Summary
Covid-19
This task exists only for tagging COVID-19 relevant cases
The Debian Med team intends to take part at the
COVID-19 Biohackathon (April 5-11, 2020)
This task was created only for the purpose to list relevant packages.
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 Covid-19 packages
Official Debian packages with high relevance
abacas
close gaps in genomic alignments from short reads
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Versions of package abacas |
Release | Version | Architectures |
bookworm | 1.3.1-9 | all |
stretch | 1.3.1-3 | all |
buster | 1.3.1-5 | all |
bullseye | 1.3.1-9 | all |
jessie | 1.3.1-2 | all |
sid | 1.3.1-9 | all |
trixie | 1.3.1-9 | all |
Debtags of package abacas: |
role | program |
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License: DFSG free
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ABACAS (Algorithm Based Automatic Contiguation of Assembled Sequences)
intends to rapidly contiguate (align, order, orientate), visualize and
design primers to close gaps on shotgun assembled contigs based on a
reference sequence.
ABACAS uses MUMmer to find alignment positions and identify syntenies
of assembled contigs against the reference. The output is then processed
to generate a pseudomolecule taking overlapping contigs and gaps in to
account. ABACAS generates a comparison file that can be used to
visualize ordered and oriented contigs in ACT. Synteny is represented by
red bars where colour intensity decreases with lower values of percent
identity between comparable blocks. Information on contigs such as the
orientation, percent identity, coverage and overlap with other contigs
can also be visualized by loading the outputted feature file on ACT.
Topics: Probes and primers
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abyss
de novo, parallel, sequence assembler for short reads
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Versions of package abyss |
Release | Version | Architectures |
bullseye | 2.2.5+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 2.3.9-1 | amd64,arm64,mips64el,ppc64el,riscv64 |
jessie | 1.5.2-1 (non-free) | amd64 |
buster | 2.1.5-7 | amd64,arm64,armhf,i386 |
stretch-backports | 2.1.5-7~bpo9+1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 2.3.10-1 | amd64,arm64,mips64el,ppc64el,riscv64 |
bookworm | 2.3.5+dfsg-2 | amd64,arm64,mips64el,ppc64el,s390x |
stretch | 2.0.2-2 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
Debtags of package abyss: |
role | program |
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License: DFSG free
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ABySS is a de novo, parallel, sequence assembler that is designed for
short reads. It may be used to assemble genome or transcriptome
sequence data. Parallelization is achieved using MPI, OpenMP and
pthread.
Please cite:
Shaun D. Jackman, Benjamin P. Vandervalk, Hamid Mohamadi, Justin Chu, Sarah Yeo, S. Austin Hammond, Golnaz Jahesh, Hamza Khan, Lauren Coombe, Rene L. Warren and İnanç Birol:
"ABySS 2.0: resource-efficient assembly of large genomes using a Bloom filter".
(PubMed,eprint)
Genome Research
27(5):768-777
(2017)
Topics: Sequence assembly
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allelecount
NGS copy number algorithms
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Versions of package allelecount |
Release | Version | Architectures |
bullseye | 4.2.1-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 4.3.0-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 4.3.0-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 4.3.0-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
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License: DFSG free
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Support code for NGS copy number algorithms. Takes a file of locations
and a [cr|b]am file and generates a count of coverage of each allele
[ACGT] at that location (given any filter settings).
The alleleCount package primarily exists to prevent code duplication
between some other projects, specifically AscatNGS and Battenberg.
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assembly-stats
get assembly statistics from FASTA and FASTQ files
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Versions of package assembly-stats |
Release | Version | Architectures |
trixie | 1.0.1+ds-6 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 1.0.1+ds-6 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 1.0.1+ds-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.0.1+ds-6 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
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License: DFSG free
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Get statistics from a list of files.
Detection of FASTA or FASTQ format of each file is automatic from the
file contents, so file names and extensions are irrelevant.
The default output format is human readable. You can change the output
format and ignore sequences shorter than a given length.
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augur
pipeline components for real-time virus analysis
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Versions of package augur |
Release | Version | Architectures |
bookworm | 20.0.0-1 | all |
sid | 24.4.0-1 | all |
trixie | 24.4.0-1 | all |
bullseye | 11.0.0-1 | all |
buster-backports | 6.4.2-2~bpo10+1 | all |
upstream | 26.2.0 |
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License: DFSG free
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The nextstrain project is an attempt to make flexible informatic
pipelines and visualization tools to track ongoing pathogen evolution as
sequence data emerges. The nextstrain project derives from nextflu,
which was specific to influenza evolution.
nextstrain is comprised of three components:
- fauna: database and IO scripts for sequence and serological data
- augur: informatic pipelines to conduct inferences from raw data
- auspice: web app to visualize resulting inferences
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bamclipper
Remove gene-specific primer sequences from SAM/BAM alignments
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Versions of package bamclipper |
Release | Version | Architectures |
bookworm | 1.0.0-3 | all |
trixie | 1.0.0-3 | all |
sid | 1.0.0-3 | all |
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License: DFSG free
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Remove gene-specific primer sequences from SAM/BAM alignments of PCR
amplicons by soft-clipping.
bamclipper.sh soft-clips gene-specific primers from BAM alignment file based
on genomic coordinates of primer pairs in BEDPE format.
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bamkit
tools for common BAM file manipulations
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Versions of package bamkit |
Release | Version | Architectures |
sid | 0.0.1+git20170413.ccd079d-3 | all |
bullseye | 0.0.1+git20170413.ccd079d-2 | all |
bookworm | 0.0.1+git20170413.ccd079d-3 | all |
trixie | 0.0.1+git20170413.ccd079d-3 | all |
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License: DFSG free
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This package provides some Python3 tools for common BAM file
manipulations.
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bbmap
BBTools genomic aligner and other tools for short sequences
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Versions of package bbmap |
Release | Version | Architectures |
sid | 39.11+dfsg-1 | all |
buster-backports | 38.63+dfsg-1~bpo10+1 | all |
bullseye | 38.90+dfsg-1 | all |
bookworm | 39.01+dfsg-2 | all |
trixie | 39.11+dfsg-1 | all |
upstream | 39.13 |
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License: DFSG free
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The BBTools are a collection of small programs to solve recurrent
tasks for the creative handling of short biological RNA/DNA sequences.
This suite may be best known for its mapper, which is also the name of
the project on sourceforge, but several tools have been added over time.
All tools are multi-threaded, implemented platform-independently in Java:
BBMap: Short read aligner for DNA and RNA-seq data. Capable of handling
arbitrarily large genomes with millions of scaffolds. Handles Illumina,
PacBio, 454, and other reads; very high sensitivity and tolerant of
errors and numerous large indels.
BBNorm: Kmer-based error-correction and normalization tool.
Dedupe: Simplifies assemblies by removing duplicate or contained
subsequences that share a target percent identity.
Reformat: Reformats reads between fasta/fastq/scarf/fasta+qual/sam,
interleaved/paired, and ASCII-33/64, at over 500 MB/s.
BBDuk: Filters, trims, or masks reads with kmer matches to an
artifact/contaminant file.
The package is enhanced by the following packages:
multiqc
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bcalm
de Bruijn compaction in low memory
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Versions of package bcalm |
Release | Version | Architectures |
bookworm | 2.2.3-4 | amd64,arm64,mips64el,ppc64el |
trixie | 2.2.3-5 | amd64,arm64,mips64el,ppc64el,riscv64 |
sid | 2.2.3-5 | amd64,arm64,mips64el,ppc64el,riscv64 |
bullseye | 2.2.3-1 | amd64,arm64,i386,mips64el,ppc64el,s390x |
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License: DFSG free
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A bioinformatics tool for constructing the compacted de Bruijn graph
from sequencing data.
This is the parallel version of the BCALM software using gatb-core
library.
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bcftools
genomic variant calling and manipulation of VCF/BCF files
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Versions of package bcftools |
Release | Version | Architectures |
bookworm | 1.16-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
stretch | 1.3.1-1 | amd64,arm64,armel,mips64el,mipsel,ppc64el |
sid | 1.20-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster | 1.9-1 | amd64,arm64,armhf |
stretch-backports | 1.8-1~bpo9+1 | amd64,arm64,armel,armhf,mips64el,mipsel,ppc64el |
bullseye | 1.11-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
trixie | 1.20-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
upstream | 1.21 |
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License: DFSG free
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BCFtools is a set of utilities that manipulate variant calls in the
Variant Call Format (VCF) and its binary counterpart BCF. All commands work
transparently with both VCFs and BCFs, both uncompressed and BGZF-compressed.
The package is enhanced by the following packages:
multiqc
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bedtools
suite of utilities for comparing genomic features
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Versions of package bedtools |
Release | Version | Architectures |
bullseye | 2.30.0+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 2.31.1+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster | 2.27.1+dfsg-4 | amd64,arm64,armhf |
sid | 2.31.1+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
jessie | 2.21.0-1 | amd64,armhf,i386 |
bookworm | 2.30.0+dfsg-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
stretch | 2.26.0+dfsg-3 | amd64,arm64,armel,i386,mips64el,mipsel,ppc64el |
Debtags of package bedtools: |
field | biology, biology:bioinformatics |
interface | commandline |
role | program |
scope | suite |
use | analysing, comparing, converting, filtering |
works-with | biological-sequence |
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License: DFSG free
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The BEDTools utilities allow one to address common genomics tasks such as
finding feature overlaps and computing coverage. The utilities are largely
based on four widely-used file formats: BED, GFF/GTF, VCF, and SAM/BAM. Using
BEDTools, one can develop sophisticated pipelines that answer complicated
research questions by streaming several BEDTools together.
The groupBy utility is distributed in the filo package.
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biobambam2
tools for early stage alignment file processing
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Versions of package biobambam2 |
Release | Version | Architectures |
sid | 2.0.185+ds-2 | amd64,i386,mips64el,ppc64el,riscv64 |
trixie | 2.0.185+ds-2 | amd64,i386,mips64el,ppc64el,riscv64 |
bookworm | 2.0.185+ds-1 | amd64,arm64,i386,ppc64el |
bullseye | 2.0.179+ds-1 | amd64,arm64,i386,ppc64el |
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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bowtie2
ultrafast memory-efficient short read aligner
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Versions of package bowtie2 |
Release | Version | Architectures |
stretch | 2.3.0-2 | amd64 |
buster | 2.3.4.3-1 | amd64 |
jessie | 2.2.4-1 | amd64 |
bullseye | 2.4.2-2 | amd64,arm64,mips64el,ppc64el |
trixie | 2.5.4-1 | amd64,arm64,mips64el,ppc64el,riscv64 |
bookworm | 2.5.0-3 | amd64,arm64,mips64el,ppc64el |
sid | 2.5.4-1 | amd64,arm64,mips64el,ppc64el,riscv64 |
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License: DFSG free
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is an ultrafast and memory-efficient tool for aligning sequencing reads
to long reference sequences. It is particularly good at aligning reads
of about 50 up to 100s or 1,000s of characters, and particularly good
at aligning to relatively long (e.g. mammalian) genomes.
Bowtie 2 indexes the genome with an FM Index to keep its memory footprint
small: for the human genome, its memory footprint is typically
around 3.2 GB. Bowtie 2 supports gapped, local, and paired-end alignment modes
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busco
benchmarking sets of universal single-copy orthologs
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Versions of package busco |
Release | Version | Architectures |
sid | 5.5.0-2 | amd64,arm64,i386 |
trixie | 5.5.0-2 | amd64,arm64,i386 |
bookworm | 5.4.4-1 | amd64,i386 |
bullseye | 5.0.0-1 | all |
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License: DFSG free
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Assessing genome assembly and annotation completeness with Benchmarking
Universal Single-Copy Orthologs (BUSCO).
- Automated selection of lineages issued from https://www.orthodb.org/
- Automated download of all necessary files and datasets to conduct a run
- Use prodigal for non-eukaryotic genomes
The package is enhanced by the following packages:
multiqc
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bustools
program for manipulating BUS files for single cell RNA-Seq datasets
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Versions of package bustools |
Release | Version | Architectures |
bullseye | 0.40.0-4 | amd64,arm64,mips64el,ppc64el,s390x |
sid | 0.43.2+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
trixie | 0.43.2+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bookworm | 0.42.0+dfsg-1 | amd64,arm64,mips64el,ppc64el,s390x |
upstream | 0.44.1 |
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License: DFSG free
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This package contains BUStools program, it can be used to error correct
barcodes, collapse UMIs, produce gene count or transcript compatibility
count matrices
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bwa
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Versions of package bwa |
Release | Version | Architectures |
stretch | 0.7.15-2+deb9u1 | amd64 |
jessie | 0.7.10-1 | amd64 |
bullseye | 0.7.17-6 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 0.7.17-7 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 0.7.18-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 0.7.18-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch-backports | 0.7.17-1~bpo9+1 | amd64 |
buster | 0.7.17-3 | amd64 |
Debtags of package bwa: |
biology | nuceleic-acids, peptidic |
field | biology, biology:bioinformatics |
interface | commandline, text-mode |
role | program |
use | analysing, comparing |
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License: DFSG free
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BWA is a software package for mapping low-divergent sequences against
a large reference genome, such as the human genome. It consists of
three algorithms: BWA-backtrack, BWA-SW and BWA-MEM. The first
algorithm is designed for Illumina sequence reads up to 100bp, while
the rest two for longer sequences ranged from 70bp to 1Mbp. BWA-MEM
and BWA-SW share similar features such as long-read support and split
alignment, but BWA-MEM, which is the latest, is generally recommended
for high-quality queries as it is faster and more accurate. BWA-MEM
also has better performance than BWA-backtrack for 70-100bp Illumina
reads.
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cat-bat
taxonomic classification of contigs and metagenome-assembled genomes (MAGs)
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Versions of package cat-bat |
Release | Version | Architectures |
bookworm | 5.2.3-2 | amd64,arm64,ppc64el,s390x |
sid | 5.3-2 | amd64,arm64,ppc64el,riscv64,s390x |
bullseye | 5.2.2-1 | amd64,arm64,ppc64el,s390x |
trixie | 5.3-2 | amd64,arm64,ppc64el,riscv64,s390x |
upstream | 6.0.1 |
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License: DFSG free
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Contig Annotation Tool (CAT) and Bin Annotation Tool (BAT) are pipelines
for the taxonomic classification of long DNA sequences and metagenome
assembled genomes (MAGs/bins) of both known and (highly) unknown
microorganisms, as generated by contemporary metagenomics studies. The
core algorithm of both programs involves gene calling, mapping of
predicted ORFs against the nr protein database, and voting-based
classification of the entire contig / MAG based on classification of the
individual ORFs. CAT and BAT can be run from intermediate steps if files
are formatted appropriately.
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centrifuge
rapid and memory-efficient system for classification of DNA sequences
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Versions of package centrifuge |
Release | Version | Architectures |
trixie | 1.0.4.2-1 | amd64,arm64,mips64el,ppc64el,riscv64 |
buster | 1.0.3-2 | amd64 |
sid | 1.0.4.2-1 | amd64,arm64,mips64el,ppc64el,riscv64 |
bullseye | 1.0.3-8 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el |
bookworm | 1.0.3-11 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el |
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License: DFSG free
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Centrifuge is a very rapid and memory-efficient system for the
classification of DNA sequences from microbial samples, with better
sensitivity than and comparable accuracy to other leading systems. The
system uses a novel indexing scheme based on the Burrows-Wheeler
transform (BWT) and the Ferragina-Manzini (FM) index, optimized
specifically for the metagenomic classification problem. Centrifuge
requires a relatively small index (e.g., 4.3 GB for ~4,100 bacterial
genomes) yet provides very fast classification speed, allowing it to
process a typical DNA sequencing run within an hour. Together these
advances enable timely and accurate analysis of large metagenomics data
sets on conventional desktop computers.
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changeo
Repertoire clonal assignment toolkit (Python 3)
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Versions of package changeo |
Release | Version | Architectures |
bullseye | 1.0.2-1 | all |
buster | 0.4.5-1 | all |
trixie | 1.3.0-2 | all |
sid | 1.3.0-2 | all |
bookworm | 1.3.0-1 | all |
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License: DFSG free
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Change-O is a collection of tools for processing the output of V(D)J
alignment tools, assigning clonal clusters to immunoglobulin (Ig)
sequences, and reconstructing germline sequences.
Dramatic improvements in high-throughput sequencing technologies now
enable large-scale characterization of Ig repertoires, defined as the
collection of trans-membrane antigen-receptor proteins located on the
surface of B cells and T cells. Change-O is a suite of utilities to
facilitate advanced analysis of Ig and TCR sequences following germline
segment assignment. Change-O handles output from IMGT/HighV-QUEST
and IgBLAST, and provides a wide variety of clustering methods for
assigning clonal groups to Ig sequences. Record sorting, grouping,
and various database manipulation operations are also included.
This package installs the library for Python 3.
Please cite:
Namita T. Gupta, Jason A. Vander Heiden, Mohamed Uduman, Daniel Gadala-Maria, Gur Yaari and Steven H. Kleinstein:
Link
to publication
(PubMed,eprint)
Bioinformatics
31(20):3356-3358
(2015)
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chip-seq
tools performing common ChIP-Seq data analysis tasks
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Versions of package chip-seq |
Release | Version | Architectures |
buster-backports | 1.5.5-3~bpo10+1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
bullseye | 1.5.5-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.5.5-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.5.5-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 1.5.5-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
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License: DFSG free
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The ChIP-Seq software provides a set of tools performing common genome-
wide ChIP- seq analysis tasks, including positional correlation
analysis, peak detection, and genome partitioning into signal-rich and
signal-poor regions. These tools exist as stand-alone C programs and
perform the following tasks:
1. Positional correlation analysis and generation of an aggregation
plot (AP) (chipcor),
2. Extraction of specific genome annotation features around reference
anchor points (chipextract),
3. Read centering or shifting (chipcenter),
4. Narrow peak caller using a fixed width peak size (chippeak),
5. Broad peak caller used for large regions of enrichment (chippart),
6. Feature selection tool based on a read count threshold (chipscore).
Because the ChIP-Seq tools are primarily optimized for speed, they use
their own compact format for ChIP-seq data representation called SGA
(Simplified Genome Annotation). SGA is a line-oriented, tab-delimited
plain text format.
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clonalframeml
Efficient Inference of Recombination in Whole Bacterial Genomes
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Versions of package clonalframeml |
Release | Version | Architectures |
bookworm | 1.12-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.13-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.12-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 1.11-3 | amd64,arm64,armhf,i386 |
trixie | 1.13-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
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License: DFSG free
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ClonalFrameML is a software package that performs efficient inference of
recombination in bacterial genomes. ClonalFrameML was created by Xavier
Didelot and Daniel Wilson. ClonalFrameML can be applied to any type of
aligned sequence data, but is especially aimed at analysis of whole
genome sequences. It is able to compare hundreds of whole genomes in a
matter of hours on a standard Desktop computer. There are three main
outputs from a run of ClonalFrameML: a phylogeny with branch lengths
corrected to account for recombination, an estimation of the key
parameters of the recombination process, and a genomic map of where
recombination took place for each branch of the phylogeny.
ClonalFrameML is a maximum likelihood implementation of the Bayesian
software ClonalFrame which was previously described by Didelot and
Falush (2007). The recombination model underpinning ClonalFrameML is
exactly the same as for ClonalFrame, but this new implementation is a
lot faster, is able to deal with much larger genomic dataset, and does
not suffer from MCMC convergence issues
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cutadapt
Clean biological sequences from high-throughput sequencing reads
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Versions of package cutadapt |
Release | Version | Architectures |
buster | 1.18-1 | all |
stretch | 1.12-2 | all |
trixie | 4.7-2 | all |
bookworm | 4.2-1 | all |
sid | 4.7-2 | all |
bullseye | 3.2-2 | all |
upstream | 4.9 |
|
License: DFSG free
|
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 user interface.
The package is enhanced by the following packages:
multiqc
|
|
cwltool
Common Workflow Language reference implementation
|
Versions of package cwltool |
Release | Version | Architectures |
bullseye | 3.0.20210124104916-3+deb11u1 | all |
sid | 3.1.20241024121129-1 | all |
trixie | 3.1.20241024121129-1 | all |
bookworm | 3.1.20230209161050-1 | all |
stretch | 1.0.20170114120503-1 | all |
buster | 1.0.20181217162649+dfsg-10 | all |
upstream | 3.1.20241112140730 |
|
License: DFSG free
|
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.
|
|
dcmtk
OFFIS DICOM toolkit command line utilities
|
Versions of package dcmtk |
Release | Version | Architectures |
stretch | 3.6.1~20160216-4 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster-security | 3.6.4-2.1+deb10u1 | amd64,arm64,armhf,i386 |
bullseye-backports | 3.6.7-6~bpo11+1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
jessie | 3.6.0-15+deb8u1 | amd64,armel,armhf,i386 |
bookworm | 3.6.7-9~deb12u1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
jessie-security | 3.6.0-15+deb8u1 | amd64,armel,armhf,i386 |
buster | 3.6.4-2.1 | amd64,arm64,armhf,i386 |
trixie | 3.6.8-6 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 3.6.8-6 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 3.6.5-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
Debtags of package dcmtk: |
interface | commandline |
role | program |
scope | utility |
use | converting, downloading |
works-with | image, image:raster |
|
License: DFSG free
|
DCMTK includes a collection of libraries and applications for examining,
constructing and converting DICOM image files, handling offline media,
sending and receiving images over a network connection, as well as
demonstrative image storage and worklist servers.
This package contains the DCMTK utility applications.
Note: This version was compiled with libssl support.
|
|
delly
Structural variant discovery by read analysis
|
Versions of package delly |
Release | Version | Architectures |
trixie | 1.1.8-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 1.1.8-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster | 0.8.1-2 | amd64,arm64,armhf |
bullseye | 0.8.7-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.1.6-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
upstream | 1.3.1 |
|
License: DFSG free
|
Delly performs Structural variant discovery by integrated paired-end and
split-read analysis. It discovers, genotypes and visualizes deletions,
tandem duplications, inversions and translocations at single-nucleotide
resolution in short-read massively parallel sequencing data. It uses
paired-ends, split-reads and read-depth to sensitively and accurately
delineate genomic rearrangements throughout the genome.
|
|
dextractor
(d)extractor and compression command library
|
|
License: DFSG free
|
Dextractor commands allow one to pull exactly and only the
information needed for assembly and reconstruction from the source HDF5
files produced by the PacBio RS II sequencer, or from the source BAM
files produced by the PacBio Sequel sequencer.
