | Architectures |
bookworm | 2022.11.1+dfsg-2 | all |
bullseye | 2020.11.1+dfsg-2 | all |
sid | 2024.5.0+dfsg-1 | all |
upstream | 2024.10.0 |
|
License: DFSG free
|
QIIME 2 is a powerful, extensible, and decentralized microbiome analysis
package with a focus on data and analysis transparency. QIIME 2 enables
researchers to start an analysis with raw DNA sequence data and finish with
publication-quality figures and statistical results.
Key features:
- Integrated and automatic tracking of data provenance
- Semantic type system
- Plugin system for extending microbiome analysis functionality
- Support for multiple types of user interfaces (e.g. API, command line,
graphical)
QIIME 2 is a complete redesign and rewrite of the QIIME 1 microbiome analysis
pipeline. QIIME 2 will address many of the limitations of QIIME 1, while
retaining the features that makes QIIME 1 a powerful and widely-used analysis
pipeline.
QIIME 2 currently supports an initial end-to-end microbiome analysis pipeline.
New functionality will regularly become available through QIIME 2 plugins. You
can view a list of plugins that are currently available on the QIIME 2 plugin
availability page. The future plugins page lists plugins that are being
developed.
Please cite:
Evan Bolyen, Jai Ram Rideout, Matthew R Dillon, Nicholas A Bokulich, Christian Abnet, Gabriel A Al-Ghalith, Harriet Alexander, Eric J Alm, Manimozhiyan Arumugam, Francesco Asnicar, Yang Bai, Jordan E Bisanz, Kyle Bittinger, Asker Brejnrod, Colin J Brislawn, C Titus Brown, Benjamin J Callahan, Andrés Mauricio Caraballo-Rodríguez, John Chase, Emily Cope, Ricardo Da Silva, Pieter C Dorrestein, Gavin M Douglas, Daniel M Durall, Claire Duvallet, Christian F Edwardson, Madeleine Ernst, Mehrbod Estaki, Jennifer Fouquier, Julia M Gauglitz, Deanna L Gibson, Antonio Gonzalez, Kestrel Gorlick, Jiarong Guo, Benjamin Hillmann, Susan Holmes, Hannes Holste, Curtis Huttenhower, Gavin Huttley, Stefan Janssen, Alan K Jarmusch, Lingjing Jiang, Benjamin Kaehler, Kyo Bin Kang, Christopher R Keefe, Paul Keim, Scott T Kelley, Dan Knights, Irina Koester, Tomasz Kosciolek, Jorden Kreps, Morgan GI Langille, Joslynn Lee, Ruth Ley, Yong-Xin Liu, Erikka Loftfield, Catherine Lozupone, Massoud Maher, Clarisse Marotz, Bryan D Martin, Daniel McDonald, Lauren J McIver, Alexey V Melnik, Jessica L Metcalf, Sydney C Morgan, Jamie Morton, Ahmad Turan Naimey, Jose A Navas-Molina, Louis Felix Nothias, Stephanie B Orchanian, Talima Pearson, Samuel L Peoples, Daniel Petras, Mary Lai Preuss, Elmar Pruesse, Lasse Buur Rasmussen, Adam Rivers, Michael S Robeson, Patrick Rosenthal, Nicola Segata, Michael Shaffer, Arron Shiffer, Rashmi Sinha, Se Jin Song, John R Spear, Austin D Swafford, Luke R Thompson, Pedro J Torres, Pauline Trinh, Anupriya Tripathi, Peter J Turnbaugh, Sabah Ul-Hasan, Justin JJ van der Hooft, Fernando Vargas, Yoshiki Vázquez-Baeza, Emily Vogtmann, Max von Hippel, William Walters, Yunhu Wan, Mingxun Wang, Jonathan Warren, Kyle C Weber, Chase HD Williamson, Amy D Willis, Zhenjiang Zech Xu, Jesse R Zaneveld, Yilong Zhang, Qiyun Zhu, Rob Knight and J Gregory Caporaso:
Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2.
(eprint)
Nature Biotechnology
37
(2019)
|
|
q2-types
QIIME 2 plugin defining types for microbiome analysis
|
Versions of package q2-types |
Release | Version | Architectures |
bullseye | 2020.11.1-1 | all |
sid | 2024.5.0-1 | all |
bookworm | 2022.11.1-2 | all |
upstream | 2024.10.0 |
|
License: DFSG free
|
QIIME 2 is a powerful, extensible, and decentralized microbiome analysis
package with a focus on data and analysis transparency. QIIME 2 enables
researchers to start an analysis with raw DNA sequence data and finish with
publication-quality figures and statistical results.
Key features:
- Integrated and automatic tracking of data provenance
- Semantic type system
- Plugin system for extending microbiome analysis functionality
- Support for multiple types of user interfaces (e.g. API, command line,
graphical)
QIIME 2 is a complete redesign and rewrite of the QIIME 1 microbiome analysis
pipeline. QIIME 2 will address many of the limitations of QIIME 1, while
retaining the features that makes QIIME 1 a powerful and widely-used analysis
pipeline.
QIIME 2 currently supports an initial end-to-end microbiome analysis pipeline.
New functionality will regularly become available through QIIME 2 plugins. You
can view a list of plugins that are currently available on the QIIME 2 plugin
availability page. The future plugins page lists plugins that are being
developed.
Please cite:
Evan Bolyen, Jai Ram Rideout, Matthew R Dillon, Nicholas A Bokulich, Christian Abnet, Gabriel A Al-Ghalith, Harriet Alexander, Eric J Alm, Manimozhiyan Arumugam, Francesco Asnicar, Yang Bai, Jordan E Bisanz, Kyle Bittinger, Asker Brejnrod, Colin J Brislawn, C Titus Brown, Benjamin J Callahan, Andrés Mauricio Caraballo-Rodríguez, John Chase, Emily Cope, Ricardo Da Silva, Pieter C Dorrestein, Gavin M Douglas, Daniel M Durall, Claire Duvallet, Christian F Edwardson, Madeleine Ernst, Mehrbod Estaki, Jennifer Fouquier, Julia M Gauglitz, Deanna L Gibson, Antonio Gonzalez, Kestrel Gorlick, Jiarong Guo, Benjamin Hillmann, Susan Holmes, Hannes Holste, Curtis Huttenhower, Gavin Huttley, Stefan Janssen, Alan K Jarmusch, Lingjing Jiang, Benjamin Kaehler, Kyo Bin Kang, Christopher R Keefe, Paul Keim, Scott T Kelley, Dan Knights, Irina Koester, Tomasz Kosciolek, Jorden Kreps, Morgan GI Langille, Joslynn Lee, Ruth Ley, Yong-Xin Liu, Erikka Loftfield, Catherine Lozupone, Massoud Maher, Clarisse Marotz, Bryan D Martin, Daniel McDonald, Lauren J McIver, Alexey V Melnik, Jessica L Metcalf, Sydney C Morgan, Jamie Morton, Ahmad Turan Naimey, Jose A Navas-Molina, Louis Felix Nothias, Stephanie B Orchanian, Talima Pearson, Samuel L Peoples, Daniel Petras, Mary Lai Preuss, Elmar Pruesse, Lasse Buur Rasmussen, Adam Rivers, Michael S Robeson, Patrick Rosenthal, Nicola Segata, Michael Shaffer, Arron Shiffer, Rashmi Sinha, Se Jin Song, John R Spear, Austin D Swafford, Luke R Thompson, Pedro J Torres, Pauline Trinh, Anupriya Tripathi, Peter J Turnbaugh, Sabah Ul-Hasan, Justin JJ van der Hooft, Fernando Vargas, Yoshiki Vázquez-Baeza, Emily Vogtmann, Max von Hippel, William Walters, Yunhu Wan, Mingxun Wang, Jonathan Warren, Kyle C Weber, Chase HD Williamson, Amy D Willis, Zhenjiang Zech Xu, Jesse R Zaneveld, Yilong Zhang, Qiyun Zhu, Rob Knight and J Gregory Caporaso:
Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2.
(eprint)
Nature Biotechnology
37
(2019)
|
|
q2cli
Click-based command line interface for QIIME 2
|
Versions of package q2cli |
Release | Version | Architectures |
sid | 2024.5.0-2 | all |
bullseye | 2020.11.1-1 | all |
bookworm | 2022.11.1-2 | all |
upstream | 2024.10.1 |
|
License: DFSG free
|
QIIME 2 is a powerful, extensible, and decentralized microbiome analysis
package with a focus on data and analysis transparency. QIIME 2 enables
researchers to start an analysis with raw DNA sequence data and finish with
publication-quality figures and statistical results.
Key features:
- Integrated and automatic tracking of data provenance
- Semantic type system
- Plugin system for extending microbiome analysis functionality
- Support for multiple types of user interfaces (e.g. API, command line,
graphical)
QIIME 2 is a complete redesign and rewrite of the QIIME 1 microbiome analysis
pipeline. QIIME 2 will address many of the limitations of QIIME 1, while
retaining the features that makes QIIME 1 a powerful and widely-used analysis
pipeline.
QIIME 2 currently supports an initial end-to-end microbiome analysis pipeline.
New functionality will regularly become available through QIIME 2 plugins. You
can view a list of plugins that are currently available on the QIIME 2 plugin
availability page. The future plugins page lists plugins that are being
developed.
Please cite:
Evan Bolyen, Jai Ram Rideout, Matthew R Dillon, Nicholas A Bokulich, Christian Abnet, Gabriel A Al-Ghalith, Harriet Alexander, Eric J Alm, Manimozhiyan Arumugam, Francesco Asnicar, Yang Bai, Jordan E Bisanz, Kyle Bittinger, Asker Brejnrod, Colin J Brislawn, C Titus Brown, Benjamin J Callahan, Andrés Mauricio Caraballo-Rodríguez, John Chase, Emily Cope, Ricardo Da Silva, Pieter C Dorrestein, Gavin M Douglas, Daniel M Durall, Claire Duvallet, Christian F Edwardson, Madeleine Ernst, Mehrbod Estaki, Jennifer Fouquier, Julia M Gauglitz, Deanna L Gibson, Antonio Gonzalez, Kestrel Gorlick, Jiarong Guo, Benjamin Hillmann, Susan Holmes, Hannes Holste, Curtis Huttenhower, Gavin Huttley, Stefan Janssen, Alan K Jarmusch, Lingjing Jiang, Benjamin Kaehler, Kyo Bin Kang, Christopher R Keefe, Paul Keim, Scott T Kelley, Dan Knights, Irina Koester, Tomasz Kosciolek, Jorden Kreps, Morgan GI Langille, Joslynn Lee, Ruth Ley, Yong-Xin Liu, Erikka Loftfield, Catherine Lozupone, Massoud Maher, Clarisse Marotz, Bryan D Martin, Daniel McDonald, Lauren J McIver, Alexey V Melnik, Jessica L Metcalf, Sydney C Morgan, Jamie Morton, Ahmad Turan Naimey, Jose A Navas-Molina, Louis Felix Nothias, Stephanie B Orchanian, Talima Pearson, Samuel L Peoples, Daniel Petras, Mary Lai Preuss, Elmar Pruesse, Lasse Buur Rasmussen, Adam Rivers, Michael S Robeson, Patrick Rosenthal, Nicola Segata, Michael Shaffer, Arron Shiffer, Rashmi Sinha, Se Jin Song, John R Spear, Austin D Swafford, Luke R Thompson, Pedro J Torres, Pauline Trinh, Anupriya Tripathi, Peter J Turnbaugh, Sabah Ul-Hasan, Justin JJ van der Hooft, Fernando Vargas, Yoshiki Vázquez-Baeza, Emily Vogtmann, Max von Hippel, William Walters, Yunhu Wan, Mingxun Wang, Jonathan Warren, Kyle C Weber, Chase HD Williamson, Amy D Willis, Zhenjiang Zech Xu, Jesse R Zaneveld, Yilong Zhang, Qiyun Zhu, Rob Knight and J Gregory Caporaso:
Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2.
(eprint)
Nature Biotechnology
37
(2019)
|
|
q2templates
Design template package for QIIME 2 Plugins
|
Versions of package q2templates |
Release | Version | Architectures |
trixie | 2024.5.0+ds-1 | all |
bullseye | 2020.11.1+dfsg-1 | all |
sid | 2024.5.0+ds-1 | all |
bookworm | 2022.11.1+ds-2 | all |
upstream | 2024.10.0 |
|
License: DFSG free
|
QIIME 2 is a powerful, extensible, and decentralized microbiome analysis
package with a focus on data and analysis transparency. QIIME 2 enables
researchers to start an analysis with raw DNA sequence data and finish with
publication-quality figures and statistical results.
Key features:
- Integrated and automatic tracking of data provenance
- Semantic type system
- Plugin system for extending microbiome analysis functionality
- Support for multiple types of user interfaces (e.g. API, command line,
graphical)
QIIME 2 is a complete redesign and rewrite of the QIIME 1 microbiome analysis
pipeline. QIIME 2 will address many of the limitations of QIIME 1, while
retaining the features that makes QIIME 1 a powerful and widely-used analysis
pipeline.
QIIME 2 currently supports an initial end-to-end microbiome analysis pipeline.
New functionality will regularly become available through QIIME 2 plugins. You
can view a list of plugins that are currently available on the QIIME 2 plugin
availability page. The future plugins page lists plugins that are being
developed.
This package provides templates for QIIME 2 plugins.
Please cite:
Evan Bolyen, Jai Ram Rideout, Matthew R Dillon, Nicholas A Bokulich, Christian Abnet, Gabriel A Al-Ghalith, Harriet Alexander, Eric J Alm, Manimozhiyan Arumugam, Francesco Asnicar, Yang Bai, Jordan E Bisanz, Kyle Bittinger, Asker Brejnrod, Colin J Brislawn, C Titus Brown, Benjamin J Callahan, Andrés Mauricio Caraballo-Rodríguez, John Chase, Emily Cope, Ricardo Da Silva, Pieter C Dorrestein, Gavin M Douglas, Daniel M Durall, Claire Duvallet, Christian F Edwardson, Madeleine Ernst, Mehrbod Estaki, Jennifer Fouquier, Julia M Gauglitz, Deanna L Gibson, Antonio Gonzalez, Kestrel Gorlick, Jiarong Guo, Benjamin Hillmann, Susan Holmes, Hannes Holste, Curtis Huttenhower, Gavin Huttley, Stefan Janssen, Alan K Jarmusch, Lingjing Jiang, Benjamin Kaehler, Kyo Bin Kang, Christopher R Keefe, Paul Keim, Scott T Kelley, Dan Knights, Irina Koester, Tomasz Kosciolek, Jorden Kreps, Morgan GI Langille, Joslynn Lee, Ruth Ley, Yong-Xin Liu, Erikka Loftfield, Catherine Lozupone, Massoud Maher, Clarisse Marotz, Bryan D Martin, Daniel McDonald, Lauren J McIver, Alexey V Melnik, Jessica L Metcalf, Sydney C Morgan, Jamie Morton, Ahmad Turan Naimey, Jose A Navas-Molina, Louis Felix Nothias, Stephanie B Orchanian, Talima Pearson, Samuel L Peoples, Daniel Petras, Mary Lai Preuss, Elmar Pruesse, Lasse Buur Rasmussen, Adam Rivers, Michael S Robeson, Patrick Rosenthal, Nicola Segata, Michael Shaffer, Arron Shiffer, Rashmi Sinha, Se Jin Song, John R Spear, Austin D Swafford, Luke R Thompson, Pedro J Torres, Pauline Trinh, Anupriya Tripathi, Peter J Turnbaugh, Sabah Ul-Hasan, Justin JJ van der Hooft, Fernando Vargas, Yoshiki Vázquez-Baeza, Emily Vogtmann, Max von Hippel, William Walters, Yunhu Wan, Mingxun Wang, Jonathan Warren, Kyle C Weber, Chase HD Williamson, Amy D Willis, Zhenjiang Zech Xu, Jesse R Zaneveld, Yilong Zhang, Qiyun Zhu, Rob Knight and J Gregory Caporaso:
Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2.
(eprint)
Nature Biotechnology
37
(2019)
|
|
qiime
Quantitative Insights Into Microbial Ecology
|
Versions of package qiime |
Release | Version | Architectures |
bookworm | 2022.11.1-2 | all |
bullseye | 2020.11.1-1 | all |
jessie | 1.8.0+dfsg-4 | amd64,armel,armhf,i386 |
sid | 2024.5.0-1 | all |
upstream | 2024.10.1 |
Debtags of package qiime: |
role | program |
|
License: DFSG free
|
Microbes are surrounding us, animals, plants and all their parasites with
strong effect on these and the environment these live in. Soil quality comes
to mind but also the effect that bacteria have on each other. Humans are
influencing the absolute and relative abundance of bacteria by antibiotics,
food, fertilizers - you name it - and these changes affect us.
QIIME 2 is a powerful, extensible, and decentralized microbiome analysis
package with a focus on data and analysis transparency. QIIME 2 enables
researchers to start an analysis with raw DNA sequence data and finish with
publication-quality figures and statistical results.
Key features:
- Integrated and automatic tracking of data provenance
- Semantic type system
- Plugin system for extending microbiome analysis functionality
- Support for multiple types of user interfaces (e.g. API, command line,
graphical)
QIIME 2 is a complete redesign and rewrite of the QIIME 1 microbiome analysis
pipeline. QIIME 2 will address many of the limitations of QIIME 1, while
retaining the features that makes QIIME 1 a powerful and widely-used analysis
pipeline.
QIIME 2 currently supports an initial end-to-end microbiome analysis pipeline.
New functionality will regularly become available through QIIME 2 plugins. You
can view a list of plugins that are currently available on the QIIME 2 plugin
availability page. The future plugins page lists plugins that are being
developed.
Please cite:
Evan Bolyen, Jai Ram Rideout, Matthew R Dillon, Nicholas A Bokulich, Christian Abnet, Gabriel A Al-Ghalith, Harriet Alexander, Eric J Alm, Manimozhiyan Arumugam, Francesco Asnicar, Yang Bai, Jordan E Bisanz, Kyle Bittinger, Asker Brejnrod, Colin J Brislawn, C Titus Brown, Benjamin J Callahan, Andrés Mauricio Caraballo-Rodríguez, John Chase, Emily Cope, Ricardo Da Silva, Pieter C Dorrestein, Gavin M Douglas, Daniel M Durall, Claire Duvallet, Christian F Edwardson, Madeleine Ernst, Mehrbod Estaki, Jennifer Fouquier, Julia M Gauglitz, Deanna L Gibson, Antonio Gonzalez, Kestrel Gorlick, Jiarong Guo, Benjamin Hillmann, Susan Holmes, Hannes Holste, Curtis Huttenhower, Gavin Huttley, Stefan Janssen, Alan K Jarmusch, Lingjing Jiang, Benjamin Kaehler, Kyo Bin Kang, Christopher R Keefe, Paul Keim, Scott T Kelley, Dan Knights, Irina Koester, Tomasz Kosciolek, Jorden Kreps, Morgan GI Langille, Joslynn Lee, Ruth Ley, Yong-Xin Liu, Erikka Loftfield, Catherine Lozupone, Massoud Maher, Clarisse Marotz, Bryan D Martin, Daniel McDonald, Lauren J McIver, Alexey V Melnik, Jessica L Metcalf, Sydney C Morgan, Jamie Morton, Ahmad Turan Naimey, Jose A Navas-Molina, Louis Felix Nothias, Stephanie B Orchanian, Talima Pearson, Samuel L Peoples, Daniel Petras, Mary Lai Preuss, Elmar Pruesse, Lasse Buur Rasmussen, Adam Rivers, Michael S Robeson, Patrick Rosenthal, Nicola Segata, Michael Shaffer, Arron Shiffer, Rashmi Sinha, Se Jin Song, John R Spear, Austin D Swafford, Luke R Thompson, Pedro J Torres, Pauline Trinh, Anupriya Tripathi, Peter J Turnbaugh, Sabah Ul-Hasan, Justin JJ van der Hooft, Fernando Vargas, Yoshiki Vázquez-Baeza, Emily Vogtmann, Max von Hippel, William Walters, Yunhu Wan, Mingxun Wang, Jonathan Warren, Kyle C Weber, Chase HD Williamson, Amy D Willis, Zhenjiang Zech Xu, Jesse R Zaneveld, Yilong Zhang, Qiyun Zhu, Rob Knight and J Gregory Caporaso:
Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2.
(PubMed,eprint)
Nature Biotechnology
37:852 - 857
(2019)
Topics: Microbial ecology
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r-bioc-affxparser
Affymetrix File Parsing SDK
|
Versions of package r-bioc-affxparser |
Release | Version | Architectures |
experimental | 1.78.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
sid | 1.76.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
trixie | 1.76.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bookworm | 1.70.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
upstream | 1.78.0 |
|
License: DFSG free
|
Package for parsing Affymetrix files (CDF, CEL, CHP, BPMAP, BAR). It
provides methods for fast and memory efficient parsing of Affymetrix
files using the Affymetrix' Fusion SDK. Both ASCII- and binary-based
files are supported. Currently, there are methods for reading chip
definition file (CDF) and a cell intensity file (CEL). These files can
be read either in full or in part. For example, probe signals from a few
probesets can be extracted very quickly from a set of CEL files into a
convenient list structure.
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r-bioc-affy
BioConductor methods for Affymetrix Oligonucleotide Arrays
|
Versions of package r-bioc-affy |
Release | Version | Architectures |
stretch | 1.52.0-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
trixie | 1.82.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
jessie | 1.42.3-1 | amd64,armel,armhf,i386 |
experimental | 1.84.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.68.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.76.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 1.60.0-1 | amd64,arm64,armhf,i386 |
sid | 1.82.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
upstream | 1.84.0 |
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License: DFSG free
|
This is part of the BioConductor GNU R suite. The package contains
functions for exploratory oligonucleotide array analysis.
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r-bioc-affyio
BioConductor tools for parsing Affymetrix data files
|
Versions of package r-bioc-affyio |
Release | Version | Architectures |
buster | 1.52.0-1 | amd64,arm64,armhf,i386 |
stretch | 1.44.0-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.68.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.74.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
jessie | 1.32.0-1 | amd64,armel,armhf,i386 |
experimental | 1.76.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
trixie | 1.74.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.60.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
upstream | 1.76.0 |
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License: DFSG free
|
This BioConductor package provides routines for parsing Affymetrix data
files based upon file format information. Primary focus is on accessing
the CEL and CDF file formats.
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r-bioc-altcdfenvs
BioConductor alternative CDF environments
|
Versions of package r-bioc-altcdfenvs |
Release | Version | Architectures |
buster | 2.44.0-1 | all |
stretch | 2.36.0-1 | all |
trixie | 2.66.0-1 | all |
sid | 2.66.0-1 | all |
bookworm | 2.60.0-1 | all |
experimental | 2.68.0-1 | all |
jessie | 2.26.0-1 | all |
bullseye | 2.52.0-1 | all |
upstream | 2.68.0 |
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License: DFSG free
|
This BioConductor module provides alternative CDF environments (aka
probeset mappings) which are Convenience data structures and functions
to handle cdfenvs.
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r-bioc-annotate
BioConductor annotation for microarrays
|
Versions of package r-bioc-annotate |
Release | Version | Architectures |
experimental | 1.84.0+dfsg-1 | all |
bookworm | 1.76.0+dfsg-1 | all |
bullseye | 1.68.0+dfsg-1 | all |
trixie | 1.82.0+dfsg-1 | all |
sid | 1.82.0+dfsg-1 | all |
buster | 1.60.0+dfsg-1 | all |
stretch | 1.52.1+dfsg-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
upstream | 1.84.0 |
|
License: DFSG free
|
This BioConductor module provides methods for annotation for microarrays.
In its current state the basic purpose of annotate is to
supply interface routines that support user actions that rely on the
different meta-data packages provided through the Bioconductor
Project.
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r-bioc-annotationdbi
GNU R Annotation Database Interface for BioConductor
|
Versions of package r-bioc-annotationdbi |
Release | Version | Architectures |
buster | 1.44.0-1 | all |
experimental | 1.68.0-1 | all |
bookworm | 1.60.0-1 | all |
bullseye | 1.52.0-1 | all |
stretch | 1.36.1-2 | all |
jessie | 1.26.1-1 | all |
trixie | 1.66.0-1 | all |
sid | 1.66.0-1 | all |
upstream | 1.68.0 |
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License: DFSG free
|
This BioConductor module provides user interface and database
connection code for annotation data packages using SQLite data
storage.
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r-bioc-annotationhub
GNU R client to access AnnotationHub resources
|
Versions of package r-bioc-annotationhub |
Release | Version | Architectures |
sid | 3.12.0+dfsg-1 | all |
experimental | 3.14.0+dfsg-1 | all |
bookworm | 3.6.0+dfsg-1 | all |
bullseye | 2.22.0+dfsg-1 | all |
trixie | 3.12.0+dfsg-1 | all |
buster | 2.14.3+dfsg-1 | all |
stretch | 2.6.4-1 | all |
upstream | 3.14.0 |
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License: DFSG free
|
This package provides a client for the Bioconductor AnnotationHub web
resource. The AnnotationHub web resource provides a central location
where genomic files (e.g., VCF, bed, wig) and other resources from
standard locations (e.g., UCSC, Ensembl) can be discovered. The resource
includes metadata about each resource, e.g., a textual description,
tags, and date of modification. The client creates and manages a local
cache of files retrieved by the user, helping with quick and
reproducible access.
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r-bioc-aroma.light
BioConductor methods normalization and visualization of microarray data
|
Versions of package r-bioc-aroma.light |
Release | Version | Architectures |
buster | 3.12.0-1 | all |
bookworm | 3.28.0-1 | all |
stretch | 3.4.0-1 | all |
bullseye | 3.20.0-1 | all |
sid | 3.34.0-1 | all |
experimental | 3.36.0-1 | all |
trixie | 3.34.0-1 | all |
upstream | 3.36.0 |
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License: DFSG free
|
This BioConductor module provides light-weight methods for
normalization and visualization of microarray data using only basic R
data types.
Methods for microarray analysis that take basic data types such as
matrices and lists of vectors. These methods can be used standalone, be
utilized in other packages, or be wrapped up in higher-level classes.
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r-bioc-arrayexpress
access to the ArrayExpress Microarray Database at EBI
|
Versions of package r-bioc-arrayexpress |
Release | Version | Architectures |
experimental | 1.66.0-1 | all |
trixie | 1.64.0-1 | all |
bookworm | 1.57.0-1 | all |
sid | 1.64.0-1 | all |
upstream | 1.66.0 |
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License: DFSG free
|
Access to the ArrayExpress Microarray Database at EBI and build
Bioconductor data structures: ExpressionSet, AffyBatch,
NChannelSet
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r-bioc-biocgenerics
generic functions for Bioconductor
|
Versions of package r-bioc-biocgenerics |
Release | Version | Architectures |
trixie | 0.50.0-2 | all |
experimental | 0.52.0-1 | all |
stretch | 0.20.0-1 | all |
jessie | 0.10.0-1 | all |
sid | 0.50.0-2 | all |
bullseye | 0.36.0-1 | all |
bookworm | 0.44.0-2 | all |
buster | 0.28.0-2 | all |
upstream | 0.52.0 |
|
License: DFSG free
|
S4 generic functions needed by many other Bioconductor packages.
Bioconductor provides tools for the analysis and comprehension of
high-throughput genomic data. Bioconductor uses the R statistical
programming language, and is open source and open development.
Please cite:
Wolfgang Huber, Vincent J Carey, Robert Gentleman, Simon Anders, Marc Carlson, Benilton S Carvalho, Hector Corrada Bravo, Sean Davis, Laurent Gatto, Thomas Girke, Raphael Gottardo, Florian Hahne, Kasper D Hansen, Rafael A Irizarry, Michael Lawrence, Michael I Love, James MacDonald, Valerie Obenchain, Andrzej K Oleś, Hervé Pagès, Alejandro Reyes, Paul Shannon, Gordon K Smyth, Dan Tenenbaum, Levi Waldron and Martin Morgan:
Orchestrating high-throughput genomic analysis with Bioconductor.
(PubMed)
Nature Methods
(2015)
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r-bioc-biocneighbors
Nearest Neighbor Detection for Bioconductor Packages
|
Versions of package r-bioc-biocneighbors |
Release | Version | Architectures |
sid | 1.22.0+ds-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
trixie | 1.22.0+ds-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bookworm | 1.16.0+ds-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 1.8.2+ds-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
upstream | 2.0.1 |
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License: DFSG free
|
Implements exact and approximate methods for nearest neighbor
detection, in a framework that allows them to be easily switched within
Bioconductor packages or workflows. Exact searches can be performed using
the k-means for k-nearest neighbors algorithm or with vantage point trees.
Approximate searches can be performed using the Annoy or HNSW libraries.
Searching on either Euclidean or Manhattan distances is supported.
Parallelization is achieved for all methods by using BiocParallel. Functions
are also provided to search for all neighbors within a given distance.
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r-bioc-biomart
GNU R Interface to BioMart databases (Ensembl, COSMIC, Wormbase and Gramene)
|
Versions of package r-bioc-biomart |
Release | Version | Architectures |
stretch | 2.30.0-1 | all |
bookworm | 2.54.0+dfsg-1 | all |
experimental | 2.62.0+dfsg-1 | all |
bullseye | 2.46.2+dfsg-1 | all |
sid | 2.60.1+dfsg-1 | all |
trixie | 2.60.1+dfsg-1 | all |
jessie | 2.20.0-1 | all |
buster | 2.38.0+dfsg-1 | all |
upstream | 2.62.0 |
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License: DFSG free
|
In recent years a wealth of biological data has become available in
public data repositories. Easy access to these valuable data resources
and firm integration with data analysis is needed for comprehensive
bioinformatics data analysis. biomaRt provides an interface to a growing
collection of databases implementing the BioMart software suite
(http://www.biomart.org). The package enables retrieval of large amounts
of data in a uniform way without the need to know the underlying
database schemas or write complex SQL queries. Examples of BioMart
databases are Ensembl, COSMIC, Uniprot, HGNC, Gramene, Wormbase and
dbSNP mapped to Ensembl. These major databases give biomaRt users direct
access to a diverse set of data and enable a wide range of powerful
online queries from gene annotation to database mining.
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r-bioc-biomformat
GNU R interface package for the BIOM file format
|
Versions of package r-bioc-biomformat |
Release | Version | Architectures |
bookworm | 1.26.0+dfsg-1 | all |
buster | 1.10.1+dfsg-1 | all |
bullseye | 1.18.0+dfsg-2 | all |
trixie | 1.32.0+dfsg-1 | all |
sid | 1.32.0+dfsg-1 | all |
stretch | 1.2.0-1 | all |
experimental | 1.34.0+dfsg-1 | all |
upstream | 1.34.0 |
|
License: DFSG free
|
This is an R package for interfacing with the BIOM format. This package
includes basic tools for reading biom-format files, accessing and
subsetting data tables from a biom object (which is more complex than a
single table), as well as limited support for writing a biom-object back
to a biom-format file. The design of this API is intended to match the
Python API and other tools included with the biom-format project, but
with a decidedly "R flavor" that should be familiar to R users. This
includes S4 classes and methods, as well as extensions of common core
functions/methods.