For each of the three extracted file types -- fasta, quiva, and
arrow -- the library contains commands to compress the given file
type, and to decompress it, which is a reversible process delivering
the original uncompressed file. The compressed .fasta files, with the
extension .dexta, consume 1/4 byte per base. The compressed .quiva
files, with the extension .dexqv, consume 1.5 bytes per base on
average, and the compressed .arrow files, with the extension .dexar,
consume 1/4 byte per base
For more information, please view the available documentation at
https://github.com/thegenemyers/DEXTRACTOR
|
|
diamond-aligner
accelerated BLAST compatible local sequence aligner
|
Versions of package diamond-aligner |
Release | Version | Architectures |
sid | 2.1.9-1 | amd64,arm64,ppc64el,riscv64,s390x |
bookworm | 2.1.3-1 | amd64,arm64,ppc64el,s390x |
buster | 0.9.24+dfsg-1 | amd64 |
trixie | 2.1.9-1 | amd64,arm64,ppc64el,riscv64,s390x |
stretch-backports | 0.9.22+dfsg-2~bpo9+1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
bullseye | 2.0.7-1 | amd64,arm64,ppc64el,s390x |
upstream | 2.1.10 |
|
License: DFSG free
|
DIAMOND is a sequence aligner for protein and translated DNA searches
and functions as a drop-in replacement for the NCBI BLAST software
tools. It is suitable for protein-protein search as well as DNA-protein
search on short reads and longer sequences including contigs and
assemblies, providing a speedup of BLAST ranging up to x20,000.
|
|
discosnp
discovering Single Nucleotide Polymorphism from raw set(s) of reads
|
Versions of package discosnp |
Release | Version | Architectures |
bookworm | 2.6.2-2 | amd64,arm64,mips64el,ppc64el |
jessie | 1.2.5-1 | amd64,armel,armhf,i386 |
buster | 2.3.0-2 | amd64,arm64,i386 |
stretch | 1.2.6-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
bullseye | 4.4.4-1 | amd64,arm64,i386,mips64el,ppc64el,s390x |
sid | 2.6.2-3 | amd64,arm64,mips64el,ppc64el,riscv64 |
trixie | 2.6.2-3 | amd64,arm64,mips64el,ppc64el,riscv64 |
|
License: DFSG free
|
Software discoSnp is designed for discovering Single Nucleotide
Polymorphism (SNP) from raw set(s) of reads obtained with Next Generation
Sequencers (NGS).
Note that number of input read sets is not constrained, it can be one, two,
or more. Note also that no other data as reference genome or annotations
are needed.
The software is composed by two modules. First module, kissnp2, detects SNPs
from read sets. A second module, kissreads, enhance the kissnp2 results by
computing per read set and for each found SNP:
1) its mean read coverage
2) the (phred) quality of reads generating the polymorphism.
This program is superseded by DiscoSnp++.
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|
drop-seq-tools
|
Versions of package drop-seq-tools |
Release | Version | Architectures |
sid | 3.0.2+dfsg-1 | all |
trixie | 3.0.2+dfsg-1 | all |
bookworm | 2.5.2+dfsg-1 | all |
bullseye | 2.4.0+dfsg-6 | all |
|
License: DFSG free
|
This software provide for core computational analysis of Drop-seq data,
which shows you how to transform raw sequence data into an expression
measurement for each gene in each individual cell.
|
|
fasta3
tools for searching collections of biological sequences
|
Versions of package fasta3 |
Release | Version | Architectures |
bullseye | 36.3.8h.2020-02-11-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 36.3.8i.14-Nov-2020-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 36.3.8i.14-Nov-2020-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster | 36.3.8g-1 (non-free) | amd64 |
trixie | 36.3.8i.14-Nov-2020-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
|
License: DFSG free
|
The FASTA programs find regions of local or global similarity between
Protein or DNA sequences, either by searching Protein or DNA databases,
or by identifying local duplications within a sequence. Other
programs provide information on the statistical significance of an
alignment. Like BLAST, FASTA can be used to infer functional and
evolutionary relationships between sequences as well as help identify
members of gene families.
- Protein
- Protein-protein FASTA
- Protein-protein Smith-Waterman (ssearch)
- Global Protein-protein (Needleman-Wunsch) (ggsearch)
- Global/Local protein-protein (glsearch)
- Protein-protein with unordered peptides (fasts)
-
Protein-protein with mixed peptide sequences (fastf)
-
Nucleotide
- Nucleotide-Nucleotide (DNA/RNA fasta)
- Ordered Nucleotides vs Nucleotide (fastm)
-
Un-ordered Nucleotides vs Nucleotide (fasts)
-
Translated
- Translated DNA (with frameshifts, e.g. ESTs)
vs Proteins (fastx/fasty)
- Protein vs Translated DNA (with frameshifts)
(tfastx/tfasty)
-
Peptides vs Translated DNA (tfasts)
-
Statistical Significance
- Protein vs Protein shuffle (prss)
- DNA vs DNA shuffle (prss)
-
Translated DNA vs Protein shuffle (prfx)
-
Local Duplications
- Local Protein alignments (lalign)
- Plot Protein alignment "dot-plot" (plalign)
- Local DNA alignments (lalign)
- Plot DNA alignment "dot-plot" (plalign)
This software is often used via a web service at the
EBI with readily indexed reference databases at
http://www.ebi.ac.uk/Tools/fasta/.
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|
fastani
Fast alignment-free computation of whole-genome Average Nucleotide Identity
|
Versions of package fastani |
Release | Version | Architectures |
bookworm | 1.33-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.33-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 1.33-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
|
License: DFSG free
|
ANI is defined as mean nucleotide identity of orthologous gene pairs
shared between two microbial genomes. FastANI supports pairwise comparison
of both complete and draft genome assemblies.
|
|
fastp
Ultra-fast all-in-one FASTQ preprocessor
|
Versions of package fastp |
Release | Version | Architectures |
sid | 0.23.4+dfsg-1 | amd64,arm64,armel,armhf,mips64el,ppc64el,riscv64,s390x |
buster | 0.19.6+dfsg-1 | amd64,arm64,armhf,i386 |
bullseye | 0.20.1+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 0.23.2+dfsg-2 | amd64,arm64,armel,armhf,mips64el,mipsel,ppc64el,s390x |
trixie | 0.23.4+dfsg-1 | amd64,arm64,armel,armhf,mips64el,ppc64el,riscv64,s390x |
upstream | 0.24.0 |
|
License: DFSG free
|
All-in-one FASTQ preprocessor, fastp provides functions including quality
profiling, adapter trimming, read filtering and base correction. It supports
both single-end and paired-end short read data and also provides basic support
for long-read data.
The package is enhanced by the following packages:
multiqc
|
|
fastqc
quality control for high throughput sequence data
|
Versions of package fastqc |
Release | Version | Architectures |
stretch | 0.11.5+dfsg-6 | all |
sid | 0.12.1+dfsg-4 | all |
trixie | 0.12.1+dfsg-4 | all |
bookworm | 0.11.9+dfsg-6 | all |
bullseye | 0.11.9+dfsg-4 | all |
buster | 0.11.8+dfsg-2 | all |
jessie | 0.11.2+dfsg-3 | all |
|
License: DFSG free
|
FastQC aims to provide a simple way to do some quality control checks on
raw sequence data coming from high throughput sequencing pipelines. It
provides a modular set of analyses which you can use to give a quick
impression of whether your data has any problems of which you should
be aware before doing any further analysis.
The main functions of FastQC are
- Import of data from BAM, SAM or FastQ files (any variant)
- Providing a quick overview to tell you in which areas there may
be problems
- Summary graphs and tables to quickly assess your data
- Export of results to an HTML based permanent report
- Offline operation to allow automated generation of reports without
running the interactive application
The package is enhanced by the following packages:
multiqc
|
|
filtlong
quality filtering tool for long reads of genome sequences
|
Versions of package filtlong |
Release | Version | Architectures |
bookworm | 0.2.1-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 0.2.1-4 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 0.2.0-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 0.2.1-4 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
|
License: DFSG free
|
Filtlong is a tool for filtering long reads by quality. It can take a
set of long reads and produce a smaller, better subset. It uses both
read length (longer is better) and read identity (higher is better) when
choosing which reads pass the filter.
|
|
flash
Fast Length Adjustment of SHort reads
|
Versions of package flash |
Release | Version | Architectures |
bookworm | 1.2.11-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.2.11-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.2.11-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.2.11-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
|
License: DFSG free
|
FLASH (Fast Length Adjustment of SHort reads) is a very fast and
accurate software tool to merge paired-end reads from next-generation
sequencing experiments. FLASH is designed to merge pairs of reads when
the original DNA fragments are shorter than twice the length of reads.
The resulting longer reads can significantly improve genome assemblies.
They can also improve transcriptome assembly when FLASH is used to merge
RNA-seq data.
The package is enhanced by the following packages:
multiqc
|
|
flye
de novo assembler for single molecule sequencing reads using repeat graphs
|
Versions of package flye |
Release | Version | Architectures |
trixie | 2.9.5+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
sid | 2.9.5+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bookworm | 2.9.1+dfsg-1 | amd64,arm64,mips64el,ppc64el,s390x |
|
License: DFSG free
|
Flye is a de novo assembler for single molecule sequencing reads, such
as those produced by PacBio and Oxford Nanopore Technologies. It is
designed for a wide range of datasets, from small bacterial projects to
large mammalian-scale assemblies. The package represents a complete
pipeline: it takes raw PacBio / ONT reads as input and outputs polished
contigs. Flye also has a special mode for metagenome assembly.
|
|
freebayes
Bayesian haplotype-based polymorphism discovery and genotyping
|
Versions of package freebayes |
Release | Version | Architectures |
bookworm | 1.3.6-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
stretch-backports | 1.2.0-1~bpo9+1 | amd64 |
buster | 1.2.0-2 | amd64 |
sid | 1.3.7-1 | amd64,arm64,mips64el,ppc64el,riscv64 |
experimental | 1.3.7-1~exp | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,s390x |
bullseye | 1.3.5-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
upstream | 1.3.8-pre3 |
|
License: DFSG free
|
FreeBayes is a Bayesian genetic variant detector designed to find
small polymorphisms, specifically SNPs (single-nucleotide
polymorphisms), indels (insertions and deletions), MNPs
(multi-nucleotide polymorphisms), and complex events (composite
insertion and substitution events) smaller than the length of a
short-read sequencing alignment.
|
|
genometools
versatile genome analysis toolkit
|
Versions of package genometools |
Release | Version | Architectures |
bookworm | 1.6.2+ds-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.6.5+ds-2.2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm-backports | 1.6.5+ds-2~bpo12+1 | 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 |
buster-backports | 1.6.1+ds-3~bpo10+1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 1.5.10+ds-3 | amd64,arm64,armhf,i386 |
stretch | 1.5.9+ds-4 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
jessie | 1.5.3-2 | amd64,armel,armhf,i386 |
bullseye | 1.6.1+ds-3 | 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 genometools: |
biology | nuceleic-acids |
field | biology, biology:bioinformatics |
interface | commandline |
role | program |
uitoolkit | ncurses |
|
License: DFSG free
|
The GenomeTools contains a collection of useful tools for biological
sequence analysis and -presentation combined into a single binary.
The toolkit contains binaries for sequence and annotation handling, sequence
compression, index structure generation and access, annotation visualization,
and much more.
|
|
gffread
GFF/GTF format conversions, region filtering, FASTA sequence extraction
|
Versions of package gffread |
Release | Version | Architectures |
bullseye | 0.12.1-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 0.12.7-8 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,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 |
|
License: DFSG free
|
Gffread is a GFF/GTF parsing utility providing format conversions,
region filtering, FASTA sequence extraction and more.
|
|
ginkgocadx
Medical Imaging Software and complete DICOM Viewer
|
Versions of package ginkgocadx |
Release | Version | Architectures |
buster | 3.8.8-1 | amd64,i386 |
stretch | 3.8.4-1 | amd64,i386 |
bullseye | 3.8.8-5 | amd64,i386 |
jessie | 3.7.0.1465.37+dfsg-1 | amd64,armel,armhf,i386 |
Debtags of package ginkgocadx: |
field | medicine, medicine:imaging |
role | program |
uitoolkit | gtk, wxwidgets |
use | viewing |
|
License: DFSG free
|
Ginkgo CADx provides a complete DICOM viewer solution with advanced
capabilities and support for extensions.
- Easy and customizable interface through profiles.
- Full featured DICOM image visualization.
- Complete tool set (measure, markers, text, ...).
- Multiple modalities support (Neurological, Radiological, Dermatological,
Ophthalmological, Ultrasound, Endoscopy, ...)
- Dicomization support from JPEG, PNG, GIF and TIFF.
- Full EMH integration support: HL7 standard and IHE compliant workflows.
- PACS Workstation (C-FIND, C-MOVE, C-STORE...)
- Extensible through custom extensions.
- Retinal image mosaic composition.
- Automatic retinal analysis diagnostics.
- Psoriasis automatic diagnostics.
|
|
gnumed-client
medical practice management - Client
|
Versions of package gnumed-client |
Release | Version | Architectures |
bullseye | 1.8.5+dfsg-2 | all |
sid | 1.8.19+dfsg-1 | all |
stretch | 1.6.11+dfsg-3 | all |
trixie | 1.8.19+dfsg-1 | all |
bookworm | 1.8.9+dfsg-1 | all |
buster | 1.7.5+dfsg-3 | all |
jessie | 1.4.12+dfsg-1 | all |
Debtags of package gnumed-client: |
field | medicine |
interface | x11 |
network | client |
role | program |
scope | application |
uitoolkit | wxwidgets |
use | organizing |
works-with | db, people |
x11 | application |
|
License: DFSG free
|
This is the GNUmed Electronic Medical Record. Its purpose is
to enable doctors to keep a medically sound record on their
patients' health. It does not currently provide functionality
for stock keeping. Clinical features are well-tested by real
doctors in the field.
While the GNUmed team has taken the utmost care to make sure
the medical records are safe at all times you still need to
make sure you are taking appropriate steps to backup the
medical data to a safe place at appropriate intervals. Do
not forget to test your recovery procedures, too !
Protect your data! GNUmed itself comes without
any warranty whatsoever. You have been warned.
This package contains the wxpython client.
|
|
gnumed-server
medical practice management - server
|
Versions of package gnumed-server |
Release | Version | Architectures |
stretch | 21.11-1 | all |
buster | 22.5-1 | all |
bullseye | 22.15-1 | all |
bookworm | 22.19-1 | all |
jessie | 19.12-1 | all |
trixie | 22.28-1 | all |
sid | 22.28-1 | all |
upstream | 22.29 |
Debtags of package gnumed-server: |
field | medicine |
role | program |
|
License: DFSG free
|
This is the GNUmed Electronic Medical Record. Its purpose is
to enable doctors to keep a medically sound record on their
patients' health. It does not currently provide functionality
for billing and stock keeping. Clinical features are well-tested
by real doctors in the field.
While the GNUmed team has taken the utmost care to make sure
the medical records are safe at all times you still need to
make sure you are taking appropriate steps to backup the
medical data to a safe place at appropriate intervals. Do
not forget to test your recovery procedures, too !
Protect your data! GNUmed itself comes without
any warranty whatsoever. You have been warned.
This package contains the PostgreSQL server part.
Note: The package does currently NOT build the GNUmed database
but just installs the needed SQL files. Please see README.Debian.
|
|
gromacs
Molecular dynamics simulator, with building and analysis tools
|
Versions of package gromacs |
Release | Version | Architectures |
bullseye | 2020.6-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 2024.4-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
trixie | 2024.3-2 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
buster | 2019.1-1 | amd64,arm64,armhf,i386 |
stretch | 2016.1-2 | amd64,arm64,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
bookworm | 2022.5-2 | amd64,arm64,mips64el,ppc64el,s390x |
jessie | 5.0.2-1 | amd64,armel,armhf,i386 |
upstream | 2025.0~beta |
Debtags of package gromacs: |
field | biology, biology:structural, chemistry |
interface | commandline, x11 |
role | program |
uitoolkit | xlib |
x11 | application |
|
License: DFSG free
|
GROMACS is a versatile package to perform molecular dynamics, i.e. simulate
the Newtonian equations of motion for systems with hundreds to millions of
particles.
It is primarily designed for biochemical molecules like proteins and lipids
that have a lot of complicated bonded interactions, but since GROMACS is
extremely fast at calculating the nonbonded interactions (that usually
dominate simulations) many groups are also using it for research on non-
biological systems, e.g. polymers.
This package contains variants both for execution on a single machine, and
using the MPI interface across multiple machines.
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|
gubbins
phylogenetic analysis of genome sequences
|
Versions of package gubbins |
Release | Version | Architectures |
buster | 2.3.4-1 | amd64,i386 |
bullseye | 2.4.1-4 | amd64,i386 |
trixie | 3.3.5-1 | amd64,i386 |
bookworm | 2.4.1-5 | amd64,i386 |
sid | 3.3.5-1 | amd64,i386 |
stretch | 2.2.0-1 | amd64,i386 |
upstream | 3.4 |
|
License: DFSG free
|
Gubbins supports rapid phylogenetic analysis of large samples of
recombinant bacterial whole genome sequences.
Gubbins (Genealogies Unbiased By recomBinations In Nucleotide
Sequences) is an algorithm that iteratively identifies loci containing
elevated densities of base substitutions while concurrently constructing
a phylogeny based on the putative point mutations outside of these
regions. Simulations demonstrate the algorithm generates highly accurate
reconstructions under realistic models of short-term bacterial
evolution, and can be run in only a few hours on alignments of hundreds
of bacterial genome sequences.
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|
imagej
Image processing program with a focus on microscopy images
|
Versions of package imagej |
Release | Version | Architectures |
bookworm | 1.53t-1 | all |
sid | 1.54g-1 | all |
trixie | 1.54g-1 | all |
bullseye | 1.53g-2 | all |
buster | 1.52j-1 | all |
stretch | 1.51i+dfsg-2 | all |
jessie | 1.49i+dfsg-1 | all |
Debtags of package imagej: |
role | program |
use | analysing, editing, viewing |
works-with | image, image:raster |
works-with-format | gif, jpg, tiff |
|
License: DFSG free
|
It can display, edit, analyze, process, save and print 8-bit, 16-bit and
32-bit images. It can read many image formats including TIFF, GIF, JPEG,
BMP, DICOM, FITS and "raw". It supports "stacks", a series of images that
share a single window.
It can calculate area and pixel value statistics of user-defined
selections. It can measure distances and angles. It can create density
histograms and line profile plots. It supports standard image processing
functions such as contrast manipulation, sharpening, smoothing, edge
detection and median filtering.
Spatial calibration is available to provide real world dimensional
measurements in units such as millimeters. Density or gray scale
calibration is also available.
ImageJ is developed by Wayne Rasband (wayne@codon.nih.gov), is at the
Research Services Branch, National Institute of Mental Health, Bethesda,
Maryland, USA.
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|
ivar
functions broadly useful for viral amplicon-based sequencing
|
Versions of package ivar |
Release | Version | Architectures |
bullseye | 1.3+dfsg-1 | amd64,arm64,i386,mips64el,mipsel |
bookworm | 1.3.1+dfsg-7 | amd64,arm64,i386,mips64el,mipsel |
sid | 1.4.3+dfsg-2 | amd64,arm64,i386,mips64el,riscv64 |
trixie | 1.4.3+dfsg-2 | amd64,arm64,i386,mips64el,riscv64 |
|
License: DFSG free
|
iVar is a computational package that contains functions broadly useful
for viral amplicon-based sequencing. Additional tools for metagenomic
sequencing are actively being incorporated into iVar. While each of
these functions can be accomplished using existing tools, iVar contains
an intersection of functionality from multiple tools that are required
to call iSNVs and consensus sequences from viral sequencing data across
multiple replicates. iVar provided the following functions:
1. trimming of primers and low-quality bases,
2. consensus calling,
3. variant calling - both iSNVs and insertions/deletions, and
4. identifying mismatches to primer sequences and excluding the
corresponding reads from alignment files.
The package is enhanced by the following packages:
multiqc
Please cite:
Nathan D. Grubaugh, Karthik Gangavarapu, Joshua Quick, Nathaniel L. Matteson, Jaqueline Goes De Jesus, Bradley J. Main, Amanda L. Tan, Lauren M. Paul, Doug E. Brackney, Saran Grewal, Nikos Gurfield, Koen K. A. Van Rompay, Sharon Isern, Scott F. Michael, Lark L. Coffey, Nicholas J. Loman and Kristian G. Andersen:
An amplicon-based sequencing framework for accurately measuring intrahost virus diversity using PrimalSeq and iVar.
(PubMed,eprint)
Genome Biology
20(1):8
(2019)
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kalign
Global and progressive multiple sequence alignment
|
Versions of package kalign |
Release | Version | Architectures |
bullseye | 3.3-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 3.4.0-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch | 2.03+20110620-3 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 2.03+20110620-5 | amd64,arm64,armhf,i386 |
jessie | 2.03+20110620-2 | amd64,armel,armhf,i386 |
sid | 3.4.0-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 3.3.5-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
Debtags of package kalign: |
biology | format:aln, nuceleic-acids, peptidic |
field | biology, biology:bioinformatics |
interface | commandline |
role | program |
scope | utility |
use | comparing |
works-with-format | plaintext |
|
License: DFSG free
|
Kalign is a command line tool to perform multiple alignment of
biological sequences. It employs the Muth-Manber string-matching
algorithm, to improve both the accuracy and speed of the alignment.
It uses global, progressive alignment approach, enriched by employing
an approximate string-matching algorithm to calculate sequence
distances and by incorporating local matches into the otherwise global
alignment.