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r-bioc-biostrings
GNU R string objects representing biological sequences
|
Versions of package r-bioc-biostrings |
Release | Version | Architectures |
sid | 2.72.1+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
experimental | 2.74.0+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bookworm | 2.66.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 2.72.1+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
stretch | 2.42.1-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 2.50.2-1 | amd64,arm64,armhf,i386 |
bullseye | 2.58.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
jessie | 2.32.1-1 | amd64,armel,armhf,i386 |
upstream | 2.74.0 |
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License: DFSG free
|
Memory efficient string containers, string matching algorithms, and other
utilities, for fast manipulation of large biological sequences or set of
sequences.
|
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r-bioc-biovizbase
GNU R basic graphic utilities for visualization of genomic data
|
Versions of package r-bioc-biovizbase |
Release | Version | Architectures |
buster | 1.30.1-1 | amd64,arm64,armhf,i386 |
bullseye | 1.38.0-1 | amd64,arm64,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.52.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
trixie | 1.52.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bookworm | 1.46.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
experimental | 1.54.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
jessie | 1.12.3-1 | amd64,armel,armhf,i386 |
stretch | 1.22.0-2 | amd64,arm64,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
upstream | 1.54.0 |
|
License: DFSG free
|
The biovizBase package is designed to provide a set of utilities, color
schemes and conventions for genomic data. It serves as the base for
various high-level packages for biological data visualization. This
saves development effort and encourages consistency.
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r-bioc-bitseq
transcript expression inference and analysis for RNA-seq data
|
Versions of package r-bioc-bitseq |
Release | Version | Architectures |
buster | 1.26.1+dfsg-1 | amd64,arm64,armhf,i386 |
bullseye | 1.34.0+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
|
License: DFSG free
|
The BitSeq package is targeted for transcript expression
analysis and differential expression analysis of RNA-seq data
in two stage process. In the first stage it uses Bayesian
inference methodology to infer expression of individual
transcripts from individual RNA-seq experiments. The second
stage of BitSeq embraces the differential expression analysis
of transcript expression. Providing expression estimates from
replicates of multiple conditions, Log-Normal model of the
estimates is used for inferring the condition mean transcript
expression and ranking the transcripts based on the likelihood
of differential expression.
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r-bioc-bsgenome
BioConductor infrastructure for Biostrings-based genome data packages
|
Versions of package r-bioc-bsgenome |
Release | Version | Architectures |
sid | 1.72.0-1 | all |
trixie | 1.72.0-1 | all |
experimental | 1.74.0-1 | all |
buster | 1.50.0-1 | all |
bookworm | 1.66.3-1 | all |
stretch | 1.42.0-2 | all |
jessie | 1.32.0-1 | all |
bullseye | 1.58.0-1 | all |
upstream | 1.74.0 |
|
License: DFSG free
|
This BioConductor module provides some basic infrastructure for
Biostrings-based genome data packages.
|
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r-bioc-cner
CNE Detection and Visualization
|
Versions of package r-bioc-cner |
Release | Version | Architectures |
bullseye | 1.26.0+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.34.0+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 1.18.1+dfsg-1 | amd64,arm64,armhf,i386 |
experimental | 1.42.0+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
trixie | 1.40.0+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
sid | 1.40.0+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
upstream | 1.42.0 |
|
License: DFSG free
|
Large-scale identification and advanced visualization
of sets of conserved noncoding elements.
|
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r-bioc-complexheatmap
make complex heatmaps using GNU R
|
Versions of package r-bioc-complexheatmap |
Release | Version | Architectures |
bullseye | 2.6.2+dfsg-1 | all |
trixie | 2.20.0+dfsg-1 | all |
sid | 2.20.0+dfsg-1 | all |
bookworm | 2.14.0+dfsg-1 | all |
experimental | 2.22.0+dfsg-1 | all |
upstream | 2.22.0 |
|
License: DFSG free
|
Complex heatmaps are efficient to visualize associations
between different sources of data sets and reveal potential patterns.
Here the ComplexHeatmap package provides a highly flexible way to arrange
multiple heatmaps and supports various annotation graphics.
|
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r-bioc-ctc
Cluster and Tree Conversion
|
Versions of package r-bioc-ctc |
Release | Version | Architectures |
sid | 1.78.0-1 | all |
trixie | 1.78.0-1 | all |
bookworm | 1.72.0-1 | all |
experimental | 1.80.0-1 | all |
bullseye | 1.64.0-1 | all |
upstream | 1.80.0 |
|
License: DFSG free
|
Tools for export and import classification trees and clusters to other
programs.
|
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r-bioc-cummerbund
tool for analysis of Cufflinks RNA-Seq output
|
Versions of package r-bioc-cummerbund |
Release | Version | Architectures |
jessie | 2.6.1-1 | all |
buster | 2.24.0-2 | all |
experimental | 2.48.0-1 | all |
sid | 2.46.0-1 | all |
trixie | 2.46.0-1 | all |
stretch | 2.16.0-2 | all |
bookworm | 2.40.0-1 | all |
bullseye | 2.32.0-1 | all |
upstream | 2.48.0 |
|
License: DFSG free
|
Allows for persistent storage, access, exploration, and manipulation of
Cufflinks high-throughput sequencing data. In addition, provides
numerous plotting functions for commonly used visualizations.
Please cite:
L. Goff and C. Trapnell:
cummeRbund: Analysis, exploration, manipulation, and visualization of Cufflinks high-throughput sequencing data
(2012)
|
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r-bioc-dada2
sample inference from amplicon sequencing data
|
Versions of package r-bioc-dada2 |
Release | Version | Architectures |
bookworm | 1.26.0+dfsg-1 | amd64 |
experimental | 1.34.0+dfsg-1 | amd64 |
sid | 1.32.0+dfsg-1 | amd64 |
trixie | 1.32.0+dfsg-1 | amd64 |
bullseye | 1.18.0+dfsg-1 | amd64 |
upstream | 1.34.0 |
|
License: DFSG free
|
The dada2 package contributes to software workflows to interpret
sequencing data from microbiota - the relative abundance of
bacterial and/or yeast, typically measured in the gut.
It infers exact amplicon sequence
variants (ASVs) from high-throughput amplicon sequencing data,
replacing the coarser and less accurate OTU clustering approach.
The dada2 pipeline takes as input demultiplexed fastq files, and
outputs the sequence variants and their sample-wise abundances
after removing substitution and chimera errors. Taxonomic
classification is available via a native implementation of the RDP
naive Bayesian classifier, and species-level assignment to 16S
rRNA gene fragments by exact matching.
|
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r-bioc-deseq2
R package for RNA-Seq Differential Expression Analysis
|
Versions of package r-bioc-deseq2 |
Release | Version | Architectures |
buster | 1.22.2+dfsg-1 | amd64,arm64,armhf,i386 |
sid | 1.44.0+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.30.1+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
experimental | 1.46.0+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bookworm | 1.38.3+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
stretch | 1.14.1-1 | amd64,arm64,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
trixie | 1.44.0+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
upstream | 1.46.0 |
|
License: DFSG free
|
Differential gene expression analysis based on the negative binomial
distribution. Estimate variance-mean dependence in count data from
high-throughput sequencing assays and test for differential expression based
on a model using the negative binomial distribution.
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r-bioc-dnacopy
R package: DNA copy number data analysis
|
Versions of package r-bioc-dnacopy |
Release | Version | Architectures |
buster | 1.56.0-1 | amd64,arm64,armhf,i386 |
bullseye | 1.64.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
experimental | 1.80.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
stretch | 1.48.0-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.72.3-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.78.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
sid | 1.78.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
upstream | 1.80.0 |
|
License: DFSG free
|
Implements the circular binary segmentation (CBS) algorithm to segment DNA
copy number data and identify genomic regions with abnormal copy number.
This package is for analyzing array DNA copy number data, which is usually
(but not always) called array Comparative Genomic Hybridization (array CGH)
data It implements a methodology for finding change-points in these data which
are points after which the (log) test over reference ratios have changed
location. This model is that the change-points correspond to positions where
the underlying DNA copy number has changed. Therefore, change-points can be
used to identify regions of gained and lost copy number. Also provided is a
function for making relevant plots of these data.
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r-bioc-ebseq
R package for RNA-Seq Differential Expression Analysis
|
Versions of package r-bioc-ebseq |
Release | Version | Architectures |
bookworm | 1.38.0-1 | all |
bullseye | 1.30.0-1 | all |
experimental | 2.4.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
trixie | 2.2.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
sid | 2.2.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
buster | 1.22.1-2 | all |
stretch | 1.14.0-1 | all |
upstream | 2.4.0 |
|
License: DFSG free
|
r-bioc-ebseq is an R package for identifying genes and isoforms differentially
expressed (DE) across two or more biological conditions in an RNA-seq
experiment.
|
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r-bioc-ensembldb
GNU R utilities to create and use an Ensembl based annotation database
|
Versions of package r-bioc-ensembldb |
Release | Version | Architectures |
buster | 2.6.5+dfsg-1 | all |
stretch | 1.6.2-1 | all |
experimental | 2.30.0+dfsg-1 | all |
sid | 2.28.1+dfsg-1 | all |
bullseye | 2.14.0+dfsg-1 | all |
trixie | 2.28.1+dfsg-1 | all |
bookworm | 2.22.0+dfsg-1 | all |
upstream | 2.30.0 |
|
License: DFSG free
|
The package provides functions to create and use transcript centric
annotation databases/packages. The annotation for the databases are
directly fetched from Ensembl using their Perl API. The functionality
and data is similar to that of the TxDb packages from the
GenomicFeatures package, but, in addition to retrieve all
gene/transcript models and annotations from the database, the ensembldb
package provides also a filter framework allowing to retrieve
annotations for specific entries like genes encoded on a chromosome
region or transcript models of lincRNA genes.
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r-bioc-genefilter
methods for filtering genes from microarray experiments
|
Versions of package r-bioc-genefilter |
Release | Version | Architectures |
sid | 1.86.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
experimental | 1.88.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.72.1-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 1.64.0-1 | amd64,arm64,armhf,i386 |
trixie | 1.86.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
stretch | 1.56.0-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.80.3-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
upstream | 1.88.0 |
|
License: DFSG free
|
This BioConductor module provides methods for filtering genes from microarray
experiments. It contains some basic functions for filtering genes.
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r-bioc-geneplotter
R package of functions for plotting genomic data
|
Versions of package r-bioc-geneplotter |
Release | Version | Architectures |
sid | 1.82.0+dfsg-1 | all |
buster | 1.60.0-1 | all |
stretch | 1.52.0-2 | all |
bullseye | 1.68.0-1 | all |
bookworm | 1.76.0-1 | all |
trixie | 1.82.0+dfsg-1 | all |
experimental | 1.84.0+dfsg-1 | all |
upstream | 1.84.0 |
|
License: DFSG free
|
Geneplotter contains plotting functions for microarrays.
The functions cPlot and cColor allow the user to
associate microarray expression data with chromosomal location.
The plots can include any subset (by default all chromosomes are
shown) of chromosomes for the organism being considered.
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r-bioc-genomeinfodb
BioConductor utilities for manipulating chromosome identifiers
|
Versions of package r-bioc-genomeinfodb |
Release | Version | Architectures |
trixie | 1.40.1+dfsg-1 | all |
stretch | 1.10.3-1 | all |
bookworm | 1.34.9-1 | all |
jessie | 1.0.2-2 | all |
buster | 1.18.1-1 | all |
experimental | 1.42.1+dfsg-1 | all |
bullseye | 1.26.2-2 | all |
sid | 1.40.1+dfsg-1 | all |
upstream | 1.42.1 |
|
License: DFSG free
|
This package contains BioConductor utilities for manipulating
chromosome and other 'seqname' identifiers.
The Seqnames package contains data and functions that define and allow
translation between different chromosome sequence naming conventions
(e.g., "chr1" versus "1"), including a function that attempts to place
sequence names in their natural, rather than lexicographic, order.
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r-bioc-genomicalignments
BioConductor representation and manipulation of short genomic alignments
|
Versions of package r-bioc-genomicalignments |
Release | Version | Architectures |
bookworm | 1.34.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.40.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
jessie | 1.0.6-1 | amd64,armel,armhf,i386 |
sid | 1.40.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
stretch | 1.10.0-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 1.18.1-1 | amd64,arm64,armhf,i386 |
experimental | 1.42.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.26.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
upstream | 1.42.0 |
|
License: DFSG free
|
This BioConductor package provides efficient containers for storing and
manipulating short genomic alignments (typically obtained by aligning
short reads to a reference genome). This includes read counting,
computing the coverage, junction detection, and working with the
nucleotide content of the alignments.
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r-bioc-genomicfeatures
GNU R tools for making and manipulating transcript centric annotations
|
Versions of package r-bioc-genomicfeatures |
Release | Version | Architectures |
bullseye | 1.42.1+dfsg-1 | all |
jessie | 1.16.3-1 | all |
stretch | 1.26.2-1 | all |
buster | 1.34.3+dfsg-1 | all |
bookworm | 1.50.4+dfsg-1 | all |
trixie | 1.56.0+dfsg-1 | all |
sid | 1.56.0+dfsg-1 | all |
experimental | 1.58.0+dfsg-1 | all |
upstream | 1.58.0 |
|
License: DFSG free
|
A set of tools and methods for making and manipulating transcript
centric annotations. With these tools the user can easily download the
genomic locations of the transcripts, exons and cds of a given organism,
from either the UCSC Genome Browser or a BioMart database (more sources
will be supported in the future). This information is then stored in a
local database that keeps track of the relationship between transcripts,
exons, cds and genes. Flexible methods are provided for extracting the
desired features in a convenient format.
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r-bioc-genomicranges
BioConductor representation and manipulation of genomic intervals
|
Versions of package r-bioc-genomicranges |
Release | Version | Architectures |
jessie | 1.16.4-2 | amd64,armel,armhf,i386 |
trixie | 1.56.1+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
experimental | 1.58.0+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bookworm | 1.50.2+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.56.2+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
buster | 1.34.0+dfsg-1 | amd64,arm64,armhf,i386 |
bullseye | 1.42.0+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
stretch | 1.26.2-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
upstream | 1.58.0 |
|
License: DFSG free
|
The ability to efficiently store genomic annotations and alignments is
playing a central role when it comes to analyze high-throughput
sequencing data (a.k.a. NGS data). The package defines general purpose
containers for storing genomic intervals as well as more specialized
containers for storing alignments against a reference genome.
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r-bioc-geoquery
Get data from NCBI Gene Expression Omnibus (GEO)
|
Versions of package r-bioc-geoquery |
Release | Version | Architectures |
sid | 2.72.0+dfsg-1 | all |
bullseye | 2.58.0+dfsg-2 | all |
bookworm | 2.66.0+dfsg-1 | all |
experimental | 2.74.0+dfsg-1 | all |
trixie | 2.72.0+dfsg-1 | all |
upstream | 2.74.0 |
|
License: DFSG free
|
The NCBI Gene Expression Omnibus (GEO) is a public repository of
microarray data. Given the rich and varied nature of this resource, it
is only natural to want to apply BioConductor tools to these data.
GEOquery is the bridge between GEO and BioConductor.
Please cite:
Sean Davis and Paul Meltzer:
GEOquery: a bridge between the Gene Expression Omnibus (GEO) and BioConductor
Bioinformatics
14,:1846-1847,
(2007,)
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r-bioc-go.db
annotation maps describing the entire Gene Ontology
|
Versions of package r-bioc-go.db |
Release | Version | Architectures |
bookworm | 3.16.0-1 | all |
trixie | 3.19.1-1 | all |
sid | 3.19.1-1 | all |
stretch | 3.4.0-1 | all |
experimental | 3.20.0-1 | all |
buster | 3.7.0-1 | all |
bullseye | 3.12.1-1 | all |
upstream | 3.20.0 |
|
License: DFSG free
|
This package is part of BioConductor and provides a set of annotation
maps describing the entire Gene Ontology assembled using data from GO.
The package helps running the test suites of some BioConductor packages.
|
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r-bioc-graph
handle graph data structures for BioConductor
|
Versions of package r-bioc-graph |
Release | Version | Architectures |
bullseye | 1.68.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
jessie | 1.42.0-1 | amd64,armel,armhf,i386 |
bookworm | 1.76.0-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
stretch | 1.52.0-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
sid | 1.82.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
trixie | 1.82.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
buster | 1.60.0-1 | amd64,arm64,armhf,i386 |
experimental | 1.84.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
upstream | 1.84.0 |
|
License: DFSG free
|
This BioConductor module implements some simple graph handling
capabilities. These are for instance used in hypergraph module
which in turn is used by several other BioConductor packages.
|
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r-bioc-gseabase
Gene set enrichment data structures and methods
|
Versions of package r-bioc-gseabase |
Release | Version | Architectures |
experimental | 1.68.0+ds-1 | all |
sid | 1.66.0+ds-1 | all |
trixie | 1.66.0+ds-1 | all |
bookworm | 1.60.0+ds-1 | all |
upstream | 1.68.0 |
|
License: DFSG free
|
This package provides classes and methods to support Gene
Set Enrichment Analysis (GSEA).
|
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r-bioc-gsva
Gene Set Variation Analysis for microarray and RNA-seq data
|
Versions of package r-bioc-gsva |
Release | Version | Architectures |
sid | 1.52.3+ds-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
trixie | 1.52.3+ds-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bookworm | 1.46.0+ds-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
experimental | 2.0.2+ds-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
upstream | 2.0.3 |
|
License: DFSG free
|
Gene Set Variation Analysis (GSVA) is a non-parametric, unsupervised
method for estimating variation of gene set enrichment through the
samples of a expression data set. GSVA performs a change in coordinate
systems, transforming the data from a gene by sample matrix to a gene-
set by sample matrix, thereby allowing the evaluation of pathway
enrichment for each sample. This new matrix of GSVA enrichment scores
facilitates applying standard analytical methods like functional
enrichment, survival analysis, clustering, CNV-pathway analysis or cross-
tissue pathway analysis, in a pathway-centric manner.
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r-bioc-gviz
Plotting data and annotation information along genomic coordinates
|
Versions of package r-bioc-gviz |
Release | Version | Architectures |
bullseye | 1.34.0+dfsg-1 | all |
jessie | 1.8.4-1 | all |
stretch | 1.18.1-1 | all |
buster | 1.26.4-1 | all |
bookworm | 1.42.1+dfsg-1 | all |
trixie | 1.48.0+dfsg-1 | all |
sid | 1.48.0+dfsg-1 | all |
experimental | 1.50.0+dfsg-1 | all |
upstream | 1.50.0 |
|
License: DFSG free
|
Genomic data analyses requires integrated visualization of known
genomic information and new experimental data. Gviz uses the biomaRt and
the rtracklayer packages to perform live annotation queries to Ensembl
and UCSC and translates this to e.g. gene/transcript structures in
viewports of the grid graphics package. This results in genomic
information plotted together with your data.
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r-bioc-hypergraph
BioConductor hypergraph data structures
|
Versions of package r-bioc-hypergraph |
Release | Version | Architectures |
bullseye | 1.62.0-1 | all |
buster | 1.54.0-1 | all |
trixie | 1.76.0-1 | all |
bookworm | 1.70.0-1 | all |
experimental | 1.78.0-1 | all |
stretch | 1.46.0-1 | all |
jessie | 1.36.0-1 | all |
sid | 1.76.0-1 | all |
upstream | 1.78.0 |
|
License: DFSG free
|
This package BioConductor implements some simple capabilities for
representing and manipulating hypergraphs.
|
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r-bioc-impute
Imputation for microarray data
|
Versions of package r-bioc-impute |
Release | Version | Architectures |
bookworm | 1.72.3-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.78.0-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 1.78.0-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster | 1.56.0-1 | amd64,arm64,armhf,i386 |
experimental | 1.80.0-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.64.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
upstream | 1.80.0 |
|
License: DFSG free
|
R package which provide a function to perform imputation for
microarray data (currently KNN only).
|
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r-bioc-iranges
GNU R low-level containers for storing sets of integer ranges
|
Versions of package r-bioc-iranges |
Release | Version | Architectures |
jessie | 1.22.10-1 | amd64,armel,armhf,i386 |
bullseye | 2.24.1-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
experimental | 2.40.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
buster | 2.16.0-1 | amd64,arm64,armhf,i386 |
sid | 2.38.1-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
stretch | 2.8.1-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
bookworm | 2.32.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 2.38.1-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
upstream | 2.40.1 |
|
License: DFSG free
|
The IRanges class and its extensions are low-level containers for
storing sets of integer ranges. A typical use of these containers in
biology is for representing a set of chromosome regions. More specific
extensions of the IRanges class will typically allow the storage of
additional information attached to each chromosome region as well as a
hierarchical relationship between these regions.
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r-bioc-limma
linear models for microarray data
|
Versions of package r-bioc-limma |
Release | Version | Architectures |
bullseye | 3.46.0+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 3.54.1+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 3.60.6+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
sid | 3.60.6+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
experimental | 3.62.1+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
jessie | 3.22.1+dfsg-1 | amd64,armel,armhf,i386 |
buster | 3.38.3+dfsg-1 | amd64,arm64,armhf,i386 |
stretch | 3.30.8+dfsg-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
upstream | 3.62.1 |
|
License: DFSG free
|
Microarrays are microscopic plates with carefully arranged short DNA
strands and/or chemically prepared surfaces to which other DNA
preferably binds. The amount of DNA binding at different locations of
these chips, typically determined by a fluorescent dye, is to be
interpreted. The technology is typically used with DNA that is derived
from RNA, i.e to determine the activity of a gene and/or its splice
variants. But the technology is also used to determine sequence
variations in genomic DNA.
This Bioconductor package supports the analysis of gene expression
microarray data, especially the use of linear models for analysing
designed experiments and the assessment of differential expression. The
package includes pre-processing capabilities for two-colour spotted
arrays. The differential expression methods apply to all array platforms
and treat Affymetrix, single channel and two channel experiments in a
unified way.
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r-bioc-makecdfenv
BioConductor CDF Environment Maker
|
Versions of package r-bioc-makecdfenv |
Release | Version | Architectures |
jessie | 1.40.0-1 | amd64,armel,armhf,i386 |
bullseye | 1.66.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
stretch | 1.50.0-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
experimental | 1.82.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
trixie | 1.80.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bookworm | 1.74.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.80.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
buster | 1.58.0-1 | amd64,arm64,armhf,i386 |
upstream | 1.82.0 |
|
License: DFSG free
|
This package has two functions. One reads a Affymetrix chip description
file (CDF) and creates a hash table environment containing the
location/probe set membership mapping. The other creates a package that
automatically loads that environment.
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r-bioc-mergeomics
Integrative network analysis of omics data
|
Versions of package r-bioc-mergeomics |
Release | Version | Architectures |
trixie | 1.32.0-1 | all |
sid | 1.32.0-1 | all |
stretch | 1.2.0-1 | all |
buster | 1.10.0-1 | all |
experimental | 1.34.0-1 | all |
bullseye | 1.18.0-1 | all |
bookworm | 1.26.0-1 | all |
upstream | 1.34.0 |
|
License: DFSG free
|
The Mergeomics pipeline serves as a flexible framework for integrating
multidimensional omics-disease associations, functional genomics,
canonical pathways and gene-gene interaction networks to generate
mechanistic hypotheses. It includes two main parts:
1) Marker set enrichment analysis (MSEA);
2) Weighted Key Driver Analysis (wKDA).
Please cite:
Le Shu, Yuqi Zhao, Zeyneb Kurt, Sean Geoffrey Byars, Taru Tukiainen, Johannes Kettunen, Luz D. Orozco, Matteo Pellegrini, Aldons J. Lusis, Samuli Ripatti, Bin Zhang, Michael Inouye, Ville-Petteri Mäkinen and Xia Yang:
Mergeomics: multidimensional data integration to identify pathogenic perturbations to biological systems.
(eprint)
BMC Genomics
(2016)
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r-bioc-metagenomeseq
GNU R statistical analysis for sparse high-throughput sequencing
|
Versions of package r-bioc-metagenomeseq |
Release | Version | Architectures |
buster | 1.24.1-1 | all |
bookworm | 1.40.0-1 | all |
trixie | 1.46.0-1 | all |
experimental | 1.46.0-2 | all |
bullseye | 1.32.0-1 | all |
sid | 1.46.0-1 | all |
stretch | 1.16.0-2 | all |
|
License: DFSG free
|
MetagenomeSeq is designed to determine features (be it Operational
Taxanomic Unit (OTU), species, etc.) that are differentially abundant
between two or more groups of multiple samples. metagenomeSeq is
designed to address the effects of both normalization and under-sampling
of microbial communities on disease association detection and the
testing of feature correlations.
|
|
r-bioc-mofa
Multi-Omics Factor Analysis (MOFA)
|
Versions of package r-bioc-mofa |
Release | Version | Architectures |
bookworm | 1.6.1+dfsg-10 | all |
sid | 1.6.1+dfsg-13 | all |
experimental | 1.6.1+dfsg-14 | all |
bullseye | 1.6.1+dfsg-1 | all |
|
License: DFSG free
|
Multi-Omics Factor Analysis: an unsupervised framework for the
integration of multi-omics data sets.
Upstream no longer supports this package. This package only still
ships to help with rerunning/comparing/transitioning existing projects.
For new projects please upgrade to MOFA2 (MOFA+). Actually, also when
adding new data to old projects, MOFA2 has further improved the handling
of multiple factors, and to compensate for a batch effect that is likely
introduced with additional data, may be an immediate use case for that
new version.
Please cite:
Ricard Argelaguet, Britta Velten, Damien Arnol, Sascha Dietrich, Thorsten Zenz, John C Marioni, Florian Buettner, Wolfgang Huber and Oliver Stegle:
Link
to publication
Mol Syst Biol
14:e8124
(2018)
|
|
r-bioc-multiassayexperiment
Software for integrating multi-omics experiments in BioConductor
|
Versions of package r-bioc-multiassayexperiment |
Release | Version | Architectures |
trixie | 1.30.3+dfsg-2 | all |
bullseye | 1.16.0+dfsg-1 | all |
sid | 1.30.3+dfsg-2 | all |
experimental | 1.32.0+dfsg-1 | all |
bookworm | 1.24.0+dfsg-2 | all |
upstream | 1.32.0 |
|
License: DFSG free
|
MultiAssayExperiment harmonizes data management of
multiple assays performed on an overlapping set of specimens. It provides a
familiar Bioconductor user experience by extending concepts from
SummarizedExperiment, supporting an open-ended mix of standard data classes
for individual assays, and allowing subsetting by genomic ranges or rownames.
|
|
r-bioc-nanostringqcpro
??? missing short description for package r-bioc-nanostringqcpro :-(
|
Versions of package r-bioc-nanostringqcpro |
Release | Version | Architectures |
bookworm | 1.30.0-1 | all |
bullseye | 1.22.0-1 | all |
|
License: DFSG free
|
|
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r-bioc-oligo
Preprocessing tools for oligonucleotide arrays
|
Versions of package r-bioc-oligo |
Release | Version | Architectures |
bookworm | 1.62.2+ds-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.68.2+ds-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
sid | 1.68.2+ds-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
experimental | 1.70.0+ds-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
upstream | 1.70.0 |
|
License: DFSG free
|
A package to analyze oligonucleotide arrays
(expression/SNP/tiling/exon) at probe-level. It currently
supports Affymetrix (CEL files) and NimbleGen arrays (XYS
files).
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r-bioc-oligoclasses
Classes for high-throughput arrays supported by oligo and crlmm
|
Versions of package r-bioc-oligoclasses |
Release | Version | Architectures |
bookworm | 1.60.0-1 | all |
sid | 1.66.0-1 | all |
experimental | 1.68.0-1 | all |
trixie | 1.66.0-1 | all |
upstream | 1.68.0 |
|
License: DFSG free
|
This package contains class definitions, validity checks, and
initialization methods for classes used by the oligo and crlmm packages.
|
|
r-bioc-org.hs.eg.db
genome-wide annotation for Human
|
Versions of package r-bioc-org.hs.eg.db |
Release | Version | Architectures |
bookworm | 3.16.0-1 | all |
sid | 3.19.1-1 | all |
trixie | 3.19.1-1 | all |
experimental | 3.20.0-1 | all |
bullseye | 3.12.0-1 | all |
upstream | 3.20.0 |
|
License: DFSG free
|
This package provides descriptions of parts of the human genome
that have been identified to be coding for RNA, and likely also for
proteins. It also offers links to entries of equivalent (orthologous)
genes in other species.
This package is prepared from the BioConductor community and contributes
to many workflows and routine analyses in computational biology.
|
|
r-bioc-pcamethods
BioConductor collection of PCA methods
|
Versions of package r-bioc-pcamethods |
Release | Version | Architectures |
sid | 1.96.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
experimental | 1.98.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.82.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 1.74.0-1 | amd64,arm64,armhf,i386 |
trixie | 1.96.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bookworm | 1.90.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
upstream | 1.98.0 |
|
License: DFSG free
|
Provides Bayesian PCA, Probabilistic PCA, Nipals PCA,
Inverse Non-Linear PCA and the conventional SVD PCA. A cluster
based method for missing value estimation is included for
comparison. BPCA, PPCA and NipalsPCA may be used to perform PCA
on incomplete data as well as for accurate missing value
estimation. A set of methods for printing and plotting the
results is also provided. All PCA methods make use of the same
data structure (pcaRes) to provide a common interface to the
PCA results. Initiated at the Max-Planck Institute for
Molecular Plant Physiology, Golm, Germany.
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|
r-bioc-phyloseq
GNU R handling and analysis of high-throughput microbiome census data
|
Versions of package r-bioc-phyloseq |
Release | Version | Architectures |
trixie | 1.48.0+dfsg-1 | all |
stretch | 1.19.1-2 | all |
experimental | 1.50.0+dfsg-1 | all |
sid | 1.48.0+dfsg-1 | all |
buster | 1.26.1+dfsg-1 | all |
bookworm | 1.42.0+dfsg-1 | all |
bullseye | 1.34.0+dfsg-1 | all |
upstream | 1.50.0 |
|
License: DFSG free
|
The Bioconductor module phyloseq provides a set of classes and tools to
facilitate the import, storage, analysis, and graphical display of
microbiome census data.
|
|
r-bioc-preprocesscore
BioConductor collection of pre-processing functions
|
Versions of package r-bioc-preprocesscore |
Release | Version | Architectures |
jessie | 1.26.1-1 | amd64,armel,armhf,i386 |
bookworm | 1.60.2+ds-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
experimental | 1.68.0+ds-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch | 1.36.0-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
sid | 1.66.0+ds-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.52.1-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.66.0+ds-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster | 1.44.0-1 | amd64,arm64,armhf,i386 |
upstream | 1.68.0 |
|
License: DFSG free
|
This BioConductor module contains a library of pre-processing
functions. It is imported by several other BioConductor modules.
|
|
r-bioc-purecn
copy number calling and SNV classification using targeted short read sequencing
|
Versions of package r-bioc-purecn |
Release | Version | Architectures |
trixie | 2.10.0+dfsg-1 | all |
bullseye | 1.20.0+dfsg-3 | all |
sid | 2.10.0+dfsg-1 | all |
bookworm | 2.4.0+dfsg-1 | all |
experimental | 2.12.0+dfsg-1 | all |
upstream | 2.12.0 |
|
License: DFSG free
|
This package estimates tumor purity, copy number, and loss of
heterozygosity (LOH), and classifies single nucleotide variants (SNVs) by
somatic status and clonality. PureCN is designed for targeted short read
sequencing data, integrates well with standard somatic variant detection
and copy number pipelines, and has support for tumor samples without
matching normal samples.
|
|
r-bioc-qusage
qusage: Quantitative Set Analysis for Gene Expression
|
Versions of package r-bioc-qusage |
Release | Version | Architectures |
bullseye | 2.24.0-1 | all |
experimental | 2.40.0-1 | all |
bookworm | 2.32.0-1 | all |
trixie | 2.38.0-1 | all |
sid | 2.38.0-1 | all |
upstream | 2.40.0 |
|
License: DFSG free
|
This package is an implementation the Quantitative Set
Analysis for Gene Expression (QuSAGE) method described in
(Yaari G. et al, Nucl Acids Res, 2013). This is a novel Gene
Set Enrichment-type test, which is designed to provide a
faster, more accurate, and easier to understand test for gene
expression studies. qusage accounts for inter-gene correlations
using the Variance Inflation Factor technique proposed by Wu et
al. (Nucleic Acids Res, 2012). In addition, rather than simply
evaluating the deviation from a null hypothesis with a single
number (a P value), qusage quantifies gene set activity with a
complete probability density function (PDF). From this PDF, P
values and confidence intervals can be easily extracted.