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|
kallisto
near-optimal RNA-Seq quantification
|
Versions of package kallisto |
Release | Version | Architectures |
bullseye | 0.46.2+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 0.48.0+dfsg-3 | amd64,arm64,mips64el,ppc64el,s390x |
trixie | 0.48.0+dfsg-4 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
sid | 0.48.0+dfsg-4 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
upstream | 0.51.1 |
|
License: DFSG free
|
Kallisto is a program for quantifying abundances of transcripts from
RNA-Seq data, or more generally of target sequences using high-throughput
sequencing reads. It is based on the novel idea of pseudoalignment for
rapidly determining the compatibility of reads with targets, without the
need for alignment. On benchmarks with standard RNA-Seq data, kallisto
can quantify 30 million human reads in less than 3 minutes on a Mac
desktop computer using only the read sequences and a transcriptome index
that itself takes less than 10 minutes to build. Pseudoalignment of
reads preserves the key information needed for quantification, and
kallisto is therefore not only fast, but also as accurate than existing
quantification tools. In fact, because the pseudoalignment procedure is
robust to errors in the reads, in many benchmarks kallisto significantly
outperforms existing tools.
The package is enhanced by the following packages:
multiqc
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kraken2
taxonomic classification system using exact k-mer matches
|
Versions of package kraken2 |
Release | Version | Architectures |
trixie | 2.1.3-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 2.1.1-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 2.1.2-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 2.1.3-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
|
License: DFSG free
|
Kraken 2 is the newest version of Kraken, a taxonomic classification
system using exact k-mer matches to achieve high accuracy and fast
classification speeds. This classifier matches each k-mer within a query
sequence to the lowest common ancestor (LCA) of all genomes containing
the given k-mer. The k-mer assignments inform the classification
algorithm. [see: Kraken 1's Webpage for more details].
Kraken 2 provides significant improvements to Kraken 1, with faster
database build times, smaller database sizes, and faster classification
speeds. These improvements were achieved by the following updates to the
Kraken classification program:
1. Storage of Minimizers: Instead of storing/querying entire k-mers,
Kraken 2 stores minimizers (l-mers) of each k-mer. The length of
each l-mer must be ≤ the k-mer length. Each k-mer is treated by
Kraken 2 as if its LCA is the same as its minimizer's LCA.
2. Introduction of Spaced Seeds: Kraken 2 also uses spaced seeds to
store and query minimizers to improve classification accuracy.
3. Database Structure: While Kraken 1 saved an indexed and sorted list
of k-mer/LCA pairs, Kraken 2 uses a compact hash table. This hash
table is a probabilistic data structure that allows for faster
queries and lower memory requirements. However, this data structure
does have a <1% chance of returning the incorrect LCA or returning
an LCA for a non-inserted minimizer. Users can compensate for this
possibility by using Kraken's confidence scoring thresholds.
4. Protein Databases: Kraken 2 allows for databases built from amino
acid sequences. When queried, Kraken 2 performs a six-frame
translated search of the query sequences against the database.
5. 16S Databases: Kraken 2 also provides support for databases not
based on NCBI's taxonomy. Currently, these include the 16S
databases: Greengenes, SILVA, and RDP.
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lastz
pairwise aligning DNA sequences
|
Versions of package lastz |
Release | Version | Architectures |
sid | 1.04.22-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.04.03-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.04.22-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.04.22-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
|
License: DFSG free
|
LASTZ is a drop-in replacement for BLASTZ, and is backward compatible with
BLASTZ’s command-line syntax. That is, it supports all of BLASTZ’s options
but also has additional ones, and may produce slightly different alignment
results.
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libbbhash-dev
bloom-filter based minimal perfect hash function library
|
Versions of package libbbhash-dev |
Release | Version | Architectures |
sid | 1.0.0-6 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bookworm | 1.0.0-5 | amd64,arm64,mips64el,ppc64el,s390x |
bullseye | 1.0.0-3 | amd64,arm64,mips64el,ppc64el,s390x |
trixie | 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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libchipcard-dev
API for smartcard readers
|
Versions of package libchipcard-dev |
Release | Version | Architectures |
buster | 5.1.0beta-3 | amd64,arm64,armhf,i386 |
stretch | 5.0.4-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
bullseye | 5.1.5rc2-7 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 5.1.6-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster-backports | 5.1.5rc2-7~bpo10+1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
jessie | 5.0.3beta-5 | amd64,armel,armhf,i386 |
experimental | 5.99.1beta-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 5.1.6-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 5.1.6-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
upstream | 5.99.1beta |
Debtags of package libchipcard-dev: |
devel | lang:c, library |
role | devel-lib |
|
License: DFSG free
|
libchipcard provides an API for accessing smartcards. Examples are
memory cards, as well as HBCI (home banking), German GeldKarte
(electronic small change), and KVK (health insurance) cards.
This package contains the development files for libchipcard.
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libgclib-dev
header files for Genome Code Lib (GCLib)
|
Versions of package libgclib-dev |
Release | Version | Architectures |
trixie | 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 |
sid | 0.12.7+ds-5 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 0.12.7+ds-5 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,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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libgdcm-tools
Grassroots DICOM tools and utilities
|
Versions of package libgdcm-tools |
Release | Version | Architectures |
buster | 2.8.8-9 | amd64,arm64,armhf,i386 |
sid | 3.0.24-5 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 3.0.24-5 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch | 2.6.6-3 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
bookworm | 3.0.21-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye-backports | 3.0.17-4~bpo11+1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
jessie | 2.4.4-3+deb8u1 | amd64,armel,armhf,i386 |
bullseye | 3.0.8-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
Debtags of package libgdcm-tools: |
field | medicine:imaging |
interface | commandline |
role | program |
scope | utility |
use | converting |
works-with | image, image:raster |
|
License: DFSG free
|
Grassroots DiCoM is a C++ library for DICOM medical files. It is
automatically wrapped to python/C#/Java (using swig). It supports
RAW,JPEG (lossy/lossless),J2K,JPEG-LS, RLE and deflated.
Install this package for the gdcmanon, gdcmclean, gdcmconv, gdcmdiff,
gdcmdump, gdcmpap3, gdcmgendir, gdcmimg, gdcminfo, gdcmpdf, gdcmraw,
gdcmscanner, gdcmscu, gdcmtar, gdcmxml programs.
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libhtscodecs-dev
Development headers for custom compression for CRAM and others
|
Versions of package libhtscodecs-dev |
Release | Version | Architectures |
bookworm | 1.3.0-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 0.5-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.6.1-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 1.6.1-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,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
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libics-dev
Image Cytometry Standard file reading and writing (devel)
|
Versions of package libics-dev |
Release | Version | Architectures |
bullseye | 1.6.4-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.6.6-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.6.8-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch | 1.5.2-6 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
trixie | 1.6.8-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
jessie | 1.5.2-6 | amd64,armel,armhf,i386 |
buster | 1.6.2-2 | amd64,arm64,armhf,i386 |
Debtags of package libics-dev: |
devel | library |
role | devel-lib |
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License: DFSG free
|
This is the reference library for ICS (Image Cytometry Standard), an open
standard for writing images of any dimensionality and data type to file,
together with associated information regarding the recording equipment or
recorded subject.
This package contains the libraries needed to build ICS applications.
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libmaus2-dev
collection of data structures and algorithms for biobambam (devel)
|
Versions of package libmaus2-dev |
Release | Version | Architectures |
trixie | 2.0.813+ds-3 | amd64,i386,mips64el,ppc64el,riscv64 |
sid | 2.0.813+ds-3 | amd64,i386,mips64el,ppc64el,riscv64 |
bullseye | 2.0.768+dfsg-2 | amd64,arm64,i386,ppc64el |
bookworm | 2.0.813+ds-1 | 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 |
bookworm | 2.2.0+dfsg-1 | all |
buster | 1.10-2 | all |
bullseye | 1.13-1 | all |
sid | 2.2.0+dfsg-1 | all |
trixie | 2.2.0+dfsg-1 | all |
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License: DFSG free
|
A helping Java package adopted by a range of Open Source tools for the
analysis of B and T cell repertoires.
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libseqan3-dev
C++ library for the analysis of biological sequences v3 (development)
|
Versions of package libseqan3-dev |
Release | Version | Architectures |
experimental | 3.4.0~rc.1+ds-1~0exp0 | all |
trixie | 3.3.0+ds-3 | all |
bookworm | 3.2.0+ds-6 | all |
buster-backports | 3.0.1+ds-3~bpo10+1 | amd64,arm64,mips64el,ppc64el,s390x |
bullseye | 3.0.2+ds-9 | all |
sid | 3.3.0+ds-3 | all |
upstream | 3.4.0~rc.1 |
|
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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lighter
fast and memory-efficient sequencing error corrector
|
Versions of package lighter |
Release | Version | Architectures |
bullseye | 1.1.2-5 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.1.3-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 1.1.3-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 1.1.2-7 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
|
License: DFSG free
|
Lighter is a fast, memory-efficient tool for correcting sequencing
errors. Lighter avoids counting k-mers. Instead, it uses a pair of Bloom
filters, one holding a sample of the input k-mers and the other holding
k-mers likely to be correct. As long as the sampling fraction is
adjusted in inverse proportion to the depth of sequencing, Bloom filter
size can be held constant while maintaining near-constant accuracy.
Lighter is parallelized, uses no secondary storage, and is both faster
and more memory-efficient than competing approaches while achieving
comparable accuracy.
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lumpy-sv
general probabilistic framework for structural variant discovery
|
Versions of package lumpy-sv |
Release | Version | Architectures |
bullseye | 0.3.1+dfsg-5 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
bookworm | 0.3.1+dfsg-7 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
trixie | 0.3.1+dfsg-7 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
sid | 0.3.1+dfsg-7 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
|
License: DFSG free
|
LUMPY, a novel SV discovery framework that naturally integrates multiple
SV signals jointly across multiple samples. LUMPY yields improved
sensitivity, especially when SV signal is reduced owing to either low
coverage data or low intra-sample variant allele frequency.
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mecat2
ultra-fast and accurate de novo assembly tools for SMRT reads
|
Versions of package mecat2 |
Release | Version | Architectures |
bookworm | 0.0+git20200428.f54c542+ds-3 | amd64 |
bullseye | 0.0+git20200428.f54c542+ds-3 | amd64 |
sid | 0.0+git20200428.f54c542+ds-4 | amd64 |
trixie | 0.0+git20200428.f54c542+ds-4 | amd64 |
|
License: DFSG free
|
An improved version of MECAT. It is an ultra-fast and accurate mapping
and error correcting de novo assembly tools for single molecula
sequencing (SMRT) reads. MECAT2 consists of the following three modules:
1. mecat2map: a fast and accurate alignment tool for SMRT reads.
2. mecat2cns: correct noisy reads based on their pairwise overlaps.
3. fsa: a string graph based assembly tool.
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megahit
ultra-fast and memory-efficient meta-genome assembler
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Versions of package megahit |
Release | Version | Architectures |
trixie | 1.2.9-5 | amd64 |
bullseye | 1.2.9-2 | amd64 |
sid | 1.2.9-5 | amd64 |
bookworm | 1.2.9-4 | amd64 |
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License: DFSG free
|
Megahit is an ultra-fast and memory-efficient NGS assembler. It is
optimized for metagenomes, but also works well on generic single genome
assembly (small or mammalian size) and single-cell assembly.
The software was praised in a Briefings in Bioinformatics 5/2020
review (DOI: 10.1093/bib/bbaa085).
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metabat
robust statistical framework for reconstructing genomes from metagenomic data
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Versions of package metabat |
Release | Version | Architectures |
bookworm | 2.15-4 | amd64,i386 |
sid | 2.15-4 | amd64,i386 |
bullseye | 2.15-3 | amd64,i386 |
trixie | 2.15-4 | amd64,i386 |
upstream | 2.17 |
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License: DFSG free
|
MetaBAT integrates empirical probabilistic distances of genome abundance
and tetranucleotide frequency for accurate metagenome binning. MetaBAT
outperforms alternative methods in accuracy and computational efficiency
on both synthetic and real metagenome datasets. It automatically forms
hundreds of high quality genome bins on a very large assembly consisting
millions of contigs in a matter of hours on a single node.
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minia
short-read biological sequence assembler
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Versions of package minia |
Release | Version | Architectures |
buster | 1.6906-2 | amd64,arm64,armhf,i386 |
bullseye | 3.2.1+git20200522.4960a99-1 | amd64,arm64,i386,mips64el,ppc64el,s390x |
bookworm | 3.2.6-3 | amd64,arm64,mips64el,ppc64el |
stretch | 1.6906-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
jessie | 1.6088-1 | amd64,armel,armhf,i386 |
trixie | 3.2.6-4 | amd64,arm64,mips64el,ppc64el,riscv64 |
sid | 3.2.6-4 | amd64,arm64,mips64el,ppc64el,riscv64 |
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License: DFSG free
|
What was referred to as "next-generation" DNA sequencing up to
the year 2020 delivered only "short" reads up to ~600 base pairs
in length that would then have to be puzzled by random overlaps
in their sequence towards a complete genome. This is the genome
assembly. And there are many biological pitfalls on long stretches
of low complexity regions and copy number variations and other
sorts of redundancies that render this difficult.
This package provides a short-read DNA sequence assembler based on a
de Bruijn graph, capable of assembling a human genome on a desktop
computer in a day.
The output of Minia is a set of contigs, i.e. stretches of gap-free
linear overlaps of short reads. In the best possible case this is
a whole chromosome.
Minia produces results of similar contiguity and accuracy to other
de Bruijn assemblers (e.g. Velvet).
Topics: Sequence assembly
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minimap2
versatile pairwise aligner for genomic and spliced nucleotide sequences
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Versions of package minimap2 |
Release | Version | Architectures |
trixie | 2.27+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 2.27+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch-backports | 2.15+dfsg-1~bpo9+1 | amd64,i386 |
bullseye | 2.17+dfsg-12 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 2.15+dfsg-1 | amd64,i386 |
bookworm | 2.24+dfsg-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
upstream | 2.28 |
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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%.
For ~10kb noisy reads sequences, minimap2 is tens of times faster than
mainstream long-read mappers such as BLASR, BWA-MEM, NGMLR and GMAP. It
is more accurate on simulated long reads and produces biologically
meaningful alignment ready for downstream analyses. For >100bp Illumina
short reads, minimap2 is three times as fast as BWA-MEM and Bowtie2, and
as accurate on simulated data. Detailed evaluations are available from
the minimap2 paper or the preprint.
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mmb
model the structure and dynamics of macromolecules
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Versions of package mmb |
Release | Version | Architectures |
bullseye | 3.2+dfsg-2+deb11u1 | amd64,arm64,ppc64el |
sid | 4.0.0+dfsg-4 | amd64,arm64 |
experimental | 4.0.0+dfsg-3.1~exp1 | amd64,arm64,armhf |
bookworm | 4.0.0+dfsg-2 | amd64,arm64 |
trixie | 4.0.0+dfsg-4 | amd64,arm64 |
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License: DFSG free
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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.
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mmseqs2
ultra fast and sensitive protein search and clustering
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Versions of package mmseqs2 |
Release | Version | Architectures |
sid | 15-6f452+ds-2 | amd64,arm64,mips64el,ppc64el,riscv64 |
bookworm | 14-7e284+ds-1 | amd64,arm64,mips64el,ppc64el |
trixie | 15-6f452+ds-2 | amd64,arm64,mips64el,ppc64el,riscv64 |
bullseye | 12-113e3+ds-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
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License: DFSG free
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MMseqs2 (Many-against-Many sequence searching) is a software suite to
search and cluster huge proteins/nucleotide sequence sets. MMseqs2 is
open source GPL-licensed software implemented in C++ for Linux, MacOS,
and (as beta version, via cygwin) Windows. The software is designed to
run on multiple cores and servers and exhibits very good scalability.
MMseqs2 can run 10000 times faster than BLAST. At 100 times its speed it
achieves almost the same sensitivity. It can perform profile searches
with the same sensitivity as PSI-BLAST at over 400 times its speed.
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multiqc
output integration for RNA sequencing across tools and samples
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Versions of package multiqc |
Release | Version | Architectures |
trixie | 1.21+dfsg-2 | all |
bookworm | 1.14+dfsg-1 | all |
bullseye | 1.9+dfsg-3 | all |
sid | 1.21+dfsg-2 | all |
upstream | 1.25.1 |
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License: DFSG free
|
The sequencing of DNA or RNA with current high-throughput technologies
involves an array of tools and these are applied over a range of samples.
It is easy to loose oversight. And gathering the data and forwarding
them in a readable manner to the individuals who took the samples is
a challenge for a tool in itself. Well. Here it is.
MultiQC aggregates the output of multiple tools into a single report.
Reports are generated by scanning given directories for recognised log
files. These are parsed and a single HTML report is generated summarising
the statistics for all logs found. MultiQC reports can describe multiple
analysis steps and large numbers of samples within a single plot, and
multiple analysis tools making it ideal for routine fast quality control.
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muscle
Multiple alignment program of protein sequences
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Versions of package muscle |
Release | Version | Architectures |
sid | 5.1.0-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 3.8.1551-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 5.1.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 5.1.0-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster | 3.8.1551-2 | amd64,arm64,armhf,i386 |
stretch | 3.8.31+dfsg-2 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
jessie | 3.8.31-1 | amd64,armel,armhf,i386 |
upstream | 5.3 |
Debtags of package muscle: |
biology | format:aln, nuceleic-acids, peptidic |
field | biology, biology:bioinformatics |
interface | commandline |
role | program |
scope | utility |
use | comparing |
works-with-format | plaintext |
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License: DFSG free
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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.
Muscle v5 is a major re-write of MUSCLE based on new algorithms.
Users should be aware that command line arguments compared to version
3.x of MUSCLE have changed!
Highest accuracy, scalable to thousands of sequences
Compared to previous versions, Muscle v5 is much more accurate, is often
faster, and scales to much larger datasets. At the time of writing (late
2021), Muscle v5 has the highest scores on multiple alignment benchmarks
including Balibase, Bralibase, Prefab and Balifam. It can align tens of
thousands of sequences with high accuracy on a low-cost commodity computer
(say, an 8-core Intel CPU with 32 Gb RAM). On large datasets, Muscle v5
is 20-30% more accurate than MAFFT and Clustal-Omega.
Alignment ensembles
Muscle v5 can generate ensembles of high-accuracy alternative alignments.
All replicates have equal average accuracy on benchmark test, including
the MSA made with default parameters. By comparing results of downstream
analysis (trees, structure prediction...) on different replicates, you can
assess the effects of alignment errors on your study.
Topics: Sequence analysis
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muscle3
multiple alignment program of protein sequences
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Versions of package muscle3 |
Release | Version | Architectures |
bookworm | 3.8.1551-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 3.8.1551-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 3.8.1551-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
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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 is version 3 of the muscle program. It is a different program
than muscle version 5 which is packaged as muscle in Debian.
Topics: Sequence analysis
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nanofilt
filtering and trimming of long read sequencing data
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Versions of package nanofilt |
Release | Version | Architectures |
trixie | 2.8.0-1 | all |
bullseye | 2.6.0-3 | all |
sid | 2.8.0-1 | all |
bookworm | 2.8.0-1 | all |
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License: DFSG free
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Filtering and trimming of long read sequencing data. Filtering on
quality and/or read length, and optional trimming after passing filters.
Reads from stdin, writes to stdout. Optionally reads directly from an
uncompressed file specified on the command line.
Intended to be used:
1. directly after fastq extraction.
2. prior to mapping.
3. in a stream between extraction and mapping.
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nanolyse
remove lambda phage reads from a fastq file
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Versions of package nanolyse |
Release | Version | Architectures |
bullseye | 1.2.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.2.0-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.2.0-4 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 1.2.0-4 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
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License: DFSG free
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NanoLyse is a tool for rapid removal of contaminant DNA, using the
Minimap2 aligner through the mappy Python binding. A typical application
would be the removal of the lambda phage control DNA fragment supplied
by ONT, for which the reference sequence is included in the package.
However, this approach may lead to unwanted loss of reads from regions
highly homologous to the lambda phage genome.
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nanook
pre- and post-alignment analysis of nanopore sequencing data
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Versions of package nanook |
Release | Version | Architectures |
buster | 1.33+dfsg-1 | all |
stretch-backports | 1.33+dfsg-1~bpo9+1 | all |
bookworm | 1.33+dfsg-5 | all |
trixie | 1.33+dfsg-5 | all |
bullseye | 1.33+dfsg-2.1 | all |
sid | 1.33+dfsg-5 | all |
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License: DFSG free
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NanoOK is a flexible, multi-reference software for pre- and post-
alignment analysis of nanopore sequencing data, quality and error
profiles.
NanoOK (pronounced na-nook) is a tool for extraction, alignment and
analysis of Nanopore reads. NanoOK will extract reads as FASTA or FASTQ
files, align them (with a choice of alignment tools), then generate a
comprehensive multi-page PDF report containing yield, accuracy and
quality analysis. Along the way, it generates plain text files which can
be used for further analysis, as well as graphs suitable for inclusion
in presentations and papers.
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nanopolish
consensus caller for nanopore sequencing data
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Versions of package nanopolish |
Release | Version | Architectures |
stretch | 0.5.0-1 | amd64,arm64,armel,i386,mips64el,mipsel,ppc64el |
sid | 0.14.0-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
buster | 0.11.0-2 | amd64 |
stretch-backports | 0.10.2-1~bpo9+1 | amd64 |
bullseye | 0.13.2-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 0.14.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
trixie | 0.14.0-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
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License: DFSG free
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Nanopolish uses a signal-level hidden Markov model for consensus calling
of nanopore genome sequencing data. It can perform signal-level analysis
of Oxford Nanopore sequencing data. Nanopolish can calculate an improved
consensus sequence for a draft genome assembly, detect base
modifications, call SNPs and indels with respect to a reference genome
and more.
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nanosv
structural variant caller for nanopore data
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Versions of package nanosv |
Release | Version | Architectures |
bullseye | 1.2.4+git20190409.c1ae30c-3 | all |
bookworm | 1.2.4+git20190409.c1ae30c-6 | all |
trixie | 1.2.4+git20190409.c1ae30c-6 | all |
sid | 1.2.4+git20190409.c1ae30c-6 | all |
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License: DFSG free
|
NanoSV is a software package that can be used to identify structural
genomic variations in long-read sequencing data, such as data produced
by Oxford Nanopore Technologies’ MinION, GridION or PromethION
instruments, or Pacific Biosciences RSII or Sequel sequencers. NanoSV
has been extensively tested using Oxford Nanopore MinION sequencing data.
Please cite:
Mircea Cretu Stancu, Markus J. van Roosmalen, Ivo Renkens, Marleen M. Nieboer, Sjors Middelkamp, Joep de Ligt, Giulia Pregno, Daniela Giachino, Giorgia Mandrile, Jose Espejo Valle-Inclan, Jerome Korzelius, Ewart de Bruijn, Edwin Cuppen, Michael E. Talkowski, Tobias Marschall, Jeroen de Ridder and Wigard P. Kloosterman:
Mapping and phasing of structural variation in patient genomes using nanopore sequencing..
(eprint)
Nature Communications
8:1326
(2017)
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ncbi-blast+
next generation suite of BLAST sequence search tools
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Versions of package ncbi-blast+ |
Release | Version | Architectures |
trixie | 2.16.0+ds-6 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch | 2.6.0-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
sid | 2.16.0+ds-6 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster-backports | 2.9.0-4~bpo10+1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
stretch-backports-sloppy | 2.9.0-3~bpo9+1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
jessie | 2.2.29-3 | amd64,armel,armhf,i386 |
buster | 2.8.1-1+deb10u1 | amd64,arm64,armhf,i386 |
bullseye | 2.11.0+ds-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 2.12.0+ds-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye-backports | 2.12.0+ds-3~bpo11+1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
Debtags of package ncbi-blast+: |
field | biology, biology:bioinformatics |
interface | commandline |
role | program |
use | analysing |
works-with | biological-sequence |
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License: DFSG free
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The Basic Local Alignment Search Tool (BLAST) is the most widely
used sequence similarity tool. There are versions of BLAST that
compare protein queries to protein databases, nucleotide queries
to nucleotide databases, as well as versions that translate nucleotide
queries or databases in all six frames and compare to protein databases
or queries.
PSI-BLAST produces a position-specific-scoring-matrix (PSSM) starting
with a protein query, and then uses that PSSM to perform further searches.
It is also possible to compare a protein or nucleotide query to a
database of PSSM’s.
The NCBI supports a BLAST web page at blast.ncbi.nlm.nih.gov as well as
a network service.
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ngmlr
CoNvex Gap-cost alignMents for Long Reads
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Versions of package ngmlr |
Release | Version | Architectures |
bullseye | 0.2.7+dfsg-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 0.2.7+git20210816.a2a31fb+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
experimental | 0.2.7+git20210816.a2a31fb+dfsg-4~0exp0simde | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 0.2.7+git20210816.a2a31fb+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 0.2.7+git20210816.a2a31fb+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
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License: DFSG free
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Ngmlr is a long-read mapper designed to sensitively align PacBilo or
Oxford Nanopore to (large) reference genomes. It was designed to quickly
and correctly align the reads, including those spanning (complex)
structural variations. Ngmlr uses an SV aware k-mer search to find
approximate mapping locations for a read and then a banded Smith-
Waterman alignment algorithm to compute the final alignment. Ngmlr uses
a convex gap cost model that penalizes gap extensions for longer gaps
less than for shorter ones to compute precise alignments.
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nthash
Methods to evaluate runtime and uniformity tests for hashing methods
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Versions of package nthash |
Release | Version | Architectures |
bookworm | 2.3.0+dfsg-1 | amd64,arm64,mips64el,ppc64el |
trixie | 2.3.0+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64 |
sid | 2.3.0+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64 |
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License: DFSG free
|
This contains nttest binary which has options for evaluating
runtimes and uniformity for different hashing methods.
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odil
C++11 library for the DICOM standard (application)
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Versions of package odil |
Release | Version | Architectures |
stretch | 0.7.3-1 | all |
bullseye | 0.12.1-1 | all |
buster | 0.10.0-3 | all |
sid | 0.12.2-5 | all |
trixie | 0.12.2-5 | all |
bookworm | 0.12.2-2 | all |
upstream | 0.13.0 |
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License: DFSG free
|
Odil leverages C++ constructs to provide a user-friendly API of the
different parts of the DICOM standard. Included in Odil are exception-based
error handling, generic access to datasets elements, standard JSON and XML
representation of datasets, and generic implementation of messages, clients
and servers for the various DICOM protocols.
This package contains the command-line application.
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orthanc
Lightweight, RESTful DICOM server for medical imaging
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Versions of package orthanc |
Release | Version | Architectures |
buster | 1.5.6+dfsg-1 | amd64,arm64,armhf,i386 |
jessie | 0.8.4+dfsg-1 | amd64,armel,armhf,i386 |
stretch | 1.2.0+dfsg-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster-security | 1.5.6+dfsg-1+deb10u1 | amd64,arm64,armhf,i386 |
bullseye | 1.9.2+really1.9.1+dfsg-1+deb11u1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye-security | 1.9.2+really1.9.1+dfsg-1+deb11u1 | amd64,arm64,armhf,i386 |
bookworm | 1.10.1+dfsg-2+deb12u1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm-security | 1.10.1+dfsg-2+deb12u1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.12.4+dfsg-4 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 1.12.4+dfsg-4 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
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License: DFSG free
|
Orthanc aims at providing a simple, yet powerful DICOM server for
medical imaging. Orthanc can turn any computer running Windows or
Linux into a Vendor Neutral Archive (in other words, a mini-PACS
system). Its architecture is lightweight, meaning that no complex
database administration is required, nor the installation of
third-party dependencies.
What makes Orthanc unique is the fact that it provides a RESTful
API. Thanks to this major feature, it is possible to drive Orthanc
from any computer language. The DICOM tags of the stored medical
images can be downloaded in the JSON file format. Furthermore,
standard PNG images can be generated on-the-fly from the DICOM
instances by Orthanc.
Orthanc lets its users focus on the content of the DICOM files,
hiding the complexity of the DICOM format and of the DICOM protocol.
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orthanc-dicomweb
Plugin to extend Orthanc with support of WADO and DICOMweb
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Versions of package orthanc-dicomweb |
Release | Version | Architectures |
buster | 0.6+dfsg-1 | amd64,arm64,armhf,i386 |
bookworm | 1.7+dfsg-6 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.17+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch | 0.3+dfsg-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
trixie | 1.17+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.5+dfsg-3 | amd64,arm64,armhf,i386,mips64el,mipsel,ppc64el,s390x |
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License: DFSG free
|
Orthanc DICOMweb is a plugin to Orthanc, the lightweight, RESTful Vendor
Neutral Archive for medical imaging. It extends the Orthanc core with
support of the WADO (now known as WADO-URI) and DICOMweb (QIDO-RS,
STOW-RS, WADO-RS) standards.
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orthanc-python
Develop plugins for Orthanc using the Python programming language
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Versions of package orthanc-python |
Release | Version | Architectures |
bullseye | 3.1+ds-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 4.3+ds-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 4.3+ds-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 4.0+ds-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
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License: DFSG free
|
This plugin can be used to write Orthanc plugins using the Python programming
language instead of the more complex C/C++ programming languages. It can be
used to gain access to Python modules directly in Orthanc.
This plugin can be of great help to anyone wishing to automate her imaging
workflow, to design/train new machine learning algorithms, or to deploy AI
systems directly in clinical setups.
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orthanc-wsi
Whole-slide imaging support for Orthanc (digital pathology)
|
Versions of package orthanc-wsi |
Release | Version | Architectures |
bullseye | 1.0-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.1-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 0.6-2 | amd64,arm64,armhf,i386 |
sid | 2.1+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 2.1+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
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License: DFSG free
|
Orthanc-WSI brings support of whole-slide imaging for digital
pathology into Orthanc, the lightweight, RESTful Vendor Neutral
Archive for medical imaging.
This package contains two command-line tools to convert whole-slide
images to and from DICOM. Support for proprietary file formats is
available through OpenSlide. The package also contains an Orthanc
plugin to display such DICOM images by any standard Web browser. The
implementation follows DICOM Supplement 145.
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paleomix
pipelines and tools for the processing of ancient and modern HTS data
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Versions of package paleomix |
Release | Version | Architectures |
sid | 1.3.8-2 | amd64,arm64 |
bullseye | 1.3.2-1 | amd64,arm64,mips64el,ppc64el |
buster | 1.2.13.3-1 | amd64 |
bookworm | 1.3.7-3 | amd64,arm64 |
trixie | 1.3.8-2 | amd64,arm64 |
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License: DFSG free
|
The PALEOMIX pipelines are a set of pipelines and tools designed to aid
the rapid processing of High-Throughput Sequencing (HTS) data: The BAM
pipeline processes de-multiplexed reads from one or more samples,
through sequence processing and alignment, to generate BAM alignment
files useful in downstream analyses; the Phylogenetic pipeline carries
out genotyping and phylogenetic inference on BAM alignment files, either
produced using the BAM pipeline or generated elsewhere; and the Zonkey
pipeline carries out a suite of analyses on low coverage equine
alignments, in order to detect the presence of F1-hybrids in
archaeological assemblages. In addition, PALEOMIX aids in metagenomic
analysis of the extracts.
The pipelines have been designed with ancient DNA (aDNA) in mind, and
includes several features especially useful for the analyses of ancient
samples, but can all be for the processing of modern samples, in order
to ensure consistent data processing.
Please cite:
Mikkel Schubert, Luca Ermini, Clio Der Sarkissian, Hákon Jónsson, Aurélien Ginolhac, Robert Schaefer, Michael D Martin, Ruth Fernández, Martin Kircher, Molly McCue, Eske Willerslev and Ludovic Orlando:
Characterization of ancient and modern genomes by SNP detection and phylogenomic and metagenomic analysis using PALEOMIX.
(PubMed)
Nature Protocols
9(5):1056-82
(2014)
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parallel-fastq-dump
parallel fastq-dump wrapper
|
Versions of package parallel-fastq-dump |
Release | Version | Architectures |
sid | 0.6.7-3 | amd64,arm64 |
bullseye | 0.6.6-3 | amd64 |
bookworm | 0.6.7-3 | amd64,arm64 |
trixie | 0.6.7-3 | amd64,arm64 |
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License: DFSG free
|
NCBI fastq-dump can be very slow sometimes, even if you have the resources
(network, IO, CPU) to go faster, even if you already downloaded the sra
file. This tool speeds up the process by dividing the work into multiple
threads.
This is possible because fastq-dump have options (-N and -X) to query
specific ranges of the sra file, this tool works by dividing the work
into the requested number of threads, running multiple fastq-dump in
parallel and concatenating the results back together, as if you had just
executed a plain fastq-dump call.
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parasail
Aligner based on libparasail
|
Versions of package parasail |
Release | Version | Architectures |
bullseye | 2.4.3+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 2.6+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 2.6.2+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 2.6.2+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
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License: DFSG free
|
This package contains a command-line aligner based on
libparasail. 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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picard-tools
Command line tools to manipulate SAM and BAM files
|
Versions of package picard-tools |
Release | Version | Architectures |
trixie | 3.1.1+dfsg-1 | all |
bullseye | 2.24.1+dfsg-1 | all |
stretch | 2.8.1+dfsg-1 | all |
buster | 2.18.25+dfsg-2 | amd64 |
bookworm | 2.27.5+dfsg-2 | all |
jessie | 1.113-1 | all |
sid | 3.1.1+dfsg-1 | all |
upstream | 3.3.0 |
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License: DFSG free
|
SAM (Sequence Alignment/Map) format is a generic format for storing
large nucleotide sequence alignments. Picard Tools includes these
utilities to manipulate SAM and BAM files:
AddCommentsToBam FifoBuffer
AddOrReplaceReadGroups FilterSamReads
BaitDesigner FilterVcf
BamIndexStats FixMateInformation
GatherBamFiles
BedToIntervalList GatherVcfs
BuildBamIndex GenotypeConcordance
CalculateHsMetrics IlluminaBasecallsToFastq
CalculateReadGroupChecksum IlluminaBasecallsToSam
CheckIlluminaDirectory LiftOverIntervalList
CheckTerminatorBlock LiftoverVcf
CleanSam MakeSitesOnlyVcf
CollectAlignmentSummaryMetrics MarkDuplicates
CollectBaseDistributionByCycle MarkDuplicatesWithMateCigar
CollectGcBiasMetrics MarkIlluminaAdapters
CollectHiSeqXPfFailMetrics MeanQualityByCycle
CollectIlluminaBasecallingMetrics MergeBamAlignment
CollectIlluminaLaneMetrics MergeSamFiles
CollectInsertSizeMetrics MergeVcfs
CollectJumpingLibraryMetrics NormalizeFasta
CollectMultipleMetrics PositionBasedDownsampleSam
CollectOxoGMetrics QualityScoreDistribution
CollectQualityYieldMetrics RenameSampleInVcf
CollectRawWgsMetrics ReorderSam
CollectRnaSeqMetrics ReplaceSamHeader
CollectRrbsMetrics RevertOriginalBaseQualitiesAndAddMateCigar
CollectSequencingArtifactMetrics RevertSam
CollectTargetedPcrMetrics SamFormatConverter
CollectVariantCallingMetrics SamToFastq
CollectWgsMetrics ScatterIntervalsByNs
CompareMetrics SortSam
CompareSAMs SortVcf
ConvertSequencingArtifactToOxoG SplitSamByLibrary
CreateSequenceDictionary SplitVcfs
DownsampleSam UpdateVcfSequenceDictionary
EstimateLibraryComplexity ValidateSamFile
ExtractIlluminaBarcodes VcfFormatConverter
ExtractSequences VcfToIntervalList
FastqToSam ViewSam
The package is enhanced by the following packages:
multiqc
Please cite:
Broad Institute:
Picard toolkit.
Broad Institute, GitHub repository
(2019)
Topics: Sequencing; Document, record and content management
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picopore
lossless compression of Nanopore files
|
Versions of package picopore |
Release | Version | Architectures |
trixie | 1.2.0-3 | all |
sid | 1.2.0-3 | all |
bookworm | 1.2.0-2 | all |
bullseye | 1.2.0-2 | all |
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License: DFSG free
|
The Nanopore is a device to determine the sequences of single moleculres
of DNA. No amplification. The output is gigantic and tools like this
one help to reduce it.
Over time, other means have substitute the need for this one. Upstream
has halted development. Some tutorials and pipelines of the Nanopore still
refer to it, though.
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pigx-rnaseq
pipeline for checkpointed and distributed RNA-seq analyses
|
Versions of package pigx-rnaseq |
Release | Version | Architectures |
bullseye | 0.0.10+ds-2 | all |
bookworm | 0.1.0-1.1 | all |
sid | 0.1.1-1 | all |
trixie | 0.1.1-1 | all |
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License: DFSG free
|
This package provides a automated workflow for the automated analysis of
RNA-seq experiments. A series of well-accecpted tools are connected in
Python scripts and controlled via snakemake. This supports the parallel
execution of these workflows and provides checkpointing, such that
interrupted workflows can take up their work again.
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pinfish
Collection of tools to annotate genomes using long read transcriptomics data
|
Versions of package pinfish |
Release | Version | Architectures |
bookworm | 0.1.0+ds-3 | amd64,arm64,mips64el,ppc64el,s390x |
sid | 0.1.0+ds-4 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 0.1.0+ds-4 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 0.1.0+ds-2 | amd64,arm64,mips64el,ppc64el,s390x |
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License: DFSG free
|
The toolchain is composed of the following tools:
1. spliced_bam2gff - a tool for converting sorted BAM
files containing spliced alignments
into GFF2 format. Each read will be represented as a distinct
transcript. This tool comes handy when visualizing spliced
reads at particular loci and to provide input to the rest
of the toolchain.
-
cluster_gff - this tool takes a sorted GFF2 file as
input and clusters together reads having similar
exon/intron structure and creates a rough consensus
of the clusters by taking the median of exon
boundaries from all transcripts in the cluster.
-
polish_clusters - this tool takes the cluster
definitions generated by cluster_gff and for each
cluster creates an error corrected read by mapping
all reads on the read with the median length
and polishing it using racon. The polished reads
can be mapped to the genome using minimap2 or GMAP.
-
collapse_partials - this tool takes GFFs generated
by either cluster_gff or polish_clusters and filters
out transcripts which are likely to be based on RNA
degradation products from the 5' end. The tool clusters
the input transcripts into "loci" by the 3' ends and
discards transcripts which have a compatible transcripts
in the loci with more exons.
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plasmidid
mapping-based, assembly-assisted plasmid identification tool
|
Versions of package plasmidid |
Release | Version | Architectures |
trixie | 1.6.5+dfsg-2 | amd64,arm64 |
bullseye | 1.6.3+dfsg-3 | amd64 |
sid | 1.6.5+dfsg-2 | amd64,arm64 |
bookworm | 1.6.5+dfsg-2 | amd64 |
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License: DFSG free
|
PlasmidID is a mapping-based, assembly-assisted plasmid identification
tool that analyzes and gives graphic solution for plasmid
identification.
PlasmidID is a computational pipeline that maps Illumina reads over
plasmid database sequences. The k-mer filtered, most covered
sequences are clustered by identity to avoid redundancy and the
longest are used as scaffold for plasmid reconstruction. Reads are
assembled and annotated by automatic and specific annotation. All
information generated from mapping, assembly, annotation and local
alignment analyses is gathered and accurately represented in a
circular image which allow user to determine plasmidic composition in
any bacterial sample.
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plink1.9
whole-genome association analysis toolset
|
Versions of package plink1.9 |
Release | Version | Architectures |
buster | 1.90~b6.6-181012-1 | amd64,armhf,i386 |
trixie | 1.90~b7.2-231211-1 | amd64,armel,armhf,i386 |
bookworm | 1.90~b6.26-220402-1 | amd64,armel,armhf,i386,mipsel |
bullseye | 1.90~b6.21-201019-1 | amd64,armel,armhf,i386,mipsel |
stretch | 1.90~b3.45-170113-1 | amd64,armel,armhf,i386,mipsel |
sid | 1.90~b7.2-231211-1 | amd64,armel,armhf,i386 |
|
License: DFSG free
|
plink expects as input the data from SNP (single nucleotide polymorphism)
chips of many individuals and their phenotypical description of a disease.
It finds associations of single or pairs of DNA variations with a phenotype
and can retrieve SNP annotation from an online source.
SNPs can evaluated individually or as pairs for their association with the
disease phenotypes. The joint investigation of copy number variations is
supported. A variety of statistical tests have been implemented.
plink1.9 is a comprehensive update of plink with new algorithms and new
methods, faster and less memory consumer than the first plink.
Please note: The executable was renamed to plink1.9
because of a name clash. Please read more about this
in /usr/share/doc/plink1.9/README.Debian.
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plink2
whole-genome association analysis toolset
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Versions of package plink2 |
Release | Version | Architectures |
trixie | 2.00~a5.8-231123+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 2.00~a3.5-220809+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 2.00~a3-210203+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 2.00~a5.8-231123+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
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License: DFSG free
|
plink expects as input the data from SNP (single nucleotide polymorphism)
chips of many individuals and their phenotypical description of a disease.
It finds associations of single or pairs of DNA variations with a phenotype
and can retrieve SNP annotation from an online source.
SNPs can evaluated individually or as pairs for their association with the
disease phenotypes. The joint investigation of copy number variations is
supported. A variety of statistical tests have been implemented.
plink2 is a comprehensive update of plink and plink1.9 with new algorithms
and new methods, faster and less memory consumer than the first plink.
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plip
fully automated protein-ligand interaction profiler
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Versions of package plip |
Release | Version | Architectures |
buster | 1.4.3~b+dfsg-2 | all |
sid | 2.3.0+dfsg-2 | all |
trixie | 2.3.0+dfsg-2 | all |
bookworm | 2.2.2+dfsg-1 | all |
bullseye | 2.1.7+dfsg-1 | all |
stretch | 1.3.3+dfsg-1 | all |
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License: DFSG free
|
The Protein-Ligand Interaction Profiler (PLIP) is a tool to analyze
and visualize protein-ligand interactions in PDB files.
Features include:
- Detection of eight different types of noncovalent interactions
- Automatic detection of relevant ligands in a PDB file
- Direct download of PDB structures from wwPDB server if valid
PDB ID is given
- Processing of custom PDB files containing protein-ligand complexes
(e.g. from docking)
- No need for special preparation of a PDB file, works out of the box
- Atom-level interaction reports in rST and XML formats for easy parsing
- Generation of PyMOL session files (.pse) for each pairing, enabling easy
preparation of images for publications and talks
- Rendering of preview image for each ligand and its interactions
with the protein
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porechop
adapter trimmer for Oxford Nanopore reads
|
Versions of package porechop |
Release | Version | Architectures |
trixie | 0.2.4+dfsg-6 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 0.2.4+dfsg-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 0.2.4+dfsg-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 0.2.4+dfsg-1 | amd64,arm64,armhf,i386 |
sid | 0.2.4+dfsg-6 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
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License: DFSG free
|
Porechop is a tool for finding and removing adapters from Oxford
Nanopore reads. Adapters on the ends of reads are trimmed off, and
when a read has an adapter in its middle, it is treated as chimeric
and chopped into separate reads. Porechop performs thorough
alignments to effectively find adapters, even at low sequence
identity.
Porechop also supports demultiplexing of Nanopore reads that were
barcoded with the Native Barcoding Kit, PCR Barcoding Kit or Rapid
Barcoding Kit.
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poretools
toolkit for nanopore nucleotide sequencing data
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Versions of package poretools |
Release | Version | Architectures |
trixie | 0.6.0+dfsg-7 | all |
buster | 0.6.0+dfsg-3 | all |
stretch | 0.6.0+dfsg-2 | all |
bullseye | 0.6.0+dfsg-5 | all |
sid | 0.6.0+dfsg-7 | all |
bookworm | 0.6.0+dfsg-6 | all |
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License: DFSG free
|
poretools is a flexible toolkit for exploring datasets generated by nanopore
sequencing devices from MinION for the purposes of quality control and
downstream analysis. Poretools operates directly on the native FAST5 (a
variant of the HDF5 standard) file format produced by ONT and provides a
wealth of format conversion utilities and data exploration and visualization
tools.
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pplacer
phylogenetic placement and downstream analysis
|
Versions of package pplacer |
Release | Version | Architectures |
sid | 1.1~alpha19-8 | amd64,arm64,ppc64el,riscv64,s390x |
bullseye | 1.1~alpha19-4 | amd64,arm64,ppc64el,s390x |
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License: DFSG free
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Pplacer places reads on a phylogenetic tree. guppy (Grand Unified
Phylogenetic Placement Yanalyzer) yanalyzes them. rppr is a helpful tool
for working with reference packages.