Preserving the PDF also allows for post-hoc analysis (e.g.,
pair-wise comparisons of gene set activity) while maintaining
statistical traceability. Finally, while qusage is compatible
with individual gene statistics from existing methods (e.g.,
LIMMA), a Welch-based method is implemented that is shown to
improve specificity. For questions, contact Chris Bolen
(cbolen1@gmail.com) or Steven Kleinstein
(steven.kleinstein@yale.edu)
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|
r-bioc-rbgl
R interface to the graph algorithms contained in the BOOST library
|
Versions of package r-bioc-rbgl |
Release | Version | Architectures |
experimental | 1.82.0+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
stretch | 1.50.0+dfsg1-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 1.58.1+dfsg-1 | amd64,arm64,armhf,i386 |
bullseye | 1.66.0+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.74.0+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.80.0+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
sid | 1.80.0+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
upstream | 1.82.0 |
|
License: DFSG free
|
RBGL is part of the BioConductor GNU R suite. It is a fairly extensive and
comprehensive interface to the graph algorithms contained in the BOOST C++
libraries.
|
|
r-bioc-rsamtools
GNU R binary alignment (BAM), variant call (BCF), or tabix file import
|
Versions of package r-bioc-rsamtools |
Release | Version | Architectures |
sid | 2.20.0+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
trixie | 2.20.0+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bookworm | 2.14.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 2.6.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
experimental | 2.22.0+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
buster | 1.34.1-1 | amd64,arm64,armhf,i386 |
jessie | 1.16.1-2 | amd64,armel,armhf,i386 |
stretch | 1.26.1-2 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
upstream | 2.22.0 |
|
License: DFSG free
|
This package provides an interface to the 'samtools', 'bcftools', and
'tabix' utilities for manipulating SAM (Sequence Alignment / Map),
binary variant call (BCF) and compressed indexed tab-delimited (tabix)
files.
|
|
r-bioc-rtracklayer
GNU R interface to genome browsers and their annotation tracks
|
Versions of package r-bioc-rtracklayer |
Release | Version | Architectures |
stretch | 1.34.1-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
bullseye | 1.50.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 1.42.1-2 | amd64,arm64,armhf,i386 |
jessie | 1.24.2-1 | amd64,armel,armhf,i386 |
experimental | 1.66.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
sid | 1.64.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
trixie | 1.64.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bookworm | 1.58.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
upstream | 1.66.0 |
|
License: DFSG free
|
Extensible framework for interacting with multiple genome browsers
(currently UCSC built-in) and manipulating annotation tracks in various
formats (currently GFF, BED, bedGraph, BED15, WIG, BigWig and 2bit
built-in). The user may export/import tracks to/from the supported
browsers, as well as query and modify the browser state, such as the
current viewport.
|
|
r-bioc-s4vectors
BioConductor S4 implementation of vectors and lists
|
Versions of package r-bioc-s4vectors |
Release | Version | Architectures |
experimental | 0.44.0+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 0.42.1+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 0.36.1-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 0.28.1-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
stretch | 0.12.1-2 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 0.20.1-2 | amd64,arm64,armhf,i386 |
trixie | 0.42.1+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
upstream | 0.44.0 |
|
License: DFSG free
|
The S4Vectors package defines the Vector and List virtual classes and a
set of generic functions that extend the semantic of ordinary vectors
and lists in R. Package developers can easily implement vector-like or
list-like objects as concrete subclasses of Vector or List. In addition,
a few low-level concrete subclasses of general interest (e.g. DataFrame,
Rle, and Hits) are implemented in the S4Vectors package itself (many
more are implemented in the IRanges package and in other Bioconductor
infrastructure packages).
|
|
r-bioc-savr
GNU R parse and analyze Illumina SAV files
|
Versions of package r-bioc-savr |
Release | Version | Architectures |
trixie | 1.37.0-4 | all |
sid | 1.37.0-4 | all |
stretch | 1.12.0-1 | all |
buster | 1.20.0-1 | all |
bullseye | 1.28.0-1 | all |
bookworm | 1.36.0-2 | all |
|
License: DFSG free
|
This BioConductor module enables to parse Illumina Sequence Analysis
Viewer (SAV) files, access data, and generate QC plots.
|
|
r-bioc-shortread
GNU R classes and methods for high-throughput short-read sequencing data
|
Versions of package r-bioc-shortread |
Release | Version | Architectures |
stretch | 1.32.0-1 | amd64,arm64,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
jessie | 1.22.0-1 | amd64,armel,armhf,i386 |
experimental | 1.64.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
sid | 1.62.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
trixie | 1.62.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
buster | 1.40.0-1 | amd64,arm64,armhf,i386 |
bookworm | 1.56.1-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 1.48.0-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
upstream | 1.64.0 |
|
License: DFSG free
|
This BioConductor module is a package for input, quality assessment,
manipulation and output of high-throughput sequencing data. ShortRead is
provided in the R and Bioconductor environments, allowing ready access
to additional facilities for advanced statistical analysis, data
transformation, visualization and integration with diverse genomic
resources.
|
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r-bioc-snpstats
BioConductor SnpMatrix and XSnpMatrix classes and methods
|
Versions of package r-bioc-snpstats |
Release | Version | Architectures |
stretch | 1.24.0+dfsg-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 1.32.0+dfsg-1 | amd64,arm64,armhf,i386 |
bullseye | 1.40.0+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.54.0+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
sid | 1.54.0+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
experimental | 1.56.0+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bookworm | 1.48.0+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
jessie | 1.14.0+dfsg-1 | amd64,armel,armhf,i386 |
upstream | 1.56.0 |
|
License: DFSG free
|
This BioConductor package provides R functions to work with SnpMatrix
and XSnpMatrix classes and methods.
SnpStats arose out of the need to store, and analyse, SNP genotype data
in which subjects cannot be assigned to the three possible genotypes
with certainty. This necessitated a change in the way in which data are
stored internally, although snpStats can still handle conventionally
called genotype data stored in the original snpMatrix storage mode.
snpStats currently lacks some facilities which were present in snpMatrix
(although, hopefully, the important gaps will soon be filled) but it
also includes several important new facilities.
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r-bioc-structuralvariantannotation
Variant annotations for structural variants
|
Versions of package r-bioc-structuralvariantannotation |
Release | Version | Architectures |
bookworm | 1.13.0+ds-1 | all |
experimental | 1.22.0+ds-1 | all |
trixie | 1.20.0+ds-1 | all |
sid | 1.20.0+ds-1 | all |
upstream | 1.22.0 |
|
License: DFSG free
|
StructuralVariantAnnotation contains useful helper
functions for dealing with structural variants in VCF format.
The packages contains functions for parsing VCFs from a number
of popular callers as well as functions for dealing with
breakpoints involving two separate genomic loci encoded as
GRanges objects.
|
|
r-bioc-tfbstools
GNU R Transcription Factor Binding Site (TFBS) Analysis
|
Versions of package r-bioc-tfbstools |
Release | Version | Architectures |
sid | 1.42.0+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
experimental | 1.44.0+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.28.0+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.42.0+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bookworm | 1.36.0+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 1.20.0+dfsg-1 | amd64,arm64,armhf,i386 |
upstream | 1.44.0 |
|
License: DFSG free
|
TFBSTools is a package for the analysis and manipulation of
transcription factor binding sites. It includes matrices conversion
between Position Frequency Matirx (PFM), Position Weight Matirx (PWM)
and Information Content Matrix (ICM). It can also scan putative TFBS
from sequence/alignment, query JASPAR database and provides a wrapper of
de novo motif discovery software.
|
|
r-bioc-titancna
Subclonal copy number and LOH prediction from whole genome sequencing
|
Versions of package r-bioc-titancna |
Release | Version | Architectures |
bookworm | 1.36.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.42.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
sid | 1.42.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.28.0-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
experimental | 1.44.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
upstream | 1.44.0 |
|
License: DFSG free
|
Hidden Markov model to segment and predict regions of
subclonal copy number alterations (CNA) and loss of
heterozygosity (LOH), and estimate cellular prevalence of
clonal clusters in tumour whole genome sequencing data.
|
|
r-bioc-tximport
transcript-level estimates for biological sequencing
|
Versions of package r-bioc-tximport |
Release | Version | Architectures |
sid | 1.32.0+dfsg-1 | all |
bookworm | 1.26.1+dfsg-1 | all |
trixie | 1.32.0+dfsg-1 | all |
experimental | 1.34.0+dfsg-1 | all |
bullseye | 1.18.0+dfsg-1 | all |
upstream | 1.34.0 |
|
License: DFSG free
|
Imports transcript-level abundance, estimated counts and
transcript lengths, and summarizes into matrices for use with
downstream gene-level analysis packages. Average transcript
length, weighted by sample-specific transcript abundance
estimates, is provided as a matrix which can be used as an
offset for different expression of gene-level counts.
|
|
r-bioc-variantannotation
BioConductor annotation of genetic variants
|
Versions of package r-bioc-variantannotation |
Release | Version | Architectures |
bullseye | 1.36.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 1.28.10-1 | amd64,arm64,armhf,i386 |
sid | 1.50.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
jessie | 1.10.5-1 | amd64,armel,armhf,i386 |
stretch | 1.20.2-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
trixie | 1.50.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bookworm | 1.44.1-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
experimental | 1.52.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
upstream | 1.52.0 |
|
License: DFSG free
|
This BioConductor package provides R functions to annotate variants,
compute amino acid coding changess and to predict coding outcomes.
|
|
r-bioc-xvector
BioConductor representation and manpulation of external sequences
|
Versions of package r-bioc-xvector |
Release | Version | Architectures |
jessie | 0.4.0-1 | amd64,armel,armhf,i386 |
experimental | 0.46.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
sid | 0.44.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
trixie | 0.44.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bookworm | 0.38.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 0.30.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 0.22.0-1 | amd64,arm64,armhf,i386 |
stretch | 0.14.0-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
upstream | 0.46.0 |
|
License: DFSG free
|
This BioConductor package provides memory efficient S4 classes for storing
sequences "externally" (behind an R external pointer, or on disk).
|
|
r-cran-adegenet
GNU R exploratory analysis of genetic and genomic data
|
Versions of package r-cran-adegenet |
Release | Version | Architectures |
bullseye | 2.1.3-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 2.1.1-2 | amd64,arm64,armhf,i386 |
stretch | 2.0.1-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
sid | 2.1.10-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 2.1.10-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 2.1.10-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
|
License: DFSG free
|
Toolset for the exploration of genetic and genomic data. Adegenet
provides formal (S4) classes for storing and handling various genetic
data, including genetic markers with varying ploidy and hierarchical
population structure ('genind' class), alleles counts by populations
('genpop'), and genome-wide SNP data ('genlight'). It also implements
original multivariate methods (DAPC, sPCA), graphics, statistical tests,
simulation tools, distance and similarity measures, and several spatial
methods. A range of both empirical and simulated datasets is also
provided to illustrate various methods.
|
|
r-cran-adephylo
GNU R exploratory analyses for the phylogenetic comparative method
|
Versions of package r-cran-adephylo |
Release | Version | Architectures |
trixie | 1.1-16-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch | 1.1-10-2 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 1.1-11-3 | amd64,arm64,armhf,i386 |
bullseye | 1.1-11-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.1-13-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.1-16-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
|
License: DFSG free
|
This GNU R package provides multivariate tools to analyze comparative
data, i.e. a phylogeny and some traits measured for each taxa.
|
|
r-cran-amap
Another Multidimensional Analysis Package
|
Versions of package r-cran-amap |
Release | Version | Architectures |
bookworm | 0.8-19-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 0.8-20-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 0.8-19-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 0.8-18-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
|
License: DFSG free
|
Tools for Clustering and Principal Component Analysis
(With robust methods, and parallelized functions).
|
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r-cran-biwt
biweight mean vector and covariance and correlation
|
Versions of package r-cran-biwt |
Release | Version | Architectures |
bullseye | 1.0-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.0.1-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 1.0.1-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.0.1-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
|
License: DFSG free
|
Compute multivariate location, scale, and correlation
estimates based on Tukey's biweight M-estimator.
|
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r-cran-dt
GNU R wrapper of the JavaScript library 'DataTables'
|
Versions of package r-cran-dt |
Release | Version | Architectures |
bullseye | 0.17+dfsg-3 | all |
buster-backports | 0.15+dfsg-2~bpo10+1 | all |
stretch-backports | 0.5+dfsg-1~bpo9+1 | all |
buster | 0.5+dfsg-1 | all |
sid | 0.33+dfsg-1 | all |
trixie | 0.33+dfsg-1 | all |
bookworm | 0.27+dfsg-1 | all |
|
License: DFSG free
|
Data objects in R can be rendered as HTML tables using the
JavaScript library 'DataTables' (typically via R Markdown or Shiny). The
'DataTables' library has been included in this R package. The package name
'DT' is an abbreviation of 'DataTables'.
|
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r-cran-dynamictreecut
Methods for Detection of Clusters in Hierarchical Clustering
|
Versions of package r-cran-dynamictreecut |
Release | Version | Architectures |
bullseye | 1.63-1-3 | all |
bookworm | 1.63-1-3 | all |
sid | 1.63-1-3 | all |
trixie | 1.63-1-3 | all |
|
License: DFSG free
|
Dendrograms Contains methods for detection of clusters in hierarchical
clustering dendrograms.
|
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r-cran-fastcluster
Fast hierarchical clustering routines for GNU R
|
Versions of package r-cran-fastcluster |
Release | Version | Architectures |
jessie | 1.1.13-1 | amd64,armel,armhf,i386 |
stretch | 1.1.22-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 1.1.25-2 | amd64,arm64,armhf,i386 |
bullseye | 1.1.25-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.2.3-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.2.6-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 1.2.6-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
|
License: DFSG free
|
Fastcluster implements fast hierarchical, agglomerative clustering
routines. Part of the functionality is designed as drop-in replacement
for existing routines: “linkage” in the SciPy package
“scipy.cluster.hierarchy”, “hclust” in R's “stats” package, and the
“flashClust” package. It provides the same functionality with the
benefit of a much faster implementation. Moreover, there are
memory-saving routines for clustering of vector data, which go beyond
what the existing packages provide. For information on how to install
the Python files, see the file INSTALL in the source distribution.
|
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r-cran-future.apply
apply function to elements in parallel using futures
|
Versions of package r-cran-future.apply |
Release | Version | Architectures |
bullseye | 1.7.0-1 | all |
sid | 1.11.2+dfsg-1 | all |
trixie | 1.11.2+dfsg-1 | all |
bookworm | 1.10.0+dfsg-1 | all |
upstream | 1.11.3 |
|
License: DFSG free
|
Implementations of apply(), by(), eapply(), lapply(), Map(), mapply(),
replicate(), sapply(), tapply(), and vapply() that can be resolved using
any future-supported backend, e.g. parallel on the local machine or
distributed on a compute cluster. These future_apply() functions come
with the same pros and cons as the corresponding base-R apply()
functions but with the additional feature of being able to be processed
via the future framework.
|
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r-cran-future.batchtools
Future API for Parallel and Distributed Processing
|
Versions of package r-cran-future.batchtools |
Release | Version | Architectures |
bullseye | 0.10.0+dfsg-1 | all |
bookworm | 0.12.0+dfsg-1 | all |
sid | 0.12.1+dfsg-1 | all |
trixie | 0.12.1+dfsg-1 | all |
|
License: DFSG free
|
Implementation of the Future API on top of the 'batchtools' package.
This allows you to process futures, as defined by the 'future' package,
in parallel out of the box, not only on your local machine or ad-hoc
cluster of machines, but also via high-performance compute ('HPC') job
schedulers such as 'LSF', 'OpenLava', 'Slurm', 'SGE', and 'TORQUE' / 'PBS',
e.g. 'y <- future.apply::future_lapply(files, FUN = process)'.
|
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r-cran-ica
Independent Component Analysis
|
Versions of package r-cran-ica |
Release | Version | Architectures |
trixie | 1.0-3-1 | all |
bookworm | 1.0-3-1 | all |
bullseye | 1.0-2-3 | all |
sid | 1.0-3-1 | all |
|
License: DFSG free
|
Independent Component Analysis (ICA) using various algorithms: FastICA,
Information-Maximization (Infomax), and Joint Approximate
Diagonalization of Eigenmatrices (JADE).
|
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r-cran-itertools
|
Versions of package r-cran-itertools |
Release | Version | Architectures |
bullseye | 0.1-3-3 | all |
trixie | 0.1-3-3 | all |
sid | 0.1-3-3 | all |
bookworm | 0.1-3-3 | all |
|
License: DFSG free
|
Various tools for creating iterators, many patterned after
functions in the Python itertools module, and others patterned
after functions in the 'snow' package.
|
|
r-cran-kaos
Encoding of Sequences Based on Frequency Matrix Chaos
|
Versions of package r-cran-kaos |
Release | Version | Architectures |
bullseye | 0.1.2-2 | all |
bookworm | 0.1.2-2 | all |
trixie | 0.1.2-2 | all |
sid | 0.1.2-2 | all |
|
License: DFSG free
|
Sequences encoding by using the chaos game representation.
Löchel et al. (2019) .
|
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r-cran-metap
Meta-Analysis of Significance Values
|
Versions of package r-cran-metap |
Release | Version | Architectures |
bullseye | 1.3-2 | all |
bookworm | 1.8-1 | all |
sid | 1.11-1 | all |
|
License: DFSG free
|
The canonical way to perform meta-analysis involves using effect sizes.
When they are not available this package provides a number of methods
for meta-analysis of significance values including the methods of
Edgington, Fisher, Lancaster, Stouffer, Tippett, and Wilkinson; a
number of data-sets to replicate published results; and a routine for
graphical display.
|
|
r-cran-minerva
Maximal Information-Based Nonparametric Exploration
|
Versions of package r-cran-minerva |
Release | Version | Architectures |
bookworm | 1.5.10-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.5.10-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 1.5.10-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.5.8-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
|
License: DFSG free
|
Wrapper for 'minepy' implementation of Maximal
Information-based Nonparametric Exploration statistics (MIC and
MINE family). Detailed information of the ANSI C implementation of
'minepy' can be found at http://minepy.readthedocs.io/en/latest.
|
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r-cran-natserv
GNU R 'NatureServe' Interface
|
Versions of package r-cran-natserv |
Release | Version | Architectures |
trixie | 1.0.0+dfsg-1 | all |
bookworm | 1.0.0+dfsg-1 | all |
buster | 0.3.0+dfsg-2 | all |
sid | 1.0.0+dfsg-1 | all |
bullseye | 1.0.0+dfsg-1 | all |
|
License: DFSG free
|
Interface to 'NatureServe' (http://www.natureserve.org).
Includes methods to get data, image metadata, search taxonomic names,
and make maps.
|
|
r-cran-nmf
GNU R framework to perform non-negative matrix factorization
|
Versions of package r-cran-nmf |
Release | Version | Architectures |
buster | 0.21.0-3 | amd64,arm64,armhf,i386 |
sid | 0.28-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 0.28-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 0.25-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 0.23.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
stretch | 0.20.6-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
|
License: DFSG free
|
This package implements a set of previously published algorithms and
seeding methods, and provides a framework to test, develop and plug
new/custom algorithms. Most of the built-in algorithms have been
optimized, and the main interface function provides parallel
computations on multicore machines.
|
|
r-cran-optimalcutpoints
Computing Optimal Cutpoints in Diagnostic Tests
|
Versions of package r-cran-optimalcutpoints |
Release | Version | Architectures |
bookworm | 1.1-5-1 | all |
trixie | 1.1-5-1 | all |
sid | 1.1-5-1 | all |
bullseye | 1.1-4-2 | all |
|
License: DFSG free
|
Computes optimal cutpoints for diagnostic tests or continuous markers.
Various approaches for selecting optimal cutoffs have been implemented,
including methods based on cost-benefit analysis and diagnostic test
accuracy measures (Sensitivity/Specificity, Predictive Values and
Diagnostic Likelihood Ratios). Numerical and graphical output for all
methods is easily obtained.
|
|
r-cran-parmigene
Parallel Mutual Information to establish Gene Networks
|
Versions of package r-cran-parmigene |
Release | Version | Architectures |
bookworm | 1.1.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.1.1-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 1.1.1-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.1.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
|
License: DFSG free
|
The package provides a parallel estimation of the mutual
information based on entropy estimates from k-nearest neighbors
distances and algorithms for the reconstruction of gene
regulatory networks.
|
|
r-cran-pcapp
Robust PCA by Projection Pursuit
|
Versions of package r-cran-pcapp |
Release | Version | Architectures |
trixie | 2.0-5-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 2.0-5-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 2.0-3-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 1.9-73-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
|
License: DFSG free
|
Provides functions for robust PCA by projection pursuit. The methods are
described in Croux et al. (2006) , Croux et al.
(2013) , Todorov and Filzmoser (2013)
.
|
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r-cran-proc
Display and Analyze ROC Curves
|
Versions of package r-cran-proc |
Release | Version | Architectures |
bookworm | 1.18.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 1.17.0.1-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.18.5-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 1.18.5-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
|
License: DFSG free
|
Tools for visualizing, smoothing and comparing receiver operating
characteristic (ROC curves). (Partial) area under the curve (AUC) can be
compared with statistical tests based on U-statistics or bootstrap.
Confidence intervals can be computed for (p)AUC or ROC curves.
|
|
r-cran-rann
Fast Nearest Neighbour Search Using L2 Metric
|
Versions of package r-cran-rann |
Release | Version | Architectures |
trixie | 2.6.2-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 2.6.1-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 2.6.1-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 2.6.2-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
|
License: DFSG free
|
Finds the k nearest neighbours for every point in a given dataset
in O(N log N) time using Arya and Mount's ANN library (v1.1.3). There is
support for approximate as well as exact searches, fixed radius searches
and 'bd' as well as 'kd' trees. The distance is computed using the L2
(Euclidean) metric. Please see package 'RANN.L1' for the same
functionality using the L1 (Manhattan, taxicab) metric.
|
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r-cran-rcpphnsw
R bindings for a Library for Approximate Nearest Neighbors
|
Versions of package r-cran-rcpphnsw |
Release | Version | Architectures |
sid | 0.5.0+ds-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 0.5.0+ds-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 0.3.0.9001+ds-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 0.4.1+ds-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
upstream | 0.6.0 |
|
License: DFSG free
|
'Hnswlib' is a C++ library for Approximate Nearest Neighbors. This
package provides a minimal R interface by relying on the 'Rcpp' package. See
https://github.com/nmslib/hnswlib for more on 'hnswlib'. 'hnswlib' is
released under Version 2.0 of the Apache License.
|
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r-cran-robustrankaggreg
Methods for robust rank aggregation
|
Versions of package r-cran-robustrankaggreg |
Release | Version | Architectures |
bookworm | 1.2.1-1 | all |
trixie | 1.2.1-1 | all |
sid | 1.2.1-1 | all |
bullseye | 1.1-3 | all |
|
License: DFSG free
|
Methods for aggregating ranked lists, especially lists of
genes. It implements the Robust Rank Aggregation (Kolde et. al
in preparation) and some other simple algorithms for the task.
RRA method uses a probabilistic model for aggregation that is
robust to noise and also facilitates the calculation of
significance probabilities for all the elements in the final
ranking.
|
|
r-cran-rocr
GNU R package to prepare and display ROC curves
|
Versions of package r-cran-rocr |
Release | Version | Architectures |
bookworm | 1.0-11-2 | all |
jessie | 1.0-5-1 | all |
stretch | 1.0-7-2 | all |
buster | 1.0-7-4 | all |
bullseye | 1.0-11-2 | all |
trixie | 1.0-11-3 | all |
sid | 1.0-11-3 | all |
Debtags of package r-cran-rocr: |
field | statistics |
role | shared-lib |
use | analysing, viewing |
|
License: DFSG free
|
ROC graphs, sensitivity/specificity curves, lift charts,
and precision/recall plots are popular examples of trade-off
visualizations for specific pairs of performance measures. ROCR is a
flexible tool for creating cutoff-parametrized 2D performance curves
by freely combining two from over 25 performance measures (new
performance measures can be added using a standard interface).
Curves from different cross-validation or bootstrapping runs can be
averaged by different methods, and standard deviations, standard
errors or box plots can be used to visualize the variability across
the runs. The parametrization can be visualized by printing cutoff
values at the corresponding curve positions, or by coloring the
curve according to cutoff. All components of a performance plot can
be quickly adjusted using a flexible parameter dispatching
mechanism. Despite its flexibility, ROCR is easy to use, with only
three commands and reasonable default values for all optional
parameters.
ROCR features: ROC curves, precision/recall plots, lift charts, cost
curves, custom curves by freely selecting one performance measure for the
x axis and one for the y axis, handling of data from cross-validation
or bootstrapping, curve averaging (vertically, horizontally, or by
threshold), standard error bars, box plots, curves that are color-coded
by cutoff, printing threshold values on the curve, tight integration
with Rs plotting facilities (making it easy to adjust plots or to combine
multiple plots), fully customizable, easy to use (only 3 commands).
Performance measures that ROCR knows: Accuracy, error rate, true
positive rate, false positive rate, true negative rate, false negative
rate, sensitivity, specificity, recall, positive predictive value,
negative predictive value, precision, fallout, miss, phi correlation
coefficient, Matthews correlation coefficient, mutual information, chi
square statistic, odds ratio, lift value, precision/recall F measure,
ROC convex hull, area under the ROC curve, precision/recall break-even
point, calibration error, mean cross-entropy, root mean squared error,
SAR measure, expected cost, explicit cost.
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r-cran-rook
web server interface for R
|
Versions of package r-cran-rook |
Release | Version | Architectures |
bullseye | 1.1-1+dfsg-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.2+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 1.2+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.2+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
|
License: DFSG free
|
The package provides a set of routines for R to perform as a web
server. This is used by a series of reverse dependencies to develop
interactive interfaces to statistical analyses and reports.
|
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r-cran-rsvd
Randomized Singular Value Decomposition
|
Versions of package r-cran-rsvd |
Release | Version | Architectures |
sid | 1.0.5-1 | all |
trixie | 1.0.5-1 | all |
bookworm | 1.0.5-1 | all |
bullseye | 1.0.3-3 | all |
|
License: DFSG free
|
Low-rank matrix decompositions are fundamental tools and widely used for
data analysis, dimension reduction, and data compression. Classically,
highly accurate deterministic matrix algorithms are used for this task.
However, the emergence of large-scale data has severely challenged our
computational ability to analyze big data. The concept of randomness has
been demonstrated as an effective strategy to quickly produce
approximate answers to familiar problems such as the singular value
decomposition (SVD). The rsvd package provides several randomized matrix
algorithms such as the randomized singular value decomposition (rsvd),
randomized principal component analysis (rpca), randomized robust
principal component analysis (rrpca), randomized interpolative
decomposition (rid), and the randomized CUR decomposition (rcur). In
addition several plot functions are provided. The methods are discussed
in detail by Erichson et al. (2016) .
|
|
r-cran-shazam
Immunoglobulin Somatic Hypermutation Analysis
|
Versions of package r-cran-shazam |
Release | Version | Architectures |
buster | 0.1.11-1 | all |
trixie | 1.2.0-1 | all |
sid | 1.2.0-1 | all |
bookworm | 1.1.2-1 | all |
bullseye | 1.0.2-1 | all |
|
License: DFSG free
|
Provides a computational framework for Bayesian estimation of
antigen-driven selection in immunoglobulin (Ig) sequences, providing an
intuitive means of analyzing selection by quantifying the degree of
selective pressure. Also provides tools to profile mutations in Ig
sequences, build models of somatic hypermutation (SHM) in Ig sequences,
and make model-dependent distance comparisons of Ig repertoires.
SHazaM is part of the Immcantation analysis framework for Adaptive
Immune Receptor Repertoire sequencing (AIRR-seq) and provides tools for
advanced analysis of somatic hypermutation (SHM) in immunoglobulin (Ig)
sequences. Shazam focuses on the following analysis topics:
- Quantification of mutational load
SHazaM includes methods for determine the rate of observed and
expected mutations under various criteria. Mutational profiling
criteria include rates under SHM targeting models, mutations specific
to CDR and FWR regions, and physicochemical property dependent
substitution rates.
- Statistical models of SHM targeting patterns
Models of SHM may be divided into two independent components:
1) a mutability model that defines where mutations occur and
2) a nucleotide substitution model that defines the resulting mutation.
Collectively these two components define an SHM targeting
model. SHazaM provides empirically derived SHM 5-mer context mutation
models for both humans and mice, as well tools to build SHM targeting
models from data.
- Analysis of selection pressure using BASELINe
The Bayesian Estimation of Antigen-driven Selection in Ig Sequences
(BASELINe) method is a novel method for quantifying antigen-driven
selection in high-throughput Ig sequence data. BASELINe uses SHM
targeting models can be used to estimate the null distribution of
expected mutation frequencies, and provide measures of selection
pressure informed by known AID targeting biases.
- Model-dependent distance calculations
SHazaM provides methods to compute evolutionary distances between
sequences or set of sequences based on SHM targeting models. This
information is particularly useful in understanding and defining
clonal relationships.
|
|
r-cran-sitmo
GNU R parallel pseudo random number generator 'sitmo' header files
|
Versions of package r-cran-sitmo |
Release | Version | Architectures |
bookworm | 2.0.2-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 2.0.2-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 2.0.2-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 2.0.1-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
|
License: DFSG free
|
Provided within are two high quality and fast PPRNGs that may be
used in an 'OpenMP' parallel environment. In addition, there is a generator
for one dimensional low-discrepancy sequence. The objective of this library
to consolidate the distribution of the 'sitmo' (C++98 & C++11), 'threefry' and
'vandercorput' (C++11-only) engines on CRAN by enabling others to link to the
header files inside of 'sitmo' instead of including a copy of each engine
within their individual package. Lastly, the package contains example
implementations using the 'sitmo' package and three accompanying vignette that
provide additional information.
|
|
r-cran-venndiagram
Generate High-Resolution Venn and Euler Plots
|
Versions of package r-cran-venndiagram |
Release | Version | Architectures |
sid | 1.7.3-1 | all |
trixie | 1.7.3-1 | all |
bookworm | 1.7.3-1 | all |
bullseye | 1.6.20-3 | all |
|
License: DFSG free
|
A set of functions to generate high-resolution Venn and Euler plots.
Includes handling for several special cases, including two-case scaling,
and extensive customization of plot shape and structure.
|
|
ruby-rgfa
parse, edit and write GFA format graphs in Ruby
|
Versions of package ruby-rgfa |
Release | Version | Architectures |
buster | 1.3.1+dfsg-1 | all |
stretch | 1.3.1-1 | all |
bullseye | 1.3.1+dfsg-2 | all |
bookworm | 1.3.1+dfsg-2 | all |
trixie | 1.3.1+dfsg-2 | all |
sid | 1.3.1+dfsg-2 | all |
|
License: DFSG free
|
The Graphical Fragment Assembly (GFA) format is a proposed file format
to describe the product of a genome sequence assembly process.
rgfa implements the proposed specifications for the GFA format
described under https://github.com/pmelsted/GFA-spec/blob/master/GFA-spec.md
as closely as possible.