Pplacer places query sequences on a fixed reference phylogenetic tree to
maximize phylogenetic likelihood or posterior probability according to a
reference alignment. Pplacer is designed to be fast, to give useful
information about uncertainty, and to offer advanced visualization and
downstream analysis.
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presto
toolkit for processing B and T cell sequences
|
Versions of package presto |
Release | Version | Architectures |
bookworm | 0.7.1-1 | all |
sid | 0.7.2-1 | all |
trixie | 0.7.2-1 | all |
bullseye | 0.6.2-1 | 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.
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prinseq-lite
PReprocessing and INformation of SEQuence data (lite version)
|
Versions of package prinseq-lite |
Release | Version | Architectures |
trixie | 0.20.4-6 | all |
bullseye | 0.20.4-6 | all |
sid | 0.20.4-6 | all |
bookworm | 0.20.4-6 | all |
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License: DFSG free
|
PRINSEQ will help you to preprocess your genomic or metagenomic sequence data
in FASTA or FASTQ format. It is a tool that generates summary statistics of
sequence and quality data and that is used to filter, reformat and trim
next-generation sequence data. It is particular designed for 454/Roche data,
but can also be used for other types of sequence data. The standalone version
is primarily designed for data preprocessing and does not generate summary
statistics in graphical form.
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prokka
rapid annotation of prokaryotic genomes
|
Versions of package prokka |
Release | Version | Architectures |
sid | 1.14.6+dfsg-6 | all |
bullseye | 1.14.6+dfsg-3 | amd64 |
trixie | 1.14.6+dfsg-6 | all |
bookworm | 1.14.6+dfsg-4 | amd64 |
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License: DFSG free
|
A typical 4 Mbp genome can be fully annotated in less than 10 minutes on a
quad-core computer, and scales well to 32 core SMP systems. It produces GFF3,
GBK and SQN files that are ready for editing in Sequin and ultimately submitted
to Genbank/DDJB/ENA.
The package is enhanced by the following packages:
multiqc
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proteinortho
Detection of (Co-)orthologs in large-scale protein analysis
|
Versions of package proteinortho |
Release | Version | Architectures |
stretch | 5.15+dfsg-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
sid | 6.3.1+dfsg-1 | amd64,arm64,ppc64el,riscv64,s390x |
trixie | 6.3.1+dfsg-1 | amd64,arm64,ppc64el,riscv64,s390x |
buster | 5.16.b+dfsg-1 | amd64,arm64,armhf,i386 |
bullseye | 6.0.28+dfsg-1 | amd64,arm64,ppc64el,s390x |
bookworm | 6.1.7+dfsg-1 | amd64,arm64,ppc64el,s390x |
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License: DFSG free
|
Proteinortho is a stand-alone tool that is geared towards large datasets
and makes use of distributed computing techniques when run on multi-core
hardware. It implements an extended version of the reciprocal best
alignment heuristic. Proteinortho was applied to compute orthologous
proteins in the complete set of all 717 eubacterial genomes available at
NCBI at the beginning of 2009. Authors succeeded identifying thirty
proteins present in 99% of all bacterial proteomes.
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pybedtools-bin
Scripts produced for pybedtools
|
Versions of package pybedtools-bin |
Release | Version | Architectures |
sid | 0.10.0-2 | all |
trixie | 0.10.0-2 | all |
bookworm | 0.9.0-4 | all |
bullseye | 0.8.0-5 | all |
buster | 0.8.0-1 | all |
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License: DFSG free
|
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 package provides scripts that are executable with the
Python 3 version of this package.
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pycoqc
computes metrics and generates Interactive QC plots
|
Versions of package pycoqc |
Release | Version | Architectures |
trixie | 2.5.2+dfsg-3 | all |
bookworm | 2.5.2+dfsg-3 | all |
sid | 2.5.2+dfsg-3 | all |
bullseye | 2.5.2+dfsg-1 | all |
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License: DFSG free
|
PycoQC computes metrics and generates interactive QC plots for Oxford
Nanopore technologies sequencing data
PycoQC relies on the sequencing_summary.txt file generated by Albacore
and Guppy, but if needed it can also generates a summary file from
basecalled fast5 files. The package supports 1D and 1D2 runs generated
with Minion, Gridion and Promethion devices and basecalled with Albacore
1.2.1+ or Guppy 2.1.3+
The package is enhanced by the following packages:
multiqc
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python3-biom-format
Biological Observation Matrix (BIOM) format (Python 3)
|
Versions of package python3-biom-format |
Release | Version | Architectures |
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 |
bullseye | 2.1.10-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
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 |
|
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-biopython
Python3 library for bioinformatics
|
Versions of package python3-biopython |
Release | Version | Architectures |
jessie | 1.64+dfsg-5 | amd64,armel,armhf,i386 |
bookworm | 1.80+dfsg-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 1.78+dfsg-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 1.73+dfsg-1 | amd64,arm64,armhf,i386 |
stretch | 1.68+dfsg-3 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
trixie | 1.84+dfsg-4 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 1.84+dfsg-4 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
|
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-bx
library to manage genomic data and its alignment
|
Versions of package python3-bx |
Release | Version | Architectures |
trixie | 0.13.0-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 0.13.0-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster | 0.8.2-1 | amd64,arm64,armhf,i386 |
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 |
|
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 |
bookworm | 1.5.6+ds-1 | all |
sid | 1.5.6+ds-2 | all |
bullseye | 1.5.6+ds-1 | all |
trixie | 1.5.6+ds-1 | all |
|
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-cogent3
framework for genomic biology
|
Versions of package python3-cogent3 |
Release | Version | Architectures |
sid | 2024.5.7a1+dfsg-3 | amd64,arm64,mips64el,ppc64el |
sid | 2023.12.15a1+dfsg-1 | s390x |
bullseye | 2020.12.21a+dfsg-4+deb11u1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 2023.2.12a1+dfsg-2+deb12u1 | amd64,arm64,mips64el,ppc64el,s390x |
upstream | 2024.7.19a9 |
|
License: DFSG free
|
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
|
Versions of package python3-cooler |
Release | Version | Architectures |
bookworm | 0.9.1-1 | amd64,arm64,mips64el,ppc64el |
sid | 0.10.2-1 | amd64,arm64,mips64el,ppc64el,riscv64 |
trixie | 0.10.2-1 | amd64,arm64,mips64el,ppc64el,riscv64 |
|
License: DFSG free
|
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-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 |
sid | 0.31.1-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster | 0.10.4-1 | amd64,arm64,armhf,i386 |
bookworm | 0.30.18-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 0.31.1-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
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License: DFSG free
|
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-depinfo
retrieve and print Python 3 package dependencies
|
Versions of package python3-depinfo |
Release | Version | Architectures |
bookworm | 2.2.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 1.4.0-1 | amd64,arm64,armhf,i386 |
trixie | 2.2.0-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 2.2.0-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.6.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
upstream | 2.2.0rc3 |
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License: DFSG free
|
This is a utility Python package intended for other library packages.
It provides a function that when called with your package name,
will print platform and dependency information.
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python3-drmaa
interface to DRMAA-compliant distributed resource management systems
|
Versions of package python3-drmaa |
Release | Version | Architectures |
sid | 0.7.9-3 | all |
bookworm | 0.7.9-3 | all |
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License: DFSG free
|
This is a Python implementation of the Distributed Resource Management (DRM)
Application API (DRMAA). It provides all high-level functionality necessary
to consign a job to a DRM system (e.g. Sun Gridengine), including common
operations on jobs, such as termination or suspension.
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python3-etelemetry
lightweight Python3 client to communicate with the etelemetry server
|
Versions of package python3-etelemetry |
Release | Version | Architectures |
trixie | 0.3.1-1 | all |
bullseye | 0.2.0-4 | all |
sid | 0.3.1-1 | all |
bookworm | 0.3.0-3 | all |
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License: DFSG free
|
This Python3 package provides a lightweight Python3 client interface to
communicate with the etelemetry server. It can be used for nipy or
nipype.
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python3-gffutils
Work with GFF and GTF files in a flexible database framework
|
Versions of package python3-gffutils |
Release | Version | Architectures |
trixie | 0.13-1 | all |
bookworm | 0.11.1-3 | all |
buster | 0.9-1 | all |
bullseye | 0.10.1-2 | all |
sid | 0.13-1 | all |
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License: DFSG free
|
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-htseq
Python3 high-throughput genome sequencing read analysis utilities
|
Versions of package python3-htseq |
Release | Version | Architectures |
buster | 0.11.2-1 | amd64,arm64 |
bookworm | 1.99.2-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
trixie | 2.0.5-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
bullseye | 0.13.5-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
sid | 2.0.5-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
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License: DFSG free
|
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-nanoget
extract information from Oxford Nanopore sequencing data and alignments
|
Versions of package python3-nanoget |
Release | Version | Architectures |
bookworm | 1.16.1-2 | all |
bullseye | 1.12.2-4 | all |
trixie | 1.19.3-1 | all |
sid | 1.19.3-1 | all |
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License: DFSG free
|
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-nanomath
simple math function for other Oxford Nanopore processing scripts
|
Versions of package python3-nanomath |
Release | Version | Architectures |
bookworm | 1.2.1+ds-1 | all |
sid | 1.2.1+ds-1 | all |
bullseye | 1.2.0+ds-1 | all |
trixie | 1.2.1+ds-1 | all |
upstream | 1.4.0 |
|
License: DFSG free
|
This Python3 module provides a few simple math and statistics functions for
other scripts processing Oxford Nanopore sequencing data.
- Calculate read N50 from a set of lengths get_N50(readlenghts)
- Remove extreme length outliers from a dataset
remove_length_outliers(dataframe, columname)
- Calculate the average Phred quality of a read ave_qual(qualscores)
- Write out the statistics report after calling readstats function
write_stats(dataframe, outputname)
- Compute a number of statistics, return a dictionary
calc_read_stats(dataframe)
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python3-pairix
1D/2D indexing and querying with a pair of genomic coordinates
|
Versions of package python3-pairix |
Release | Version | Architectures |
bullseye | 0.3.7-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
sid | 0.3.8-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
trixie | 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 |
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License: DFSG free
|
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-pairtools
Framework to process sequencing data from a Hi-C experiment
|
Versions of package python3-pairtools |
Release | Version | Architectures |
sid | 1.1.0-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
bookworm | 1.0.2-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
trixie | 1.1.0-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
bullseye | 0.3.0-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
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License: DFSG free
|
Simple and fast command-line framework to process sequencing data from a Hi-C
experiment.
Process pair-end sequence alignments and perform the following operations:
- Detect ligation junctions (a.k.a. Hi-C pairs) in aligned paired-end
sequences of Hi-C DNA molecules
- Sort .pairs files for downstream analyses
- Detect, tag and remove PCR/optical duplicates
- Generate extensive statistics of Hi-C datasets
- Select Hi-C pairs given flexibly defined criteria
- Restore .sam alignments from Hi-C pairs
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python3-pauvre
QC and genome browser plotting Oxford Nanopore and PacBio long reads
|
Versions of package python3-pauvre |
Release | Version | Architectures |
sid | 0.2.3-4 | all |
bullseye | 0.2.2-2 | all |
bookworm | 0.2.3-2 | all |
trixie | 0.2.3-4 | all |
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License: DFSG free
|
Pauvre is a plotting package designed for nanopore and PacBio long reads.
This package currently hosts four scripts for plotting and/or printing stats.
pauvre marginplot
Takes a fastq file as input and outputs a marginal histogram with a
heatmap.
pauvre stats
Takes a fastq file as input and prints out a table of stats, including
how many basepairs/reads there are for a length/mean quality cutoff.
This is also automagically called when using pauvre marginplot
pauvre redwood
Method of representing circular genomes. A redwood plot contains long
reads as "rings" on the inside, a gene annotation "cambrium/phloem",
and a RNAseq "bark". The input is .bam files for the long reads and
RNAseq data, and a .gff file for the annotation.
pauvre synteny
Makes a synteny plot of circular genomes. Finds the most parsimonius
rotation to display the synteny of all the input genomes with the
fewest crossings-over. Input is one .gff file per circular genome
and one directory of gene alignments.
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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 |
bullseye | 2.1.1+git20201023.cc0ed3d-1 | all |
sid | 2.1.1+git20220616.3f2e6c2-3 | all |
bookworm | 2.1.1+git20220616.3f2e6c2-2 | all |
upstream | 2.1.1+git20231020.28d1635 |
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License: DFSG free
|
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-pbcore
Python 3 library for processing PacBio data files
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Versions of package python3-pbcore |
Release | Version | Architectures |
trixie | 2.1.2+dfsg-9 | all |
bullseye | 1.7.1+git20200430.a127b1e+dfsg-1 | all |
bookworm | 2.1.2+dfsg-5 | all |
sid | 2.1.2+dfsg-9 | all |
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License: DFSG free
|
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-pyani
Python3 module for average nucleotide identity analyses
|
Versions of package python3-pyani |
Release | Version | Architectures |
bullseye | 0.2.10-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 0.2.12-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 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 |
upstream | 0.2.13.1 |
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License: DFSG free
|
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-pychopper
identify, orient and trim full-length Nanopore cDNA reads
|
Versions of package python3-pychopper |
Release | Version | Architectures |
bullseye | 2.5.0-1 | all |
sid | 2.7.10-1 | all |
bookworm | 2.7.2-1 | all |
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License: DFSG free
|
Pychopper v2 is a Python module to identify, orient and trim full-length
Nanopore cDNA reads. It is also able to rescue fused reads and provides
the script 'pychopper.py'. The general approach of Pychopper v2
is the following:
- Pychopper first identifies alignment hits of the primers across the
length of the sequence. The default method for doing this is using
nhmmscan with the pre-trained strand specific profile HMMs, included
with the package. Alternatively, one can use the edlib backend,
which uses a combination of global and local alignment to identify
the primers within the read.
- After identifying the primer hits by either of the backends, the
reads are divided into segments defined by two consecutive primer
hits. The score of a segment is its length if the configuration of
the flanking primer hits is valid (such as SPP,-VNP for forward reads)
or zero otherwise.
- The segments are assigned to rescued reads using a dynamic programming
algorithm maximizing the sum of used segment scores (hence the amount
of rescued bases). A crucial observation about the algorithm is that
if a segment is included as a rescued read, then the next segment
must be excluded as one of the primer hits defining it was "used
up" by the previous segment. This put constraints on the dynamic
programming graph. The arrows in read define the optimal path for
rescuing two fused reads with the a total score of l1 + l3.
A crucial parameter of Pychopper v2 is -q, which determines the
stringency of primer alignment (E-value in the case of the pHMM
backend). This can be explicitly specified by the user, however by
default it is optimized on a random sample of input reads to produce
the maximum number of classified reads.
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python3-pydicom
DICOM medical file reading and writing (Python 3)
|
Versions of package python3-pydicom |
Release | Version | Architectures |
buster | 1.2.1-1 | all |
bullseye | 2.0.0-1 | all |
bookworm | 2.3.1-1 | all |
sid | 2.4.3-1 | all |
trixie | 2.4.3-1 | all |
upstream | 3.0.1 |
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License: DFSG free
|
pydicom is a pure Python module for parsing DICOM files. DICOM is a
standard (http://medical.nema.org) for communicating medical images
and related information such as reports and radiotherapy objects.
pydicom makes it easy to read DICOM files into natural pythonic
structures for easy manipulation. Modified datasets can be written
again to DICOM format files.
This package installs the module for Python 3.
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python3-pyfaidx
efficient random access to fasta subsequences for Python 3
|
Versions of package python3-pyfaidx |
Release | Version | Architectures |
trixie | 0.8.1.3-1 | all |
sid | 0.8.1.3-1 | all |
stretch | 0.4.8.1-1 | all |
bullseye | 0.5.9.2-1 | all |
buster | 0.5.5.2-1 | all |
bookworm | 0.7.1-2 | all |
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License: DFSG free
|
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-pynn
simulator-independent specification of neuronal network models
|
Versions of package python3-pynn |
Release | Version | Architectures |
bookworm | 0.10.1-2 | all |
sid | 0.10.1-3 | all |
bullseye | 0.9.6-1 | all |
upstream | 0.12.3 |
|
License: DFSG free
|
PyNN allows for coding a model once and run it without modification
on any simulator that PyNN supports (currently NEURON, NEST, PCSIM
and Brian). PyNN translates standard cell-model names and parameter
names into simulator-specific names.
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|
python3-pysam
interface for the SAM/BAM sequence alignment and mapping format (Python 3)
|
Versions of package python3-pysam |
Release | Version | Architectures |
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 |
trixie | 0.22.1+ds-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
buster | 0.15.2+ds-2 | amd64,arm64 |
stretch | 0.10.0+ds-2 | amd64,arm64,mips64el,ppc64el |
bookworm | 0.20.0+ds-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
bullseye | 0.15.4+ds-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
|
License: DFSG free
|
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-questplus
QUEST+ implementation in Python3
|
Versions of package python3-questplus |
Release | Version | Architectures |
bullseye | 2019.4-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 2023.1-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 2019.4-6 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 2023.1-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
|
License: DFSG free
|
QUEST+ is a Bayesian adaptive psychometric testing method that allows an
arbitrary number of stimulus dimensions, psychometric function
parameters, and trial outcomes.
This package provides an implementation in Python3.
|
|
python3-scitrack
Python3 library to track scientific data
|
Versions of package python3-scitrack |
Release | Version | Architectures |
bullseye | 2020.6.5-1 | all |
bookworm | 2021.5.3-3 | all |
trixie | 2024.10.8-1 | all |
sid | 2024.10.8-1 | all |
|
License: DFSG free
|
Scitrack is a library aimed at application developers writing scientific
software to support tracking of scientific computation. The library
provides elementary functionality to support logging. The primary
capabilities concern generating checksums on input and output files and
facilitating logging of the computational environment.
|
|
python3-screed
short nucleotide read sequence utils in Python 3
|
Versions of package python3-screed |
Release | Version | Architectures |
stretch | 0.9-2 | all |
trixie | 1.1.3-1 | all |
bullseye | 1.0.5-1 | all |
sid | 1.1.3-1 | all |
bookworm | 1.0.5-4 | all |
buster | 1.0-3 | all |
|
License: DFSG free
|
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-seirsplus
Models of SEIRS epidemic dynamics with extensions
|
Versions of package python3-seirsplus |
Release | Version | Architectures |
bookworm | 1.0.9-1 | all |
sid | 1.0.9-2 | all |
trixie | 1.0.9-2 | all |
bullseye | 0.1.4+git20200528.5c04080+ds-2 | all |
|
License: DFSG free
|
This package implements generalized SEIRS infectious disease
dynamics models with extensions that model the effect of factors
including population structure, social distancing, testing, contact
tracing, and quarantining detected cases.
Notably, this package includes stochastic implementations of these
models on dynamic networks.
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python3-streamz
build pipelines to manage continuous streams of data
|
Versions of package python3-streamz |
Release | Version | Architectures |
bullseye | 0.6.2-1 | all |
trixie | 0.6.4-2 | all |
sid | 0.6.4-2 | all |
bookworm | 0.6.4-1 | 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.
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|
python3-tinyalign
numerical representation of differences between strings
|
Versions of package python3-tinyalign |
Release | Version | Architectures |
sid | 0.2.2-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 0.2.2-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 0.2.1-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,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-toolz
List processing tools and functional utilities
|
Versions of package python3-toolz |
Release | Version | Architectures |
bookworm | 0.12.0-1 | all |
buster | 0.9.0-1 | all |
sid | 1.0.0-1 | all |
trixie | 1.0.0-1 | all |
stretch | 0.8.2-1 | all |
bullseye | 0.9.0-1.1 | all |
|
License: DFSG free
|
A set of utility functions for iterators, functions, and
dictionaries. These functions interoperate well and form the
building blocks of common data analytic operations. They extend the
standard libraries itertools and functools and borrow heavily from
the standard libraries of contemporary functional languages.
This contains the Python 3 version
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python3-torch
Tensors and Dynamic neural networks in Python (Python Interface)
|
Versions of package python3-torch |
Release | Version | Architectures |
sid | 2.5.0+dfsg-1 | amd64,arm64,ppc64el,riscv64,s390x |
bookworm | 1.13.1+dfsg-4 | amd64,arm64,ppc64el,s390x |
bullseye | 1.7.1-7 | amd64,arm64,armhf,ppc64el,s390x |
upstream | 2.5.1 |
|
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-tornado
scalable, non-blocking web server and tools - Python 3 package
|
Versions of package python3-tornado |
Release | Version | Architectures |
sid | 6.4.1-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
jessie | 3.2.2-1.1 | amd64,armel,armhf,i386 |
bullseye | 6.1.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 6.2.0-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 6.4.1-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch | 4.4.3-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 5.1.1-4 | amd64,arm64,armhf,i386 |
|
License: DFSG free
|
Tornado is a Python web framework and asynchronous networking library,
originally developed at FriendFeed. By using non-blocking network I/O,
Tornado can scale to tens of thousands of open connections, making it ideal
for long polling, WebSockets, and other applications that require a
long-lived connection to each user.
This is the Python 3 version of the package.
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python3-treetime
inference of time stamped phylogenies and ancestral reconstruction (Python 3)
|
Versions of package python3-treetime |
Release | Version | Architectures |
sid | 0.11.4-1 | all |
trixie | 0.11.4-1 | all |
bookworm | 0.9.4-1 | all |
buster | 0.5.3-1 | 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-vcf
Variant Call Format (VCF) parser for Python 3
|
Versions of package python3-vcf |
Release | Version | Architectures |
bookworm | 0.6.8+git20170215.476169c-9 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
sid | 0.6.8+git20170215.476169c-10 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
bullseye | 0.6.8+git20170215.476169c-7 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
trixie | 0.6.8+git20170215.476169c-10 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
|
License: DFSG free
|
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.
|
|
q2-cutadapt
QIIME 2 plugin to work with adapters in sequence data
|
Versions of package q2-cutadapt |
Release | Version | Architectures |
bookworm | 2022.11.1-2 | amd64,arm64,mips64el,ppc64el |
bullseye | 2020.11.1-1 | 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-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-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)
|
|
qcat
demultiplexing Oxford Nanopore reads from FASTQ files
|
Versions of package qcat |
Release | Version | Architectures |
sid | 1.1.0-6 | all |
trixie | 1.1.0-6 | all |
bookworm | 1.1.0-6 | all |
bullseye | 1.1.0-2 | all |
|
License: DFSG free
|
Qcat is a command-line tool for demultiplexing Oxford Nanopore reads
from FASTQ files. It accepts basecalled FASTQ files and splits the reads
into separate FASTQ files based on their barcode. Qcat makes the
demultiplexing algorithms used in albacore/guppy and EPI2ME available to
be used locally with FASTQ files. Currently qcat implements the EPI2ME
algorithm.
|
|
quicktree
Neighbor-Joining algorithm for phylogenies
|
Versions of package quicktree |
Release | Version | Architectures |
sid | 2.5-6 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 2.5-5 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 2.5-5 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 2.5-6 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
|
License: DFSG free
|
QuickTree is an efficient implementation of the Neighbor-Joining
algorithm (PMID: 3447015), capable of reconstructing phylogenies from
huge alignments in time less than the age of the universe.
QuickTree accepts both distance matrix and multiple-sequence-aligment
inputs. The former should be in PHYLIP format. The latter should be
in Stockholm format, which is the native alignment format for the Pfam
database. Alignments in various formats can be converted to Stockholm
format with the sreformat program, which is part of the HMMer package
(hmmer.org).
The tress are written to stdout, in the Newick/New-Hampshire format
use by PHYLIP and many other programs
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|
r-bioc-htsfilter
GNU R filter replicated high-throughput transcriptome sequencing data
|
Versions of package r-bioc-htsfilter |
Release | Version | Architectures |
bullseye | 1.30.1+dfsg-1 | all |
sid | 1.44.0+dfsg-1 | all |
bookworm | 1.38.0+dfsg-2 | all |
trixie | 1.44.0+dfsg-1 | all |
upstream | 1.46.0 |
|
License: DFSG free
|
This package implements a filtering procedure for
replicated transcriptome sequencing data based on a global
Jaccard similarity index in order to identify genes with low,
constant levels of expression across one or more experimental
conditions.
|
|
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 |
jessie | 3.22.1+dfsg-1 | amd64,armel,armhf,i386 |
stretch | 3.30.8+dfsg-1 | amd64,arm64,armel,armhf,i386,mips,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 |
buster | 3.38.3+dfsg-1 | amd64,arm64,armhf,i386 |
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-mutationalpatterns
GNU R comprehensive genome-wide analysis of mutational processes
|
Versions of package r-bioc-mutationalpatterns |
Release | Version | Architectures |
bullseye | 3.0.1+dfsg-2 | all |
sid | 3.14.0+dfsg-1 | all |
trixie | 3.14.0+dfsg-1 | all |
bookworm | 3.8.1+dfsg-1 | all |
upstream | 3.16.0 |
|
License: DFSG free
|
This BioConductor package provides an extensive toolset for the
characterization and visualization of a wide range of mutational patterns
in base substitution catalogs.
|
|
r-bioc-pwmenrich
|
Versions of package r-bioc-pwmenrich |
Release | Version | Architectures |
sid | 4.40.0-1 | all |
trixie | 4.40.0-1 | all |
bookworm | 4.34.0-1 | all |
bullseye | 4.26.0-1 | all |
upstream | 4.42.0 |
|
License: DFSG free
|
A toolkit of high-level functions for DNA motif scanning
and enrichment analysis built upon Biostrings. The main
functionality is PWM enrichment analysis of already known PWMs
(e.g. from databases such as MotifDb), but the package also
implements high-level functions for PWM scanning and
visualisation. The package does not perform "de novo" motif
discovery, but is instead focused on using motifs that are
either experimentally derived or computationally constructed by
other tools.
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|
r-bioc-rcpi
molecular informatics toolkit for compound-protein interaction
|
Versions of package r-bioc-rcpi |
Release | Version | Architectures |
sid | 1.40.3+ds-1 | all |
bookworm | 1.34.0+ds-1 | all |
trixie | 1.40.3+ds-1 | all |
upstream | 1.42.0 |
|
License: DFSG free
|
Rcpi offers a molecular informatics toolkit with a
comprehensive integration of bioinformatics and
chemoinformatics tools for drug discovery.
|
|
r-bioc-rgsepd
GNU R gene set enrichment / projection displays
|
Versions of package r-bioc-rgsepd |
Release | Version | Architectures |
bookworm | 1.30.0-1 | all |
sid | 1.36.0-1 | all |
trixie | 1.36.0-1 | all |
bullseye | 1.22.0-1 | all |
upstream | 1.38.0 |
|
License: DFSG free
|
R/GSEPD is a bioinformatics package for R to help
disambiguate transcriptome samples (a matrix of RNA-Seq counts
at transcript IDs) by automating differential expression (with
DESeq2), then gene set enrichment (with GOSeq), and finally a
N-dimensional projection to quantify in which ways each sample
is like either treatment group.
|
|
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 |
stretch | 1.26.1-2 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,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 |
trixie | 2.20.0+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 |
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.
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r-bioc-tcgabiolinks
GNU R/Bioconductor package for integrative analysis with GDC data
|
Versions of package r-bioc-tcgabiolinks |
Release | Version | Architectures |
bookworm | 2.25.3+dfsg-1 | all |
trixie | 2.32.0+dfsg-2 | all |
sid | 2.32.0+dfsg-2 | all |
bullseye | 2.18.0+dfsg-1 | all |
upstream | 2.34.0 |
|
License: DFSG free
|
The aim of TCGAbiolinks is:
1) facilitate the GDC open-access data retrieval,
2) prepare the data using the appropriate pre-processing strategies,
3) provide the means to carry out different standard analyses and
4) to easily reproduce earlier research results.
In more detail, the package provides multiple methods for analysis (e.g.,
differential expression analysis, identifying differentially methylated
regions) and methods for visualization (e.g., survival plots, volcano plots,
starburst plots) in order to easily develop complete analysis pipelines.
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r-cran-alakazam
Immunoglobulin Clonal Lineage and Diversity Analysis
|
Versions of package r-cran-alakazam |
Release | Version | Architectures |
sid | 1.3.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.1.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.2.1-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
experimental | 1.3.0-2~0exp0 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
trixie | 1.3.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
buster | 0.2.11-1 | amd64,arm64,armhf,i386 |
|
License: DFSG free
|
Alakazam is part of the Immcantation analysis framework for Adaptive
Immune Receptor Repertoire sequencing (AIRR-seq) and provides a set of
tools to investigate lymphocyte receptor clonal lineages, diversity,
gene usage, and other repertoire level properties, with a focus on
high-throughput immunoglobulin (Ig) sequencing.
Alakazam serves five main purposes:
- Providing core functionality for other R packages in the Immcantation
framework. This includes common tasks such as file I/O, basic DNA
sequence manipulation, and interacting with V(D)J segment and gene
annotations.
- Providing an R interface for interacting with the output of the
pRESTO and Change-O tool suites.
- Performing lineage reconstruction on clonal populations of Ig
sequences and analyzing the topology of the resultant lineage trees.
- Performing clonal abundance and diversity analysis on lymphocyte
repertoires.
- Performing physicochemical property analyses of lymphocyte receptor
sequences.
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r-cran-covid19us
cases of COVID-19 in the United States prepared for GNU R
|
Versions of package r-cran-covid19us |
Release | Version | Architectures |
sid | 0.1.9-1 | all |
bullseye | 0.1.7-1 | all |
bookworm | 0.1.9-1 | all |
trixie | 0.1.9-1 | all |
|
License: DFSG free
|
This package provides a GNU R wrapper around the 'COVID Tracking Project API'
https://covidtracking.com/api/ providing data on cases of COVID-19
in the US.
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r-cran-diagnosismed
medical diagnostic test accuracy analysis toolkit
|
Versions of package r-cran-diagnosismed |
Release | Version | Architectures |
buster | 0.2.3-6 | all |
jessie | 0.2.3-3 | all |
stretch | 0.2.3-4 | all |
bullseye | 0.2.3-7 | all |
sid | 0.2.3-7 | all |
bookworm | 0.2.3-7 | all |
trixie | 0.2.3-7 | all |
Debtags of package r-cran-diagnosismed: |
devel | lang:r |
field | medicine |
interface | commandline |
role | program |
use | analysing |
|
License: DFSG free
|
DiagnosisMed is a GNU R package to analyze the accuracy of data from
diagnostic tests evaluating health conditions. It was designed to be
used by health professionals. This package helps estimating sensitivity
and specificity from categorical and continuous test results including
some evaluations of indeterminate results, or compare different
categorical tests, and estimate reasonable cut-offs of tests and display
it in a way commonly used by health professionals. No graphical
interface is available yet.
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r-cran-epi
GNU R epidemiological analysis
|
Versions of package r-cran-epi |
Release | Version | Architectures |
jessie | 1.1.67-4 | amd64,armel,armhf,i386 |
sid | 2.53-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 2.47-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 2.43-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
stretch | 2.7-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
trixie | 2.53-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster | 2.32-2 | amd64,arm64,armhf,i386 |
upstream | 2.57 |
Debtags of package r-cran-epi: |
field | medicine |
interface | commandline |
role | program |
|
License: DFSG free
|
Functions for demographic and epidemiological analysis in the Lexis diagram,
i.e. register and cohort follow-up data, including interval censored data and
representation of multistate data. Also some useful functions for tabulation
and plotting. Contains some epidemiological datasets.
The Epi package is mainly focused on "classical" chronic disease epidemiology.
The package has grown out of the course Statistical Practice in Epidemiology
using R (see http://www.pubhealth.ku.dk/~bxc/SPE).
There is A short introduction to R for Epidemiology available at
http://staff.pubhealth.ku.dk/%7Ebxc/Epi/R-intro.pdf
Beware that the pages 38-120 of this is merely the manual pages for the Epi
package.
Epi is not the only R-package for epidemiological analysis, a package with
more affinity to infectious disease epidemiology is the epitools package
which is also evailable in Debian.
Epi is used in the Department of Biostatistics of the University of Copenhagen.
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r-cran-epibasix
GNU R Elementary Epidemiological Functions
|
Versions of package r-cran-epibasix |
Release | Version | Architectures |
stretch | 1.3-2 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
jessie | 1.3-1 | amd64,armel,armhf,i386 |
buster | 1.5-1 | all |
bullseye | 1.5-2 | all |
bookworm | 1.5-2 | all |
sid | 1.5-2 | all |
trixie | 1.5-2 | all |
Debtags of package r-cran-epibasix: |
field | medicine |
interface | commandline |
role | program |
|
License: DFSG free
|
Elementary Epidemiological Functions for a Graduate Epidemiology /
Biostatistics Course.
This package contains elementary tools for analysis of common epidemiological
problems, ranging from sample size estimation, through 2x2 contingency table
analysis and basic measures of agreement (kappa, sensitivity/specificity).
Appropriate print and summary statements are also written to facilitate
interpretation wherever possible. This package is a work in progress, so
any comments or suggestions would be appreciated. Source code is commented
throughout to facilitate modification. The target audience includes graduate
students in various epi/biostatistics courses.
Epibasix was developed in Canada.
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r-cran-epicalc
GNU R Epidemiological calculator
|
Versions of package r-cran-epicalc |
Release | Version | Architectures |
bookworm | 2.15.1.0-5 | all |
sid | 2.15.1.0-5 | all |
stretch | 2.15.1.0-2 | all |
bullseye | 2.15.1.0-5 | all |
buster | 2.15.1.0-4 | all |
trixie | 2.15.1.0-5 | all |
jessie | 2.15.1.0-1 | all |
Debtags of package r-cran-epicalc: |
devel | lang:r |
field | medicine, statistics |
interface | commandline |
role | program |
|
License: DFSG free
|
Functions making R easy for epidemiological calculation.
Datasets from Dbase (.dbf), Stata (.dta), SPSS(.sav), EpiInfo(.rec) and
Comma separated value (.csv) formats as well as R data frames can be
processed to do make several epidemiological calculations.
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r-cran-epiestim
GNU R estimate time varying reproduction numbers from rpidemic curves
|
Versions of package r-cran-epiestim |
Release | Version | Architectures |
bullseye | 2.2-4+dfsg-1 | all |
buster-backports | 2.2-4+dfsg-1~bpo10+1 | all |
trixie | 2.2-4+dfsg-1 | all |
bookworm | 2.2-4+dfsg-1 | all |
sid | 2.2-4+dfsg-1 | all |
|
License: DFSG free
|
Tools to quantify transmissibility throughout
an epidemic from the analysis of time series of incidence as described in
Cori et al. (2013) and Wallinga and Teunis (2004)
.
|
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r-cran-epir
GNU R Functions for analysing epidemiological data
|
Versions of package r-cran-epir |
Release | Version | Architectures |
stretch | 0.9-79-1 | all |
sid | 2.0.76+dfsg-1 | all |
bookworm | 2.0.57+dfsg-1 | all |
bullseye | 2.0.19-1 | all |
jessie | 0.9-59-1 | all |
buster | 0.9-99-1 | all |
upstream | 2.0.77 |
Debtags of package r-cran-epir: |
devel | lang:r |
field | medicine |
interface | commandline |
role | program |
use | analysing |
|
License: DFSG free
|
A package for analysing epidemiological data. Contains functions for
directly and indirectly adjusting measures of disease frequency,
quantifying measures of association on the basis of single or multiple
strata of count data presented in a contingency table, and computing
confidence intervals around incidence risk and incidence rate estimates.
Miscellaneous functions for use in meta-analysis, diagnostic test
interpretation, and sample size calculations.
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r-cran-epitools
GNU R Epidemiology Tools for Data and Graphics
|
Versions of package r-cran-epitools |
Release | Version | Architectures |
bullseye | 0.5-10.1-2 | all |
jessie | 0.5-7-1 | all |
stretch | 0.5-7-1 | all |
buster | 0.5-10-2 | all |
sid | 0.5-10.1-2 | all |
bookworm | 0.5-10.1-2 | all |
trixie | 0.5-10.1-2 | all |
Debtags of package r-cran-epitools: |
field | medicine |
interface | commandline |
role | program |
|
License: DFSG free
|
GNU R Tools for public health epidemiologists and data analysts.
Epitools provides numerical tools and programming solutions that
have been used and tested in real-world epidemiologic applications.
Many practical problems in the analysis of public health data
require programming or special software, and investigators in
different locations may duplicate programming efforts. Often,
simple analyses, such as the construction of confidence intervals,
are not calculated and thereby complicate appropriate statistical
inferences for small geographic areas. There are many examples of
simple and useful numerical tools that would enhance the work of
epidemiologists at local health departments and yet are not readily
available for the problem in front of them. The availability of
these tools will encourage wider use of appropriate methods and
promote evidence-based public health practices.
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r-cran-hms
|
Versions of package r-cran-hms |
Release | Version | Architectures |
bookworm | 1.1.2-1 | all |
buster | 0.4.2-2 | all |
bullseye | 1.0.0-1 | all |
trixie | 1.1.3-1 | all |
sid | 1.1.3-1 | all |
stretch-backports | 0.4.2-1~bpo9+1 | all |
|
License: DFSG free
|
This GNU R package implements an S3 class for storing and formatting
time-of-day values, based on the 'difftime' class.
|
|
r-cran-incidence
GNU R compute, handle, plot and model incidence of dated events
|
Versions of package r-cran-incidence |
Release | Version | Architectures |
trixie | 1.7.5-1 | all |
bullseye | 1.7.3-1 | all |
bookworm | 1.7.3-1 | all |
buster-backports | 1.7.3-1~bpo10+1 | all |
sid | 1.7.5-1 | all |
|
License: DFSG free
|
Provides functions and classes to compute, handle and visualise
incidence from dated events for a defined time interval. Dates can be
provided in various standard formats. The class 'incidence' is used to
store computed incidence and can be easily manipulated, subsetted, and
plotted. In addition, log-linear models can be fitted to 'incidence'
objects using 'fit'. This package is part of the RECON
(http://www.repidemicsconsortium.org/) toolkit for outbreak analysis.
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r-cran-kernelheaping
GNU R kernel density estimation for heaped and rounded data
|
Versions of package r-cran-kernelheaping |
Release | Version | Architectures |
bookworm | 2.3.0-1 | all |
sid | 2.3.0-1 | all |
|
License: DFSG free
|
In self-reported or anonymised data the user often encounters heaped
data, i.e. data which are rounded (to a possibly different degree of
coarseness). While this is mostly a minor problem in parametric density
estimation the bias can be very large for non-parametric methods such as
kernel density estimation. This package implements a partly Bayesian
algorithm treating the true unknown values as additional parameters and
estimates the rounding parameters to give a corrected kernel density
estimate. It supports various standard bandwidth selection methods.
Varying rounding probabilities (depending on the true value) and
asymmetric rounding is estimable as well: Gross, M. and Rendtel, U.
(2016) (). Additionally, bivariate non-
parametric density estimation for rounded data, Gross, M. et al. (2016)
(), as well as data aggregated on areas is
supported.
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|
r-cran-lexrankr
extractive summarization of text with the LexRank algorithm
|
Versions of package r-cran-lexrankr |
Release | Version | Architectures |
bookworm | 0.5.2-8 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 0.5.2-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 0.5.0-2 | amd64,arm64,armhf,i386 |
trixie | 0.5.2-8 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 0.5.2-8 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
|
License: DFSG free
|
An R implementation of the LexRank algorithm implementing stochastic
graph-based method for computing relative importance of textual units
for Natural Language Processing. The technique on the problem
of Text Summarization (TS) is tested. Extractive TS relies on the concept of
sentence salience to identify the most important sentences in a
document or set of documents. Salience is typically defined in terms of
the presence of particular important words or in terms of similarity to
a centroid pseudo-sentence.
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r-cran-mediana
clinical trial simulations
|
Versions of package r-cran-mediana |
Release | Version | Architectures |
bookworm | 1.0.8-3 | all |
sid | 1.0.8-3 | all |
bullseye | 1.0.8-3 | all |
trixie | 1.0.8-3 | all |
|
License: DFSG free
|
Provides a general framework for clinical trial simulations based on the
Clinical Scenario Evaluation (CSE) approach. The package supports a
broad class of data models (including clinical trials with continuous,
binary, survival-type and count-type endpoints as well as multivariate
outcomes that are based on combinations of different endpoints),
analysis strategies and commonly used evaluation criteria.
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r-cran-msm
GNU R Multi-state Markov and hidden Markov models in continuous time
|
Versions of package r-cran-msm |
Release | Version | Architectures |
bookworm | 1.7-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
stretch | 1.6.4-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
jessie | 1.4-2 | amd64,armel,armhf,i386 |
sid | 1.8-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.6.8-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.8-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster | 1.6.6-2 | amd64,arm64,armhf,i386 |
upstream | 1.8.2 |
Debtags of package r-cran-msm: |
interface | commandline |
role | program |
|
License: DFSG free
|
Functions for fitting general continuous-time Markov and hidden Markov
multi-state models to longitudinal data. Both Markov transition rates and the
hidden Markov output process can be modelled in terms of covariates. A variety
of observation schemes are supported, including processes observed at arbitrary
times, completely-observed processes, and censored states.
|
|
r-cran-qtl
GNU R package for genetic marker linkage analysis
|
Versions of package r-cran-qtl |
Release | Version | Architectures |
buster | 1.44-9-1 | amd64,arm64,armhf,i386 |
stretch | 1.40-8-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.58-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.70-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 1.70-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
jessie | 1.33-7-1 | amd64,armel,armhf,i386 |
bullseye | 1.47-9-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
Debtags of package r-cran-qtl: |
devel | lang:r, library |
field | biology, statistics |
role | app-data |
suite | gnu |
|
License: DFSG free
|
R/qtl is an extensible, interactive environment for mapping quantitative
trait loci (QTLs) in experimental crosses. It is implemented as an
add-on-package for the freely available and widely used statistical
language/software R (see http://www.r-project.org).
The development of this software as an add-on to R allows one to take
advantage of the basic mathematical and statistical functions, and
powerful graphics capabilities, that are provided with R. Further,
the user will benefit by the seamless integration of the QTL mapping
software into a general statistical analysis program. The goal is to
make complex QTL mapping methods widely accessible and allow users to
focus on modeling rather than computing.
A key component of computational methods for QTL mapping is the hidden
Markov model (HMM) technology for dealing with missing genotype data. The
main HMM algorithms, with allowance for the presence of genotyping errors,
for backcrosses, intercrosses, and phase-known four-way crosses
were implemented.
The current version of R/qtl includes facilities for estimating
genetic maps, identifying genotyping errors, and performing single-QTL
genome scans and two-QTL, two-dimensional genome scans, by interval
mapping (with the EM algorithm), Haley-Knott regression, and multiple
imputation. All of this may be done in the presence of covariates (such
as sex, age or treatment). One may also fit higher-order QTL models by
multiple imputation.
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r-cran-seroincidence
GNU R seroincidence calculator tool
|
Versions of package r-cran-seroincidence |
Release | Version | Architectures |
buster | 2.0.0-1 | all |
bookworm | 2.0.0-3 | all |
sid | 2.0.0-3 | all |
stretch | 1.0.5-1 | all |
bullseye | 2.0.0-2 | all |
trixie | 2.0.0-3 | all |
|
License: DFSG free
|
Antibody levels measured in a cross-sectional population samples can be
translated into an estimate of the frequency with which seroconversions
(new infections) occur. In order to interpret the measured
cross-sectional antibody levels, parameters which predict the decay of
antibodies must be known. In previously published reports (Simonsen et
al. 2009 and Versteegh et al. 2005), this information has been obtained
from longitudinal studies on subjects who had culture-confirmed
Salmonella and Campylobacter infections. A Bayesian back-calculation
model was used to convert antibody measurements into an estimation of
time since infection. This can be used to estimate the seroincidence in
the cross-sectional sample of population. For both the longitudinal and
cross-sectional measurements of antibody concentrations, the indirect
ELISA was used. The models are only valid for persons over 18 years. The
seroincidence estimates are suitable for monitoring the effect of
control programmes when representative cross-sectional serum samples are
available for analyses. These provide more accurate information on the
infection pressure in humans across countries.
|
|
r-cran-sf
|
Versions of package r-cran-sf |
Release | Version | Architectures |
stretch-backports | 0.6-3+dfsg-1~bpo9+1 | arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.0-9+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.0-17+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch-backports | 0.7-2+dfsg-1~bpo9+1 | amd64 |
bullseye | 0.9-7+dfsg-5 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 0.7-2+dfsg-1 | amd64,arm64,armhf,i386 |
upstream | 1.0-19 |
|
License: DFSG free
|
Support for simple features, a standardized way to encode spatial vector
data. Binds to 'GDAL' for reading and writing data, to 'GEOS' for
geometrical operations, and to 'PROJ' for projection conversions and
datum transformations.