The library allows one to create an RGFA object from a file in the GFA format
or from scratch, to enumerate the graph elements (segments, links,
containments, paths and header lines), to traverse the graph (by
traversing all links outgoing from or incoming to a segment), to search for
elements (e.g. which links connect two segments) and to manipulate the
graph (e.g. to eliminate a link or a segment or to duplicate a segment
distributing the read counts evenly on the copies).
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|
Debian packages in contrib or non-free
python3-bcbio
library for analysing high-throughput sequencing data
|
Versions of package python3-bcbio |
Release | Version | Architectures |
buster | 1.1.2-3 | all |
sid | 1.2.9-2 (contrib) | all |
bookworm | 1.2.9-2 (contrib) | all |
bullseye | 1.2.5-1 (contrib) | all |
|
License: DFSG free, but needs non-free components
|
This package installs the Python 3 libraries of the bcbio-nextgen
toolkit implementing best-practice pipelines for fully automated high
throughput sequencing analysis.
A high-level configuration file specifies inputs and analysis parameters
to drive a parallel pipeline that handles distributed execution,
idempotent processing restarts and safe transactional steps. The project
contributes a shared community resource that handles the data processing
component of sequencing analysis, providing researchers with more time
to focus on the downstream biology.
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python3-seqcluster
analysis of small RNA in NGS data
|
Versions of package python3-seqcluster |
Release | Version | Architectures |
bullseye | 1.2.7+ds-1 (contrib) | all |
sid | 1.2.9+ds-4 (contrib) | all |
trixie | 1.2.9+ds-4 (contrib) | all |
bookworm | 1.2.9+ds-3 (contrib) | all |
|
License: DFSG free, but needs non-free components
|
Identifies small RNA sequences of all sorts in RNA sequencing data. This is
especially helpful for the identification of RNA that is neither coding nor
belonging to the already well-established group of miRNA, towards many tools
feel constrained to.
This package provides the Python module. For executables see the package
'seqcluster'.
|
vdjtools
framework for post-analysis of B/T cell repertoires
|
Versions of package vdjtools |
Release | Version | Architectures |
bookworm | 1.2.1+git20190311+repack-1 (non-free) | all |
bullseye | 1.2.1+git20190311-5 (non-free) | all |
trixie | 1.2.1+git20190311+repack-2 (non-free) | all |
sid | 1.2.1+git20190311+repack-2 (non-free) | all |
|
License: non-free
|
VDJtools is an open-source Java/Groovy-based framework designed
to facilitate analysis of immune repertoire sequencing (RepSeq)
data. VDJtools computes a wide set of statistics and is able to perform
various forms of cross-sample analysis. Both comprehensive tabular
output and publication-ready plots are provided.
The main aims of the VDJtools Project are:
- To ensure consistency between post-analysis methods and results
- To save the time of bioinformaticians analyzing RepSeq data
- To create an API framework facilitating development of new RepSeq
analysis applications
- To provide a simple enough command line tool so it could be used by
immunologists and biologists with little computational background
Please cite:
M Shugay, D.V. Bagaev, M.A. Turchaninova, D.A. Bolotin, O.V. Britanova, E.V. Putintseva, M.V. Pogorelyy, V.I. Nazarov VI, I.V. Zvyagin, V.I. Kirgizova, K.I. Kirgizov, E.V. Skorobogatova and D.M. Chudakov:
VDJtools: Unifying Post-analysis of T Cell Receptor Repertoires.
(PubMed,eprint)
PLoS Comput Biol.
11(11):e1004503
(2015)
|
Packaging has started and developers might try the packaging code in VCS
libatomicqueue-dev
devel files for C++ atomic_queue library
|
Versions of package libatomicqueue-dev |
Release | Version | Architectures |
VCS | 0.0+git20200609.b6da4a9-1 | all |
|
License: MIT
Debian package not available
Version: 0.0+git20200609.b6da4a9-1
|
C++11 multiple-producer-multiple-consumer lockless queues based on
circular buffer with std::atomic. The main design principle these
queues follow is simplicity: the bare minimum of atomic operations,
fixed size buffer, value semantics.
The circular buffer side-steps the memory reclamation problem inherent
in linked-list based queues for the price of fixed buffer size. See
Effective memory reclamation for lock-free data structures in C++
for more details.
These qualities are also limitations:
- The maximum queue size must be set at compile time or construction time.
- There are no OS-blocking push/pop functions.
Nevertheless, ultra-low-latency applications need just that and nothing
more. The simplicity pays off, see the throughput and latency benchmarks.
Available containers are:
- AtomicQueue - a fixed size ring-buffer for atomic elements.
- OptimistAtomicQueue - a faster fixed size ring-buffer for atomic
elements which busy-waits when empty or full.
- AtomicQueue2 - a fixed size ring-buffer for non-atomic elements.
- OptimistAtomicQueue2 - a faster fixed size ring-buffer for non-atomic
elements which busy-waits when empty or full.
These containers have corresponding AtomicQueueB, OptimistAtomicQueueB,
AtomicQueueB2, OptimistAtomicQueueB2 versions where the buffer size is
specified as an argument to the constructor.
|
libfast-perl
FAST Analysis of Sequences Toolbox
|
Versions of package libfast-perl |
Release | Version | Architectures |
VCS | 1.7+dfsg-1 | all |
|
License: Artistic or GPL-1+
Debian package not available
Version: 1.7+dfsg-1
|
The FAST Analysis of Sequences Toolbox (FAST) is a set of Unix tools (for
example fasgrep, fascut, fashead and fastr) for sequence bioinformatics
modeled after the Unix textutils (such as grep, cut, head, tr, etc). FAST
workflows are designed for "inline" (serial) processing of flatfile
biological sequence record databases per-sequence, rather than per-line,
through Unix command pipelines. The default data exchange format is
multifasta (specifically, a restriction of BioPerl FastA format). FAST
tools expose the power of Perl and BioPerl for sequence analysis to
non-programmers in an easy-to-learn command-line paradigm.
You do not need to know Perl or BioPerl to use FAST.
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libforester-java
Libraries for evolutionary biology and comparative genomics research
|
Versions of package libforester-java |
Release | Version | Architectures |
VCS | 0.0+20180205-1 | all |
|
License: LGPL 2.1+
Debian package not available
Version: 0.0+20180205-1
|
Forester is a library of Java software for phylogenomics
and evolutionary biology research. It can be used to read or
write phylogenetic trees, export trees to graphics file,...
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libnexml-java
|
Versions of package libnexml-java |
Release | Version | Architectures |
VCS | 0.1+dfsg-1 | all |
|
License: FIXME
Debian package not available
Version: 0.1+dfsg-1
|
Java NeXML libraries and tools
- model: the DOM-based core java 5 NeXML reading/writing API, inside
src/main/java as well as JUnit tests inside src/tets/java. The API
consists of interfaces in the org.nexml.model package and
implementations thereof in the org.nexml.model.impl package.
- mesquite_module: NeXML import/export functionality for mesquite. This
subfolder structure contains classess (inside src/main/java) that
depend on the org.nexml.model.* architecture. In addition there are
resource files: properties files that map between certain annotation
namespaces and/or predicates as encountered in NeXML files, and the
Java handler classes that are to be dynamically loaded to operate on
them; and a default Tree Style Sheet (TSS) file for marking up tree
visualizations.
- validator: Xerces-J-based XML validator (written by Terri Liebowitz
of the San Diego Supercomputing Center, with modifications by Mark
Holder) and a ValidateNeXML class that does essentially the same
thing, but more tailored to NeXML specifically.
- transformer: class that transforms NeXML documents into CDAO
documents using the xslt stylesheets found in $NEXML_ROOT/xslt.
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python3-compclust
explore and quantify relationships between clustering results
|
Versions of package python3-compclust |
Release | Version | Architectures |
VCS | 1.3+dfsg-1 | all |
|
License: MLX
Debian package not available
Version: 1.3+dfsg-1
|
CompClust is a python package written using the pyMLX and IPlot APIs. It provides
software tools to explore and quantify relationships between clustering results. Its
development has been largely built around needs of microarray data analysis but could
be easily used in other domains.
Briefly pyMLX provides for efficient and convenient execution of many clustering
algorithms using a extendable library of algorithms. It also provides many-to-many
linkages between data features and annotations (such as cluster labels, gene names,
gene ontology information, etc.) These linkages persist through varied data
manipulations. IPlot provides an abstraction of the plotting process in which any
arbitrary feature or derived feature of the data can be projected onto any feature
of the plot, including the X,Y coordinates of points, marker symbol, marker size,
maker/line color, etc. These plots are intrinsically linked to the dataset, the
View and the Labeling classes found within pyMLX.
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python3-consensuscore2
generate consensus sequences for PacBio data -- Python 3
|
Versions of package python3-consensuscore2 |
Release | Version | Architectures |
VCS | 0.13.0+20160719-2 | all |
|
License: PacBio-BSD-3-Clause
Debian package not available
Version: 0.13.0+20160719-2
|
ConsensusCore2 embodies core C++ routines underlying the Arrow HMM
algorithm for PacBio multi-sequence consensus. Arrow is the successor
to the Quiver model---a CRF model that was embodied in the
ConsensusCore C++ library. Compared to Quiver, the Arrow model is more
statistically principled and easier and more robust to train.
This package installs the library for Python 3.
|
python3-galaxy-lib
Subset of Galaxy core code base designed to be used
|
Versions of package python3-galaxy-lib |
Release | Version | Architectures |
VCS | 19.5.2-1 | all |
|
License: AFL
Debian package not available
Version: 19.5.2-1
|
A small subset of the Galaxy project for reuse outside the core.
The Galaxy software framework enables researchers without informatics
expertise to perform computational analyses through the web. A user interacts
with Galaxy through the web by uploading and analyzing the data. Galaxy
interacts with underlying computational infrastructure (servers that run the
analyses and disks that store the data) without exposing it to the user.
|
python3-misopy
Mixture of Isoforms model for RNA-Seq isoform quantitation (Python 3)
|
Versions of package python3-misopy |
Release | Version | Architectures |
VCS | 0.5.4+dfsg-1 | all |
|
License: GPL-2.0+
Debian package not available
Version: 0.5.4+dfsg-1
|
MISO (Mixture of Isoforms) is a probabilistic framework that quantitates
the expression level of alternatively spliced genes from RNA-Seq
data, and identifies differentially regulated isoforms or exons across
samples. By modeling the generative process by which reads are produced
from isoforms in RNA-Seq, the MISO model uses Bayesian inference to
compute the probability that a read originated from a particular isoform.
MISO uses the inferred assignment of reads to isoforms to quantitate the
abundances of the underlying set of alternative mRNA isoforms. Confidence
intervals over estimates can be obtained, which quantify the reliability
of the estimates.
This is the Python 3 module.
|
python3-scanpy
Single-Cell Analysis in Python
|
Versions of package python3-scanpy |
Release | Version | Architectures |
VCS | 1.9.6-1 | all |
|
License: BSD-3-Clause
Debian package not available
Version: 1.9.6-1
|
Scanpy is a scalable toolkit for analyzing single-cell gene expression
data built jointly with anndata. It includes preprocessing,
visualization, clustering, trajectory inference and differential
expression testing. The Python-based implementation efficiently deals
with datasets of more than one million cells.
|
q2-composition
QIIME2 plugin for Compositional statistics
|
Versions of package q2-composition |
Release | Version | Architectures |
VCS | 2021.8.0+ds-1 | all |
|
License: BSD-3-clause
Debian package not available
Version: 2021.8.0+ds-1
|
QIIME 2 is a powerful, extensible, and decentralized microbiome analysis
package with a focus on data and analysis transparency. QIIME 2 enables
researchers to start an analysis with raw DNA sequence data and finish with
publication-quality figures and statistical results.
Key features:
- Integrated and automatic tracking of data provenance
- Semantic type system
- Plugin system for extending microbiome analysis functionality
- Support for multiple types of user interfaces (e.g. API, command line,
graphical)
QIIME 2 is a complete redesign and rewrite of the QIIME 1 microbiome analysis
pipeline. QIIME 2 will address many of the limitations of QIIME 1, while
retaining the features that makes QIIME 1 a powerful and widely-used analysis
pipeline.
QIIME 2 currently supports an initial end-to-end microbiome analysis pipeline.
New functionality will regularly become available through QIIME 2 plugins. You
can view a list of plugins that are currently available on the QIIME 2 plugin
availability page. The future plugins page lists plugins that are being
developed.
Please cite:
Evan Bolyen, Jai Ram Rideout, Matthew R Dillon, Nicholas A Bokulich, Christian Abnet, Gabriel A Al-Ghalith, Harriet Alexander, Eric J Alm, Manimozhiyan Arumugam, Francesco Asnicar, Yang Bai, Jordan E Bisanz, Kyle Bittinger, Asker Brejnrod, Colin J Brislawn, C Titus Brown, Benjamin J Callahan, Andrés Mauricio Caraballo-Rodríguez, John Chase, Emily Cope, Ricardo Da Silva, Pieter C Dorrestein, Gavin M Douglas, Daniel M Durall, Claire Duvallet, Christian F Edwardson, Madeleine Ernst, Mehrbod Estaki, Jennifer Fouquier, Julia M Gauglitz, Deanna L Gibson, Antonio Gonzalez, Kestrel Gorlick, Jiarong Guo, Benjamin Hillmann, Susan Holmes, Hannes Holste, Curtis Huttenhower, Gavin Huttley, Stefan Janssen, Alan K Jarmusch, Lingjing Jiang, Benjamin Kaehler, Kyo Bin Kang, Christopher R Keefe, Paul Keim, Scott T Kelley, Dan Knights, Irina Koester, Tomasz Kosciolek, Jorden Kreps, Morgan GI Langille, Joslynn Lee, Ruth Ley, Yong-Xin Liu, Erikka Loftfield, Catherine Lozupone, Massoud Maher, Clarisse Marotz, Bryan D Martin, Daniel McDonald, Lauren J McIver, Alexey V Melnik, Jessica L Metcalf, Sydney C Morgan, Jamie Morton, Ahmad Turan Naimey, Jose A Navas-Molina, Louis Felix Nothias, Stephanie B Orchanian, Talima Pearson, Samuel L Peoples, Daniel Petras, Mary Lai Preuss, Elmar Pruesse, Lasse Buur Rasmussen, Adam Rivers, Michael S Robeson, Patrick Rosenthal, Nicola Segata, Michael Shaffer, Arron Shiffer, Rashmi Sinha, Se Jin Song, John R Spear, Austin D Swafford, Luke R Thompson, Pedro J Torres, Pauline Trinh, Anupriya Tripathi, Peter J Turnbaugh, Sabah Ul-Hasan, Justin JJ van der Hooft, Fernando Vargas, Yoshiki Vázquez-Baeza, Emily Vogtmann, Max von Hippel, William Walters, Yunhu Wan, Mingxun Wang, Jonathan Warren, Kyle C Weber, Chase HD Williamson, Amy D Willis, Zhenjiang Zech Xu, Jesse R Zaneveld, Yilong Zhang, Qiyun Zhu, Rob Knight and J Gregory Caporaso:
Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2.
(eprint)
Nature Biotechnology
37
(2019)
|
q2-deblur
QIIME2 plugin to wrap the Deblur software for sequence quality control
|
Versions of package q2-deblur |
Release | Version | Architectures |
VCS | 2023.9.0-1 | all |
|
License: BSD-3-clause
Debian package not available
Version: 2023.9.0-1
|
QIIME 2 is a powerful, extensible, and decentralized microbiome analysis
package with a focus on data and analysis transparency. QIIME 2 enables
researchers to start an analysis with raw DNA sequence data and finish with
publication-quality figures and statistical results.
Key features:
- Integrated and automatic tracking of data provenance
- Semantic type system
- Plugin system for extending microbiome analysis functionality
- Support for multiple types of user interfaces (e.g. API, command line,
graphical)
QIIME 2 is a complete redesign and rewrite of the QIIME 1 microbiome analysis
pipeline. QIIME 2 will address many of the limitations of QIIME 1, while
retaining the features that makes QIIME 1 a powerful and widely-used analysis
pipeline.
QIIME 2 currently supports an initial end-to-end microbiome analysis pipeline.
New functionality will regularly become available through QIIME 2 plugins. You
can view a list of plugins that are currently available on the QIIME 2 plugin
availability page. The future plugins page lists plugins that are being
developed.
Please cite:
Amnon Amir, Daniel McDonald, Jose A. Navas-Molina, Evguenia Kopylova, James T. Morton, Zhenjiang Zech Xu, Eric P. Kightley, Luke R. Thompson, Embriette R. Hyde, Antonio Gonzalez and Rob Knight:
Deblur Rapidly Resolves Single-Nucleotide Community Sequence Patterns.
(PubMed,eprint)
mSystems
2
(2017)
|
q2-diversity
QIIME2 plugin for core diversity analysis
|
Versions of package q2-diversity |
Release | Version | Architectures |
VCS | 2021.8.0-1 | all |
|
License: BSD-3-clause
Debian package not available
Version: 2021.8.0-1
|
QIIME 2 is a powerful, extensible, and decentralized microbiome analysis
package with a focus on data and analysis transparency. QIIME 2 enables
researchers to start an analysis with raw DNA sequence data and finish with
publication-quality figures and statistical results. QIIME 2
currently supports an initial end-to-end microbiome analysis pipeline.
Functionality is made available through QIIME 2 plugins.
This plugin provides the means to statistically assess the diversity
of microbiota. This has direct clinical interest, since with whatever
we eat or have antibiotics applied, the survival of different groups
of bacteria/yeasts will be affected. From these relative abundances of
strains that constribute the microbiome, most prominently, comparisons
within a group of samples (or an individual) determines the alpha
diversity and between (groups of) samples the beta diversity is
inspected.
This package is key to most workflows in qiime.
Please cite:
Evan Bolyen, Jai Ram Rideout, Matthew R Dillon, Nicholas A Bokulich, Christian Abnet, Gabriel A Al-Ghalith, Harriet Alexander, Eric J Alm, Manimozhiyan Arumugam, Francesco Asnicar, Yang Bai, Jordan E Bisanz, Kyle Bittinger, Asker Brejnrod, Colin J Brislawn, C Titus Brown, Benjamin J Callahan, Andrés Mauricio Caraballo-Rodríguez, John Chase, Emily Cope, Ricardo Da Silva, Pieter C Dorrestein, Gavin M Douglas, Daniel M Durall, Claire Duvallet, Christian F Edwardson, Madeleine Ernst, Mehrbod Estaki, Jennifer Fouquier, Julia M Gauglitz, Deanna L Gibson, Antonio Gonzalez, Kestrel Gorlick, Jiarong Guo, Benjamin Hillmann, Susan Holmes, Hannes Holste, Curtis Huttenhower, Gavin Huttley, Stefan Janssen, Alan K Jarmusch, Lingjing Jiang, Benjamin Kaehler, Kyo Bin Kang, Christopher R Keefe, Paul Keim, Scott T Kelley, Dan Knights, Irina Koester, Tomasz Kosciolek, Jorden Kreps, Morgan GI Langille, Joslynn Lee, Ruth Ley, Yong-Xin Liu, Erikka Loftfield, Catherine Lozupone, Massoud Maher, Clarisse Marotz, Bryan D Martin, Daniel McDonald, Lauren J McIver, Alexey V Melnik, Jessica L Metcalf, Sydney C Morgan, Jamie Morton, Ahmad Turan Naimey, Jose A Navas-Molina, Louis Felix Nothias, Stephanie B Orchanian, Talima Pearson, Samuel L Peoples, Daniel Petras, Mary Lai Preuss, Elmar Pruesse, Lasse Buur Rasmussen, Adam Rivers, Michael S Robeson, Patrick Rosenthal, Nicola Segata, Michael Shaffer, Arron Shiffer, Rashmi Sinha, Se Jin Song, John R Spear, Austin D Swafford, Luke R Thompson, Pedro J Torres, Pauline Trinh, Anupriya Tripathi, Peter J Turnbaugh, Sabah Ul-Hasan, Justin JJ van der Hooft, Fernando Vargas, Yoshiki Vázquez-Baeza, Emily Vogtmann, Max von Hippel, William Walters, Yunhu Wan, Mingxun Wang, Jonathan Warren, Kyle C Weber, Chase HD Williamson, Amy D Willis, Zhenjiang Zech Xu, Jesse R Zaneveld, Yilong Zhang, Qiyun Zhu, Rob Knight and J Gregory Caporaso:
Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2.
(eprint)
Nature Biotechnology
37
(2019)
|
q2-gneiss
QIIME2 plugin for Compositional Data Analysis and Visualization
|
Versions of package q2-gneiss |
Release | Version | Architectures |
VCS | 2020.11.1-1 | all |
|
License: BSD-3-clause
Debian package not available
Version: 2020.11.1-1
|
QIIME 2 is a powerful, extensible, and decentralized microbiome analysis
package with a focus on data and analysis transparency. QIIME 2 enables
researchers to start an analysis with raw DNA sequence data and finish with
publication-quality figures and statistical results.
Key features:
- Integrated and automatic tracking of data provenance
- Semantic type system
- Plugin system for extending microbiome analysis functionality
- Support for multiple types of user interfaces (e.g. API, command line,
graphical)
QIIME 2 is a complete redesign and rewrite of the QIIME 1 microbiome analysis
pipeline. QIIME 2 will address many of the limitations of QIIME 1, while
retaining the features that makes QIIME 1 a powerful and widely-used analysis
pipeline.
QIIME 2 currently supports an initial end-to-end microbiome analysis pipeline.
New functionality will regularly become available through QIIME 2 plugins. You
can view a list of plugins that are currently available on the QIIME 2 plugin
availability page. The future plugins page lists plugins that are being
developed.
Please cite:
Evan Bolyen, Jai Ram Rideout, Matthew R Dillon, Nicholas A Bokulich, Christian Abnet, Gabriel A Al-Ghalith, Harriet Alexander, Eric J Alm, Manimozhiyan Arumugam, Francesco Asnicar, Yang Bai, Jordan E Bisanz, Kyle Bittinger, Asker Brejnrod, Colin J Brislawn, C Titus Brown, Benjamin J Callahan, Andrés Mauricio Caraballo-Rodríguez, John Chase, Emily Cope, Ricardo Da Silva, Pieter C Dorrestein, Gavin M Douglas, Daniel M Durall, Claire Duvallet, Christian F Edwardson, Madeleine Ernst, Mehrbod Estaki, Jennifer Fouquier, Julia M Gauglitz, Deanna L Gibson, Antonio Gonzalez, Kestrel Gorlick, Jiarong Guo, Benjamin Hillmann, Susan Holmes, Hannes Holste, Curtis Huttenhower, Gavin Huttley, Stefan Janssen, Alan K Jarmusch, Lingjing Jiang, Benjamin Kaehler, Kyo Bin Kang, Christopher R Keefe, Paul Keim, Scott T Kelley, Dan Knights, Irina Koester, Tomasz Kosciolek, Jorden Kreps, Morgan GI Langille, Joslynn Lee, Ruth Ley, Yong-Xin Liu, Erikka Loftfield, Catherine Lozupone, Massoud Maher, Clarisse Marotz, Bryan D Martin, Daniel McDonald, Lauren J McIver, Alexey V Melnik, Jessica L Metcalf, Sydney C Morgan, Jamie Morton, Ahmad Turan Naimey, Jose A Navas-Molina, Louis Felix Nothias, Stephanie B Orchanian, Talima Pearson, Samuel L Peoples, Daniel Petras, Mary Lai Preuss, Elmar Pruesse, Lasse Buur Rasmussen, Adam Rivers, Michael S Robeson, Patrick Rosenthal, Nicola Segata, Michael Shaffer, Arron Shiffer, Rashmi Sinha, Se Jin Song, John R Spear, Austin D Swafford, Luke R Thompson, Pedro J Torres, Pauline Trinh, Anupriya Tripathi, Peter J Turnbaugh, Sabah Ul-Hasan, Justin JJ van der Hooft, Fernando Vargas, Yoshiki Vázquez-Baeza, Emily Vogtmann, Max von Hippel, William Walters, Yunhu Wan, Mingxun Wang, Jonathan Warren, Kyle C Weber, Chase HD Williamson, Amy D Willis, Zhenjiang Zech Xu, Jesse R Zaneveld, Yilong Zhang, Qiyun Zhu, Rob Knight and J Gregory Caporaso:
Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2.
(eprint)
Nature Biotechnology
37
(2019)
|
q2-longitudinal
QIIME2 plugin for longitudinal studies and paired comparisons
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Versions of package q2-longitudinal |
Release | Version | Architectures |
VCS | 2023.9.1+ds-1 | all |
|
License: BSD-3-clause
Debian package not available
Version: 2023.9.1+ds-1
|
QIIME 2 is a powerful, extensible, and decentralized microbiome analysis
package with a focus on data and analysis transparency. QIIME 2 enables
researchers to start an analysis with raw DNA sequence data and finish with
publication-quality figures and statistical results.
Key features:
- Integrated and automatic tracking of data provenance
- Semantic type system
- Plugin system for extending microbiome analysis functionality
- Support for multiple types of user interfaces (e.g. API, command line,
graphical)
QIIME 2 is a complete redesign and rewrite of the QIIME 1 microbiome analysis
pipeline. QIIME 2 will address many of the limitations of QIIME 1, while
retaining the features that makes QIIME 1 a powerful and widely-used analysis
pipeline.
QIIME 2 currently supports an initial end-to-end microbiome analysis pipeline.
New functionality will regularly become available through QIIME 2 plugins. You
can view a list of plugins that are currently available on the QIIME 2 plugin
availability page. The future plugins page lists plugins that are being
developed.
Please cite:
Evan Bolyen, Jai Ram Rideout, Matthew R Dillon, Nicholas A Bokulich, Christian Abnet, Gabriel A Al-Ghalith, Harriet Alexander, Eric J Alm, Manimozhiyan Arumugam, Francesco Asnicar, Yang Bai, Jordan E Bisanz, Kyle Bittinger, Asker Brejnrod, Colin J Brislawn, C Titus Brown, Benjamin J Callahan, Andrés Mauricio Caraballo-Rodríguez, John Chase, Emily Cope, Ricardo Da Silva, Pieter C Dorrestein, Gavin M Douglas, Daniel M Durall, Claire Duvallet, Christian F Edwardson, Madeleine Ernst, Mehrbod Estaki, Jennifer Fouquier, Julia M Gauglitz, Deanna L Gibson, Antonio Gonzalez, Kestrel Gorlick, Jiarong Guo, Benjamin Hillmann, Susan Holmes, Hannes Holste, Curtis Huttenhower, Gavin Huttley, Stefan Janssen, Alan K Jarmusch, Lingjing Jiang, Benjamin Kaehler, Kyo Bin Kang, Christopher R Keefe, Paul Keim, Scott T Kelley, Dan Knights, Irina Koester, Tomasz Kosciolek, Jorden Kreps, Morgan GI Langille, Joslynn Lee, Ruth Ley, Yong-Xin Liu, Erikka Loftfield, Catherine Lozupone, Massoud Maher, Clarisse Marotz, Bryan D Martin, Daniel McDonald, Lauren J McIver, Alexey V Melnik, Jessica L Metcalf, Sydney C Morgan, Jamie Morton, Ahmad Turan Naimey, Jose A Navas-Molina, Louis Felix Nothias, Stephanie B Orchanian, Talima Pearson, Samuel L Peoples, Daniel Petras, Mary Lai Preuss, Elmar Pruesse, Lasse Buur Rasmussen, Adam Rivers, Michael S Robeson, Patrick Rosenthal, Nicola Segata, Michael Shaffer, Arron Shiffer, Rashmi Sinha, Se Jin Song, John R Spear, Austin D Swafford, Luke R Thompson, Pedro J Torres, Pauline Trinh, Anupriya Tripathi, Peter J Turnbaugh, Sabah Ul-Hasan, Justin JJ van der Hooft, Fernando Vargas, Yoshiki Vázquez-Baeza, Emily Vogtmann, Max von Hippel, William Walters, Yunhu Wan, Mingxun Wang, Jonathan Warren, Kyle C Weber, Chase HD Williamson, Amy D Willis, Zhenjiang Zech Xu, Jesse R Zaneveld, Yilong Zhang, Qiyun Zhu, Rob Knight and J Gregory Caporaso:
Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2.
(eprint)
Nature Biotechnology
37
(2019)
|
q2-vsearch
QIIME 2 plugin for clustering and dereplicating with vsearch
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Versions of package q2-vsearch |
Release | Version | Architectures |
VCS | 2023.9.0-1 | all |
|
License: BSD-3-clause
Debian package not available
Version: 2023.9.0-1
|
A QIIME 2 plugin that wraps the vsearch application, and provides
methods for clustering and dereplicating features and sequences.
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r-bioc-bridgedbr
identifier mapping between biological databases
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Versions of package r-bioc-bridgedbr |
Release | Version | Architectures |
VCS | 2.4.0+dfsg-1 | all |
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License: MIT
Debian package not available
Version: 2.4.0+dfsg-1
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Use BridgeDb functions and load identifier mapping
databases in R.
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r-cran-drinsight
drug repurposing on transcriptome sequencing data
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Versions of package r-cran-drinsight |
Release | Version | Architectures |
VCS | 0.1.1-1 | all |
|
License: GPL-2
Debian package not available
Version: 0.1.1-1
|
The package's name is an acronym for "Drug Repurposing Integration and
Systematic Investigation of Genomic High Throughput Data", which pretty
much describes it: This is a connectivity mapping-based drug repurposing
tool that identifies drugs that can potentially reverse query disease
phenotype or have similar functions with query drugs.
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r-other-apmswapp
GNU R Pre- and Postprocessing For Affinity Purification Mass Spectrometry
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Versions of package r-other-apmswapp |
Release | Version | Architectures |
VCS | 1.0-1 | all |
|
License: <license>
Debian package not available
Version: 1.0-1
|
The reliable detection of protein-protein-interactions by affinity
purification mass spectrometry (AP-MS) is a crucial stepping stone for
the understanding of biological processes. The main challenge in a
typical AP-MS experiment is to separate true interaction proteins from
contaminants by contrasting counts of proteins binding to specific baits
with counts of negative controls.
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No known packages available
bioclipse
platform for chemo- and bioinformatics based on Eclipse
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|
License: Eclipse Public License (EPL) + exception
Debian package not available
|
The Bioclipse project is aimed at creating a Java-based, open source,
visual platform for chemo- and bioinformatics based on the Eclipse
Rich Client Platform (RCP). Bioclipse, as any RCP application, is based
on a plugin architecture that inherits basic functionality and visual
interfaces from Eclipse, such as help system, software updates,
preferences, cross-platform deployment etc.
Bioclipse will provide functionality for chemo- and bioinformatics,
and extension points that easily can be extended by plugins to provide
added functionality. The first version of Bioclipse includes a
CDK-plugin (bc_cdk) to provide a chemoinformatic backend, a Jmol-plugin
(bc_jmol) for 3D-visualization and a general logging plugin. To stay
updated on upcoming features, releases, new plugins etc, please register
for the mailing list bioclipse-announce. The development is best
followed on the Bioclipse Wiki where we document the progress and
ideas of the development on a daily basis.
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octace-bioinfo
Bioinformatics manipulation for Octave
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License: GPL-2+
Debian package not available
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aa2int:
Convert amino acid characters into integers.
aminolookup:
Convert between amino acid representations.
cleave:
Cleave a peptide SEQUENCE using the PATTERN at the POSITION relative to the pattern.
int2aa
Convert amino acid integers into characters.
seqreverse
Reverse a nucleotide sequence.
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