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|
r-cran-shazam
Immunoglobulin Somatic Hypermutation Analysis
|
Versions of package r-cran-shazam |
Release | Version | Architectures |
bullseye | 1.0.2-1 | all |
sid | 1.2.0-1 | all |
trixie | 1.2.0-1 | all |
buster | 0.1.11-1 | all |
bookworm | 1.1.2-1 | 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.
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r-cran-sjplot
GNU R data visualization for statistics in social science
|
Versions of package r-cran-sjplot |
Release | Version | Architectures |
bookworm | 2.8.12+dfsg-1 | all |
stretch-backports | 2.6.2-1~bpo9+1 | all |
buster | 2.6.2-1 | all |
bullseye | 2.8.7-1 | all |
sid | 2.8.16+dfsg-1 | all |
|
License: DFSG free
|
Collection of plotting and table output functions for data
visualization. Results of various statistical analyses (that are
commonly used in social sciences) can be visualized using this package,
including simple and cross tabulated frequencies, histograms, box plots,
(generalized) linear models, mixed effects models, principal component
analysis and correlation matrices, cluster analyses, scatter plots,
stacked scales, effects plots of regression models (including
interaction terms) and much more. This package supports labelled data.
|
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r-cran-spp
GNU R ChIP-seq processing pipeline
|
Versions of package r-cran-spp |
Release | Version | Architectures |
buster | 1.15.5-1 | amd64,arm64,armhf,i386 |
bookworm | 1.16.0-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.16.0-2 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
sid | 1.16.0-2 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.16.0-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
|
License: DFSG free
|
R package for anlaysis of ChIP-seq and other functional sequencing data
- Assess overall DNA-binding signals in the data and select appropriate
quality of tag alignment.
- Discard or restrict positions with abnormally high number of tags.
- Calculate genome-wide profiles of smoothed tag density and save them
in WIG files for viewing in other browsers.
- Calculate genome-wide profiles providing conservative statistical
estimates of fold enrichment ratios along the genome. These can be
exported for browser viewing, or thresholded to determine regions of
significant enrichment/depletion.
- Determine statistically significant point binding positions
- Assess whether the set of point binding positions detected at a
current sequencing depth meets saturation criteria, and if does not,
estimate what sequencing depth would be required to do so.
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r-cran-stringi
GNU R character string processing facilities
|
Versions of package r-cran-stringi |
Release | Version | Architectures |
bookworm | 1.7.12-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
stretch-backports | 1.2.4-2~bpo9+1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 1.2.4-2 | amd64,arm64,armhf,i386 |
stretch | 1.1.2-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
sid | 1.8.4-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 1.8.4-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.5.3-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
|
License: DFSG free
|
Allows for fast, correct, consistent, portable, as well as convenient
character string/text processing in every locale and any native
encoding. Owing to the use of the ICU library, the package provides R
users with platform-independent functions known to Java, Perl, Python,
PHP, and Ruby programmers. Among available features there are: pattern
searching (e.g. via regular expressions), random string generation,
string collation, transliteration, concatenation, date-time formatting
and parsing, etc.
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r-cran-surveillance
GNU R package for the Modeling and Monitoring of Epidemic Phenomena
|
Versions of package r-cran-surveillance |
Release | Version | Architectures |
jessie | 1.8-0-1 | amd64,armel,armhf,i386 |
trixie | 1.24.0-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 1.24.0-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch | 1.13.0-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 1.16.2-1 | amd64,arm64,armhf,i386 |
bullseye | 1.19.0-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.20.3-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
upstream | 1.24.1 |
Debtags of package r-cran-surveillance: |
field | medicine |
interface | commandline |
role | program |
|
License: DFSG free
|
Statistical methods for the modeling and monitoring of time series of
counts, proportions and categorical data, as well as for the modeling of
continuous-time point processes of epidemic phenomena.
The monitoring methods focus on aberration detection in count data time
series from public health surveillance of communicable diseases, but
applications could just as well originate from environmetrics,
reliability engineering, econometrics, or social sciences. The package
implements many typical outbreak detection procedures such as the
(improved) Farrington algorithm, or the negative binomial GLR-CUSUM
method of Höhle and Paul (2008) . A novel
CUSUM approach combining logistic and multinomial logistic modeling is
also included. The package contains several real-world data sets, the
ability to simulate outbreak data, and to visualize the results of the
monitoring in a temporal, spatial or spatio-temporal fashion. A recent
overview of the available monitoring procedures is given by Salmon et al.
(2016) .
For the retrospective analysis of epidemic spread, the package provides
three endemic-epidemic modeling frameworks with tools for visualization,
likelihood inference, and simulation. hhh4() estimates models for
(multivariate) count time series following Paul and Held (2011)
and Meyer and Held (2014)
. twinSIR() models the
susceptible-infectious-recovered (SIR) event history of a fixed
population, e.g, epidemics across farms or networks, as a multivariate
point process as proposed by Höhle (2009) .
twinstim() estimates self-exciting point process models for a
spatio-temporal point pattern of infective events, e.g., time-stamped
geo-referenced surveillance data, as proposed by Meyer et al. (2012)
. A recent overview of the
implemented space-time modeling frameworks for epidemic phenomena is
given by Meyer et al. (2017) .
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r-cran-tigger
Infers new Immunoglobulin alleles from Rep-Seq Data
|
Versions of package r-cran-tigger |
Release | Version | Architectures |
bookworm | 1.0.1-1 | all |
bullseye | 1.0.0-1 | all |
buster | 0.3.1-1 | all |
trixie | 1.1.0-1 | all |
sid | 1.1.0-1 | all |
|
License: DFSG free
|
Summary: Infers the V genotype of an individual from immunoglobulin (Ig)
repertoire-sequencing (Rep-Seq) data, including detection of any novel
alleles. This information is then used to correct existing V allele calls
from among the sample sequences.
High-throughput sequencing of B cell immunoglobulin receptors is
providing unprecedented insight into adaptive immunity. A key step in
analyzing these data involves assignment of the germline V, D and J gene
segment alleles that comprise each immunoglobulin sequence by matching
them against a database of known V(D)J alleles. However, this process
will fail for sequences that utilize previously undetected alleles,
whose frequency in the population is unclear.
TIgGER is a computational method that significantly improves V(D)J
allele assignments by first determining the complete set of gene segments
carried by an individual (including novel alleles) from V(D)J-rearrange
sequences. TIgGER can then infer a subject’s genotype from these
sequences, and use this genotype to correct the initial V(D)J allele
assignments.
The application of TIgGER continues to identify a surprisingly high
frequency of novel alleles in humans, highlighting the critical need
for this approach. TIgGER, however, can and has been used with data
from other species.
Core Abilities:
- Detecting novel alleles
- Inferring a subject’s genotype
- Correcting preliminary allele calls
Required Input
- A table of sequences from a single individual, with columns containing
the following:
- V(D)J-rearranged nucleotide sequence (in IMGT-gapped format)
- Preliminary V allele calls
- Preliminary J allele calls
- Length of the junction region
- Germline Ig sequences in IMGT-gapped fasta format (e.g., as those
downloaded from IMGT/GENE-DB)
The former can be created through the use of IMGT/HighV-QUEST and
Change-O.
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r-other-ascat
Allele-Specific Copy Number Analysis of Tumours
|
Versions of package r-other-ascat |
Release | Version | Architectures |
sid | 3.1.2-1 | all |
trixie | 3.1.2-1 | all |
bullseye | 2.5.2-3 | all |
bookworm | 3.1.1-1 | all |
upstream | 3.2.0 |
|
License: DFSG free
|
ASCAT (allele-specific copy number analysis of tumors) is a allele-
specific copy number analysis of the in vivo breast cancer genome. It
can be used to accurately dissect the allele-specific copy number of
solid tumors, simultaneously estimating and adjusting for both tumor
ploidy and nonaberrant cell admixture.
Please cite:
Peter Van Loo, Silje H Nordgard, Ole Christian Lingjærde, Hege G Russnes, Inga H Rye, Wei Sun, Victor J Weigman, Peter Marynen, Anders Zetterberg, Bjørn Naume, Charles M Perou, Anne-Lise Børresen-Dale and Vessela N Kristensen:
Allele-specific Copy Number Analysis of Tumors.
(PubMed)
PNAS
107(39):16910-5
(2010)
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|
ragout
Reference-Assisted Genome Ordering UTility
|
Versions of package ragout |
Release | Version | Architectures |
trixie | 2.3-5 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 2.3-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 2.3-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 2.3-5 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
|
License: DFSG free
|
Ragout (Reference-Assisted Genome Ordering UTility) is a tool for
chromosome-level scaffolding using multiple references. Given initial
assembly fragments (contigs/scaffolds) and one or multiple related
references (complete or draft), it produces a chromosome-scale assembly
(as a set of scaffolds).
The approach is based on the analysis of genome rearrangements (like
inversions or chromosomal translocations) between the input genomes and
reconstructing the most parsimonious structure of the target genome.
Ragout now supports both small and large genomes (of mammalian scale
and complexity). The assembly of highly polymorphic genomes is
currently limited.
Please cite:
Mikhail Kolmogorov, Joel Armstrong, Brian J. Raney, Ian Streeter, Matthew Dunn, Fengtang Yang, Duncan Odom, Paul Flicek, Thomas M. Keane, David Thybert, Benedict Paten and Son Pham:
Chromosome assembly of large and complex genomes using multiple references.
(PubMed,eprint)
Genome Research
28(11):1720-1732
(2018)
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readucks
Nanopore read de-multiplexer (read demux -> readux -> readucks, innit)
|
Versions of package readucks |
Release | Version | Architectures |
sid | 0.0.3-5 | all |
bookworm | 0.0.3-5 | all |
bullseye | 0.0.3-2 | all |
|
License: DFSG free
|
This package is inspired by the demultiplexing options in
porechop but without the adapter trimming options - it just demuxes.
It uses the parasail library with its Python bindings to do
pairwise alignment which provides a considerable speed up over
the seqan library used by porechop due to its low-level use
of vector processor instructions.
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recan
genetic distance plotting for recombination events analysis
|
Versions of package recan |
Release | Version | Architectures |
bullseye | 0.1.2-2 | all |
trixie | 0.5+dfsg-1 | all |
bookworm | 0.1.5+dfsg-2 | all |
sid | 0.5+dfsg-1 | all |
|
License: DFSG free
|
recan is a Python package which allows one to construct genetic distance
plots to explore and discover recombination events in viral genomes.
This method has been previously implemented in desktop software
tools: RAT, Simplot and RDP4.
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rna-star
ultrafast universal RNA-seq aligner
|
Versions of package rna-star |
Release | Version | Architectures |
stretch-backports | 2.7.0a+dfsg-1~bpo9+1 | amd64,arm64,mips64el,ppc64el |
stretch | 2.5.2b+dfsg-1 | amd64,arm64,mips64el,ppc64el |
buster | 2.7.0a+dfsg-1 | amd64,arm64 |
bullseye | 2.7.8a+dfsg-2 | amd64,arm64,mips64el,ppc64el |
bookworm | 2.7.10b+dfsg-2 | amd64,arm64,mips64el,ppc64el |
trixie | 2.7.11b+dfsg-2 | amd64,arm64,mips64el,ppc64el,riscv64 |
sid | 2.7.11b+dfsg-2 | amd64,arm64,mips64el,ppc64el,riscv64 |
|
License: DFSG free
|
Spliced Transcripts Alignment to a Reference (STAR) software based on a
previously undescribed RNA-seq alignment algorithm that uses sequential
maximum mappable seed search in uncompressed suffix arrays followed by
seed clustering and stitching procedure. STAR outperforms other aligners
by a factor of >50 in mapping speed, aligning to the human genome 550
million 2 × 76 bp paired-end reads per hour on a modest 12-core server,
while at the same time improving alignment sensitivity and precision. In
addition to unbiased de novo detection of canonical junctions, STAR can
discover non-canonical splices and chimeric (fusion) transcripts, and is
also capable of mapping full-length RNA sequences. Using Roche 454
sequencing of reverse transcription polymerase chain reaction amplicons,
the authors experimentally validated 1960 novel intergenic splice
junctions with an 80-90% success rate, corroborating the high precision
of the STAR mapping strategy.
The package is enhanced by the following packages:
multiqc
Topics: Sequence analysis
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rsem
RNA-Seq by Expectation-Maximization
|
Versions of package rsem |
Release | Version | Architectures |
sid | 1.3.3+dfsg-3 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
buster | 1.3.1+dfsg-1 | amd64,arm64 |
stretch | 1.2.31+dfsg-1 | amd64,arm64,mips64el,ppc64el,s390x |
bookworm | 1.3.3+dfsg-2 | amd64,arm64,mips64el,ppc64el,s390x |
bullseye | 1.3.3+dfsg-1 | amd64,arm64,mips64el,ppc64el,s390x |
trixie | 1.3.3+dfsg-3 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
|
License: DFSG free
|
RSEM is a software package for estimating gene and isoform expression
levels from RNA-Seq data. The RSEM package provides an user-friendly
interface, supports threads for parallel computation of the EM
algorithm, single-end and paired-end read data, quality scores,
variable-length reads and RSPD estimation. In addition, it provides
posterior mean and 95% credibility interval estimates for expression
levels. For visualization, It can generate BAM and Wiggle files in both
transcript-coordinate and genomic-coordinate. Genomic-coordinate files
can be visualized by both UCSC Genome browser and Broad Institute’s
Integrative Genomics Viewer (IGV). Transcript-coordinate files can be
visualized by IGV. RSEM also has its own scripts to generate transcript
read depth plots in pdf format. The unique feature of RSEM is, the read
depth plots can be stacked, with read depth contributed to unique reads
shown in black and contributed to multi-reads shown in red. In addition,
models learned from data can also be visualized. Last but not least,
RSEM contains a simulator.
The package is enhanced by the following packages:
multiqc
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ruby-bio
Ruby tools for computational molecular biology
|
Versions of package ruby-bio |
Release | Version | Architectures |
trixie | 2.0.5-1 | all |
sid | 2.0.5-1 | all |
bookworm | 2.0.4-1 | all |
bullseye | 2.0.1-2 | all |
jessie | 1.4.3.0001-2 | all |
stretch | 1.5.0-2 | all |
buster | 1.5.2-1 | all |
|
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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salmon
wicked-fast transcript quantification from RNA-seq data
|
Versions of package salmon |
Release | Version | Architectures |
sid | 1.10.2+ds1-1 | amd64,arm64 |
buster | 0.12.0+ds1-1 | amd64 |
trixie | 1.10.2+ds1-1 | amd64,arm64 |
bookworm | 1.10.1+ds1-1 | amd64,arm64 |
stretch | 0.7.2+ds1-2 | amd64 |
bullseye | 1.4.0+ds1-1 | amd64,arm64 |
upstream | 1.10.3 |
|
License: DFSG free
|
Salmon is a wicked-fast program to produce a highly-accurate, transcript-level
quantification estimates from RNA-seq data. Salmon achieves is accuracy and
speed via a number of different innovations, including the use of lightweight
alignments (accurate but fast-to-compute proxies for traditional read
alignments) and massively-parallel stochastic collapsed variational inference.
The result is a versatile tool that fits nicely into many different pipelines.
For example, you can choose to make use of the lightweight alignments by
providing Salmon with raw sequencing reads, or, if it is more convenient, you
can provide Salmon with regular alignments (e.g. computed with your favorite
aligner), and it will use the same wicked-fast, state-of-the-art inference
algorithm to estimate transcript-level abundances for your experiment.
The package is enhanced by the following packages:
multiqc
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samblaster
marks duplicates, extracts discordant/split reads
|
Versions of package samblaster |
Release | Version | Architectures |
trixie | 0.1.26-4 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 0.1.26-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 0.1.26-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 0.1.24-2 | amd64,arm64,armhf,i386 |
sid | 0.1.26-4 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
|
License: DFSG free
|
Current "next-generation" sequencing technologies cannot tell what
exact sequence they will be reading. They take what is available. And
if some sequences are read very often, then this needs some extra
biomedical thinking. The genome could for instance be duplicated.
samblaster is a fast and flexible program for marking duplicates in
read-id grouped paired-end SAM files. It can also optionally output
discordant read pairs and/or split read mappings to separate SAM files,
and/or unmapped/clipped reads to a separate FASTQ file. When marking
duplicates, samblaster will require approximately 20MB of memory per
1M read pairs.
The package is enhanced by the following packages:
multiqc
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|
samclip
filter SAM file for soft and hard clipped alignments
|
Versions of package samclip |
Release | Version | Architectures |
trixie | 0.4.0-4 | all |
bullseye | 0.4.0-2 | all |
sid | 0.4.0-4 | all |
bookworm | 0.4.0-4 | all |
|
License: DFSG free
|
Most short read aligners perform local alignment of reads to the
reference genome. Examples includes bwa mem, minimap2, and bowtie2
(unless in --end-to-end mode). This means the ends of the read may not
be part of the best alignment.
This can be caused by:
- adapter sequences (aren't in the reference)
- poor quality bases (mismatches only make the alignment score worse)
- structural variation in your sample compared to the reference
- reads overlapping the start and end of contigs (including
circular genomes)
Read aligners output a SAM file. Column 6 in this format stores the
CIGAR string. which describes which parts of the read aligned and which
didn't. The unaligned ends of the read can be "soft" or "hard" clipped,
denoted with S and H at each end of the CIGAR string. It is possible for
both types to be present, but that is not common. Soft and hard don't
mean anything biologically, they just refer to whether the full read
sequence is in the SAM file or not.
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samtools
processing sequence alignments in SAM, BAM and CRAM formats
|
Versions of package samtools |
Release | Version | Architectures |
bullseye | 1.11-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
experimental | 1.21-0+exp1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 1.20-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 1.20-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 1.16.1-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 1.9-4 | amd64,arm64,armhf |
stretch-backports | 1.7-2~bpo9+1 | amd64,arm64,armel,armhf,mips,mips64el,mipsel,ppc64el,s390x |
jessie | 0.1.19-1 | amd64,armhf,i386 |
stretch | 1.3.1-3 | amd64,arm64,armel,i386,mips64el,mipsel,ppc64el |
upstream | 1.21 |
Debtags of package samtools: |
field | biology |
interface | commandline |
network | client |
role | program |
scope | utility |
uitoolkit | ncurses |
use | analysing, calculating, filtering |
works-with | biological-sequence |
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License: DFSG free
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Samtools is a set of utilities that manipulate nucleotide sequence alignments
in the binary BAM format. It imports from and exports to the ascii SAM
(Sequence Alignment/Map) and CRAM formats, does sorting, merging and indexing,
and allows one to retrieve reads in any regions swiftly. It is designed to work
on a stream, and is able to open a BAM or CRAM (not SAM) file on a remote FTP
or HTTP server.
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scrappie
basecaller for Nanopore sequencer
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Versions of package scrappie |
Release | Version | Architectures |
bullseye | 1.4.2-7 | amd64,arm64,armhf,i386,mips64el,ppc64el,s390x |
bookworm | 1.4.2-8 | amd64,arm64,armhf,i386,mips64el,ppc64el,s390x |
experimental | 1.4.2-9~0exp0simde | amd64,arm64,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 1.4.2-8 | amd64,arm64,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 1.4.2-8 | amd64,arm64,armhf,i386,mips64el,ppc64el,riscv64,s390x |
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License: DFSG free
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The Nanopore is a device for DNA/RNA sequencing that does
not require an amplification of the material. The polynucleotides
are threaded through a pore and while these pass through,
the change in the electrostatic potential allows one to
identify ("call") the actual base that resides in the pore.
Scrappie goes a step further and also attempts to describe
modifications to the nucleic acid.
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sepp
phylogeny with ensembles of Hidden Markov Models
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Versions of package sepp |
Release | Version | Architectures |
sid | 4.5.5+dfsg-1 | amd64,arm64 |
bullseye | 4.3.10+dfsg-5 | amd64 |
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License: DFSG free
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The tool SEPP implementing these methods uses ensembles of Hidden Markov
Models (HMMs) in different ways, each focusing on a different problem.
SEPP stands for "SATe-enabled Phylogenetic Placement", and addresses the
problem of phylogenetic placement of short reads into reference
alignments and trees.
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seqkit
cross-platform and ultrafast toolkit for FASTA/Q file manipulation
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Versions of package seqkit |
Release | Version | Architectures |
bookworm | 2.3.1+ds-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 2.8.2+ds-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 2.8.2+ds-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 0.15.0+ds-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
upstream | 2.9.0 |
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License: DFSG free
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SeqKit describes a cross-platform ultrafast comprehensive toolkit for
FASTA/Q processing. SeqKit provides executable binary files for all
major operating systems, including Windows, Linux, and Mac OS X, and can
be directly used without any dependencies or pre-configurations. SeqKit
demonstrates competitive performance in execution time and memory usage
compared to similar tools. The efficiency and usability of SeqKit enable
researchers to rapidly accomplish common FASTA/Q file manipulations.
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seqmagick
imagemagick-like frontend to Biopython SeqIO
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Versions of package seqmagick |
Release | Version | Architectures |
bookworm | 0.8.4-3 | all |
sid | 0.8.6-3 | all |
trixie | 0.8.6-3 | all |
bullseye | 0.8.4-1 | all |
buster | 0.7.0-1 | all |
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License: DFSG free
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Seqmagick is a little utility to expose the file format conversion
in BioPython in a convenient way.
Features include:
- Modifying sequences:
- Remove gaps
- Reverse & reverse complement
- Trim to a range of residues
- Change case
- Sort by length or ID
- Displaying information about sequence files
- Subsetting sequence files by:
- Position
- ID
- Deduplication
- Filtering sequences by quality score
- Trimming alignments to a region of interest defined by the forward
and reverse primers
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shapeit4
fast and accurate method for estimation of haplotypes (phasing)
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Versions of package shapeit4 |
Release | Version | Architectures |
sid | 4.2.2+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 4.2.2+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 4.2.0+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 4.2.2+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
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License: DFSG free
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Segmented HAPlotype Estimation and Imputation Tools version 4 (SHAPEIT4).
SHAPEIT4 is a fast and accurate method for estimation of haplotypes (aka
phasing) for SNP array and sequencing data.
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shiny-server
put Shiny web apps online
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Versions of package shiny-server |
Release | Version | Architectures |
trixie | 1.5.20.1002-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 1.5.20.1002-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 1.5.20.1002-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
upstream | 1.5.23.1030 |
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License: DFSG free
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Shiny Server lets you put shiny web applications and interactive
documents online. Take your Shiny apps and share them with your
organization or the world.
Shiny Server lets you go beyond static charts, and lets you manipulate
the data. Users can sort, filter, or change assumptions in real-time.
Shiny server empower your users to customize your analysis for their
specific needs and extract more insight from the data.
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shovill
Assemble bacterial isolate genomes from Illumina paired-end reads
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Versions of package shovill |
Release | Version | Architectures |
trixie | 1.1.0-9 | amd64 |
bookworm | 1.1.0-9 | amd64 |
bullseye | 1.1.0-4 | amd64 |
sid | 1.1.0-9 | amd64 |
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License: DFSG free
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Shovill is a pipeline which uses SPAdes at its core,
but alters the steps before and after the primary
assembly step to get similar results in less time.
Shovill also supports other assemblers like SKESA,
Velvet and Megahit, so you can take advantage of the
pre- and post-processing the Shovill provides
with those too.
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smrtanalysis
software suite for single molecule, real-time sequencing
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Versions of package smrtanalysis |
Release | Version | Architectures |
stretch | 0~20161126 | all |
bullseye | 0~20210111 | all |
bookworm | 0~20210112 | all |
sid | 0~20210112 | all |
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License: DFSG free
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SMRT® Analysis is a powerful, open-source bioinformatics software suite
available for analysis of DNA sequencing data from Pacific Biosciences’
SMRT technology. Users can choose from a variety of analysis protocols that
utilize PacBio® and third-party tools. Analysis protocols include de novo
genome assembly, cDNA mapping, DNA base-modification detection, and
long-amplicon analysis to determine phased consensus sequences.
This is a metapackage that depends on the components of SMRT Analysis.
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snakemake
pythonic workflow management system
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Versions of package snakemake |
Release | Version | Architectures |
stretch | 3.10.0-1 | all |
buster | 5.4.0-1 | all |
bullseye | 5.24.1-2 | all |
sid | 7.32.4-6 | all |
trixie | 7.32.4-6 | all |
bookworm | 7.21.0-1 | all |
upstream | 8.25.3 |
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License: DFSG free
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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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snpeff
genetic variant annotation and effect prediction toolbox - tool
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Versions of package snpeff |
Release | Version | Architectures |
bookworm | 5.1+d+dfsg-3 | all |
sid | 5.2.e+dfsg-1 | all |
trixie | 5.2.e+dfsg-1 | all |
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License: DFSG free
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"We are all different!" Geneticists agree to this.
Even twins, who are said to be identical are on a molecular
level only "mostly" identical. And even within the exact same individual,
healthy cells acquire mutations such that we are all genetic mosaics.
Changes to individual cells may be induced by environmental factors,
e.g. like UV light, or happen sporadically as mishaps during cellular
divisions.
Because there are so many genetic differences, and most have just no
particular meaning for the development of a phenotype, i.e. most have no
effect, it would be nice to have heuristics implemented that direct the
researcher towards single-nucleotide polymorphisms (SNPs) that are most
likely to be relevant. This identifies the gene that causes or contributes
to, e.g, an illness, and possibly also genes that are affected by that
change. Such mechanistic understanding of a disease, particularly when
multiple genes and multiple genetic variants are contributing to the
then "polygenic" phenotype, is at the onset of drug development and
increasingly also for selecting individualized therapies in the clinic.
SnpEff is a variant annotation and effect prediction tool. It annotates
and predicts the effects of variants on genes (such as amino acid
changes).
The inputs are predicted variants (SNPs, insertions, deletions and
MNPs). The input file is usually obtained as a result of a sequencing
experiment, and it is usually in variant call format (VCF).
SnpEff analyzes the input variants. It annotates the variants and
calculates the effects they produce on known genes (e.g. amino acid
changes).
This package contains the command line tool.
The package is enhanced by the following packages:
multiqc
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snpsift
tool to annotate and manipulate genome variants - tool
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Versions of package snpsift |
Release | Version | Architectures |
sid | 5.2.e+dfsg-1 | all |
bookworm | 5.1+dfsg2-2 | all |
trixie | 5.2.e+dfsg-1 | all |
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License: DFSG free
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SnpSift is a toolbox that allows one to filter and manipulate annotated files.
Once the genomic variants have been annotated, one needs to filter them out in
order to find the "interesting / relevant variants". Given the large data
files, this is not a trivial task (e.g. one cannot load all the variants into
XLS spreadsheet). SnpSift helps to perform this VCF file manipulation and
filtering required at this stage in data processing pipelines.
This package contains the command line tool.
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spades
genome assembler for single-cell and isolates data sets
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Versions of package spades |
Release | Version | Architectures |
bullseye | 3.13.1+dfsg-2 | amd64 |
stretch-backports-sloppy | 3.13.1+dfsg-2~bpo9+1 | amd64 |
buster | 3.13.0+dfsg2-2 | amd64 |
trixie | 3.15.5+dfsg-7 | amd64 |
sid | 3.15.5+dfsg-7 | amd64 |
experimental | 4.0.0+dfsg1-1 | amd64 |
bookworm | 3.15.5+dfsg-2 | amd64 |
stretch | 3.9.1+dfsg-1 | amd64 |
stretch-backports | 3.12.0+dfsg-1~bpo9+1 | amd64 |
upstream | 4.0.0 |
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License: DFSG free
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The SPAdes – St. Petersburg genome assembler is intended for both
standard isolates and single-cell MDA bacteria assemblies. It works
with Illumina or IonTorrent reads and is capable of providing hybrid
assemblies using PacBio and Sanger reads. You can also provide
additional contigs that will be used as long reads.
This package provides the following additional pipelines:
- metaSPAdes – a pipeline for metagenomic data sets
- plasmidSPAdes – a pipeline for extracting and assembling plasmids
from WGS data sets
- metaplasmidSPAdes – a pipeline for extracting and assembling
plasmids from metagenomic data sets
- rnaSPAdes – a de novo transcriptome assembler from RNA-Seq data
- truSPAdes – a module for TruSeq barcode assembly
- biosyntheticSPAdes – a module for biosynthetic gene cluster
assembly with paired-end reads
SPAdes provides several stand-alone binaries with relatively simple
command-line interface: k-mer counting (spades-kmercounter), assembly
graph construction (spades-gbuilder) and long read to graph aligner
(spades-gmapper).
Please cite:
Anton Bankevich, Sergey Nurk, Dmitry Antipov, Alexey A. Gurevich, Mikhail Dvorkin, Alexander S. Kulikov, Valery M. Lesin, Sergey I. Nikolenko, Son Pham, Andrey D. Prjibelski, Alexey V. Pyshkin, Alexander V. Sirotkin, Nikolay Vyahhi, Glenn Tesler, Max A. Alekseyev and Pavel A. Pevzner:
SPAdes: A New Genome Assembly Algorithm and Its Applications to Single-Cell Sequencing.
(PubMed,eprint)
Journal of Computational Biology
19(5):455-477
(2012)
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spaln
splicing-aware transcript-alignment to genomic DNA
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Versions of package spaln |
Release | Version | Architectures |
trixie | 3.0.2+dfsg-2 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
sid | 3.0.2+dfsg-2 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bullseye | 2.4.1+dfsg-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 2.4.13f+dfsg-1 | amd64,arm64,mips64el,ppc64el,s390x |
upstream | 3.0.6b |
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License: DFSG free
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Spaln (space-efficient spliced alignment) is a stand-alone program that
maps and aligns a set of cDNA or protein sequences onto a whole genomic
sequence in a single job. It also performs spliced or ordinary alignment
after rapid similarity search against a protein sequence database,
if a genomic segment or an amino acid sequence is given as a query.
spaln supports a combination of protein sequence database and a
given genomic segment and performs rapid similarity searches and
(semi-)global alignments of a set of protein sequence queries against
a protein sequence database. Spaln adopts multi-phase heuristics that
makes it possible to perform the job on a conventional personal computer.
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staden-io-lib-utils
programs for manipulating DNA sequencing files
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Versions of package staden-io-lib-utils |
Release | Version | Architectures |
sid | 1.15.0-1.1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.14.13-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
stretch | 1.14.8-2 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.14.15-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
jessie | 1.13.7-1 | amd64,armel,armhf,i386 |
trixie | 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 staden-io-lib-utils: |
biology | nuceleic-acids, peptidic |
field | biology, biology:bioinformatics |
interface | commandline |
role | program |
scope | utility |
use | analysing |
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License: DFSG free
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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.
This package contains the programs that are distributed with the Staden io_lib
for manipulating and converting sequencing data files, and in particular files
to manipulate short reads generated by second and third generation sequencers
and stored in SRF format.
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stringtie
assemble short RNAseq reads to transcripts
|
Versions of package stringtie |
Release | Version | Architectures |
bullseye | 2.1.4+ds-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 2.2.1+ds-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 2.2.1+ds-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 2.2.1+ds-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
upstream | 2.2.3 |
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License: DFSG free
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The abundance of transcripts in a human tissue sample
can be determined by RNA sequencing. The exact sequence
sampled may be random, depending on the technology used.
And it may be short, i.e. shorter than the transcript.
At some point, many shorter reads need to be assembled
to the model the complete transcripts.
StringTie knows how to assemble of RNA-Seq into potential
transcripts without the need of a reference genome and
provides a quantification also of the splice variants.
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sumaclust
fast and exact clustering of genomic sequences
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Versions of package sumaclust |
Release | Version | Architectures |
sid | 1.0.36+ds-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch | 1.0.20-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 1.0.31-2 | amd64,arm64,armhf,i386 |
bullseye | 1.0.36+ds-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.0.36+ds-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
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License: DFSG free
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With the development of next-generation sequencing, efficient tools are
needed to handle millions of sequences in reasonable amounts of time.
Sumaclust is a program developed by the LECA. Sumaclust aims to cluster
sequences in a way that is fast and exact at the same time. This tool
has been developed to be adapted to the type of data generated by DNA
metabarcoding, i.e. entirely sequenced, short markers. Sumaclust
clusters sequences using the same clustering algorithm as UCLUST and CD-
HIT. This algorithm is mainly useful to detect the 'erroneous' sequences
created during amplification and sequencing protocols, deriving from
'true' sequences.
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texlive-science
??? missing short description for package texlive-science :-(
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Versions of package texlive-science |
Release | Version | Architectures |
bookworm | 2022.20230122-4 | all |
trixie | 2024.20241102-1 | all |
sid | 2024.20241115-1 | all |
buster | 2018.20190227-2 | all |
stretch | 2016.20170123-5 | all |
jessie | 2014.20141024-1 | all |
bullseye | 2020.20210202-3 | all |
Debtags of package texlive-science: |
field | biology, chemistry, electronics, mathematics, physics |
made-of | tex |
role | app-data |
science | publishing |
use | typesetting |
works-with | graphs, text |
works-with-format | tex |
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License: DFSG free
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thesias
Testing Haplotype Effects In Association Studies
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Versions of package thesias |
Release | Version | Architectures |
buster-backports | 3.1.1-1~bpo10+1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
bookworm | 3.1.1-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 3.1.1-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 3.1.1-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 3.1.1-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
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License: DFSG free
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The objectif of the THESIAS program is to performed haplotype-based
association analysis in unrelated individuals. This program is based
on the maximum likelihood model described in Tregouet et al. 2002
(Hum Mol Genet 2002,11: 2015-2023) and is linked to the SEM algorithm
(Tregouet et al. Ann Hum Genet 2004,68: 165-177).
THESIAS allows one to simultaneous estimate haplotype frequencies
and their associate effects on the phenotype of interest.
In this new THESIAS release, quantitative, qualitative (logistic
and matched-pair analysis), categorical and survival outcomes can be
studied. X-linked haplotype analysis is also feasible.
Covariate-adjusted haplotype effects as well as haplotype x covariate
interactions can also be investigated.
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tiddit
structural variant calling
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Versions of package tiddit |
Release | Version | Architectures |
sid | 3.6.1+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
bullseye | 2.12.0+dfsg-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 3.5.2+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
trixie | 3.6.1+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
upstream | 3.9.0 |
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License: DFSG free
|
TIDDIT is a tool to used to identify chromosomal rearrangements using
Mate Pair or Paired End sequencing data. TIDDIT identifies intra and inter-
chromosomal translocations, deletions, tandem-duplications and
inversions, using supplementary alignments as well as discordant pairs.
TIDDIT has two analysis modules. The sv mode, which is used to search
for structural variants. And the cov mode that analyse the read depth of
a bam file and generates a coverage report.
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tipp
tool for Taxonomic Identification and Phylogenetic Profiling
|
Versions of package tipp |
Release | Version | Architectures |
sid | 1.0+dfsg-3 | amd64,arm64 |
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License: DFSG free
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TIPP is a modification of SEPP for classifying query sequences (i.e. reads)
using phylogenetic placement.
TIPP inserts each read into a taxonomic tree and uses the insertion location
to identify the taxonomic lineage of the read. The novel idea behind TIPP is
that rather than using the single best alignment and placement for taxonomic
identification, it uses a collection of alignments and placements and
considers statistical support for each alignment and placement.
TIPP can also be used for abundance estimation by computing an abundance
profile on the reads binned to marker genes in a reference dataset.
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tnseq-transit
statistical calculations of essentiality of genes or genomic regions
|
Versions of package tnseq-transit |
Release | Version | Architectures |
bookworm | 3.2.7-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 3.3.4-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 3.2.1-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
stretch-backports | 2.2.1-2~bpo9+1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 2.3.4-1 | amd64 |
sid | 3.3.4-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
upstream | 3.3.9 |
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License: DFSG free
|
This is a software that can be used to analyze Tn-Seq datasets. It
includes various statistical calculations of essentiality of genes or
genomic regions (including conditional essentiality between 2
conditions). These methods were developed and tested as a collaboration
between the Sassetti lab (UMass) and the Ioerger lab (Texas A&M)
TRANSIT is capable of analyzing TnSeq libraries constructed with Himar1
or Tn5 datasets.
TRANSIT assumes you have already done pre-processing of raw sequencing
files (.fastq) and extracted read counts into a .wig formatted file.
The .wig file should contain the counts at all sites where an insertion
could take place (including sites with no reads). For Himar1 datasets
this is all TA sites in the genome. For Tn5 datasets this would be all
nucleotides in the genome.
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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 |
bookworm | 5.9.2-2+deb12u1 | all |
sid | 6.1.0-4 | 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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|
tombo
identification of modified nucleotides from raw nanopore sequencing data
|
Versions of package tombo |
Release | Version | Architectures |
bookworm | 1.5.1-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 1.5.1-6 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 1.5.1-6 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.5.1-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
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License: DFSG free
|
Tombo is a suite of tools primarily for the identification of modified
nucleotides from nanopore sequencing data. Tombo also provides tools for
the analysis and visualization of raw nanopore signal.
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tophat-recondition
post-processor for TopHat unmapped reads
|
Versions of package tophat-recondition |
Release | Version | Architectures |
bookworm | 1.4-3 | all |
bullseye | 1.4-3 | all |
sid | 1.4-3 | all |
trixie | 1.4-3 | all |
|
License: DFSG free
|
tophat-recondition is a post-processor for TopHat unmapped reads
(contained in unmapped.bam), making them compatible with downstream
tools (e.g., the Picard suite, samtools, GATK) (TopHat issue #17). It
also works around bugs in TopHat:
- the "mate is unmapped" SAM flag is not set on any reads in the
unmapped.bam file (TopHat issue #3)
- the mapped mate of an unmapped read can be absent from
accepted_hits.bam, creating a mismatch between the file and the unmapped
read's flags (TopHat issue #16)
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trinculo
toolkit to carry out genetic association for multi-category phenotypes
|
Versions of package trinculo |
Release | Version | Architectures |
trixie | 0.96+dfsg-4 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 0.96+dfsg-4 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 0.96+dfsg-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 0.96+dfsg-4 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
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License: DFSG free
|
An efficient toolkit for carrying out genetic association for multi-category
phenotypes. Implements multinomial and ordinal association incorporating
covariates, conditional analysis, empirical and non-emperical priors and
fine-mapping.
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umap-learn
Uniform Manifold Approximation and Projection
|
Versions of package umap-learn |
Release | Version | Architectures |
bullseye | 0.4.5+dfsg-2 | all |
bookworm | 0.5.3+dfsg-2 | all |
sid | 0.5.4+dfsg-1 | all |
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License: DFSG free
|
Uniform Manifold Approximation and Projection (UMAP) is a dimension
reduction technique that can be used for visualisation similarly to t-
SNE, but also for general non-linear dimension reduction. The algorithm
is founded on three assumptions about the data:
1. The data is uniformly distributed on a Riemannian manifold;
2. The Riemannian metric is locally constant (or can be
approximated as such);
3. The manifold is locally connected.
From these assumptions it is possible to model the manifold with a fuzzy
topological structure. The embedding is found by searching for a low
dimensional projection of the data that has the closest possible
equivalent fuzzy topological structure.
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umis
tools for processing UMI RNA-tag data
|
Versions of package umis |
Release | Version | Architectures |
trixie | 1.0.9-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
bookworm | 1.0.8-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
bullseye | 1.0.7-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
sid | 1.0.9-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
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License: DFSG free
|
Umis provides tools for estimating expression in RNA-Seq data which
performs sequencing of end tags of transcript, and incorporate molecular
tags to correct for amplification bias.
There are four steps in this process.
1. Formatting reads
2. Filtering noisy cellular barcodes
3. Pseudo-mapping to cDNAs
4. Counting molecular identifiers
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uncalled
Utility for Nanopore Current Alignment to Large Expanses of DNA
|
Versions of package uncalled |
Release | Version | Architectures |
bullseye | 2.2+ds-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 2.3+ds-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 2.3+ds-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 2.2+ds1-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
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License: DFSG free
|
Streaming algorithm for mapping raw nanopore signal to DNA references
Enables real-time enrichment or depletion on Oxford Nanopore Technologies
(ONT) MinION runs via ReadUntil.
Also supports standalone signal mapping of fast5 reads
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unicycler
hybrid assembly pipeline for bacterial genomes
|
Versions of package unicycler |
Release | Version | Architectures |
stretch-backports | 0.4.7+dfsg-1~bpo9+1 | amd64 |
buster | 0.4.7+dfsg-2 | amd64 |
stretch-backports-sloppy | 0.4.8+dfsg-1~bpo9+1 | amd64 |
bullseye | 0.4.8+dfsg-2 | amd64 |
bookworm | 0.5.0+dfsg-1 | amd64 |
trixie | 0.5.0+dfsg-1 | amd64 |
sid | 0.5.0+dfsg-1 | amd64 |
upstream | 0.5.1 |
|
License: DFSG free
|
Unicycler is an assembly pipeline for bacterial genomes. It can assemble
Illumina-only read sets where it functions as a SPAdes-optimiser. It can
also assembly long-read-only sets (PacBio or Nanopore) where it runs a
miniasm+Racon pipeline. For the best possible assemblies, give it both
Illumina reads and long reads, and it will conduct a hybrid assembly.
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vg
tools for working with genome variation graphs
|
Versions of package vg |
Release | Version | Architectures |
bullseye | 1.30.0+ds-1 | amd64,mips64el |
sid | 1.30.0+ds-1 | amd64,mips64el |
upstream | 1.61.0 |
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License: DFSG free
|
variation graph data structures, interchange formats, alignment, genotyping,
and variant calling methods
Variation graphs provide a succinct encoding of the sequences of many genomes.
A variation graph (in particular as implemented in vg) is composed of:
- nodes, which are labeled by sequences and ids
- edges, which connect two nodes via either of their respective ends
- paths, describe genomes, sequence alignments, and annotations (such as gene
models and transcripts) as walks through nodes connected by edges
This model is similar to a number of sequence graphs that have been used in
assembly and multiple sequence alignment. Paths provide coordinate systems
relative to genomes encoded in the graph, allowing stable mappings to be
produced even if the structure of the graph is changed.
Please cite:
Erik Garrison, Jouni Sirén, Adam M Novak, Glenn Hickey, Jordan M Eizenga, Eric T Dawson, William Jones, Shilpa Garg, Charles Markello, Michael F Lin, Benedict Paten and Richard Durbin:
Variation graph toolkit improves read mapping by representing genetic variation in the reference.
(PubMed)
Nature Biotechnology
36(9):875–879
(2018)
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vsearch
tool for processing metagenomic sequences
|
Versions of package vsearch |
Release | Version | Architectures |
sid | 2.29.1-1 | amd64,arm64,mips64el,ppc64el,riscv64 |
stretch | 2.3.4-1 | amd64 |
buster | 2.10.4-1 | amd64 |
bookworm | 2.22.1-1 | amd64,arm64,ppc64el |
bullseye | 2.15.2-3 | amd64,arm64,ppc64el |
trixie | 2.29.1-1 | amd64,arm64,mips64el,ppc64el,riscv64 |
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License: DFSG free
|
Versatile 64-bit multithreaded tool for processing metagenomic sequences,
including searching, clustering, chimera detection, dereplication, sorting,
masking and shuffling
The aim of this project is to create an alternative to the USEARCH tool
developed by Robert C. Edgar (2010). The new tool should:
- have a 64-bit design that handles very large databases and much more
than 4GB of memory
- be as accurate or more accurate than usearch
- be as fast or faster than usearch
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vt
toolset for short variant discovery in genetic sequence data
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Versions of package vt |
Release | Version | Architectures |
bullseye | 0.57721+ds-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 0.57721+ds-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 0.57721+ds-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 0.57721+ds-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
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License: DFSG free
|
vt is a variant tool set that discovers short variants from Next Generation
Sequencing data.
Vt-normalize is a tool to normalize representation of genetic variants in
the VCF. Variant normalization is formally defined as the consistent
representation of genetic variants in an unambiguous and concise way. In
vt a simple general algorithm to enforce this is implemented.
The package is enhanced by the following packages:
vt-examples
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workrave
Repetitive Strain Injury prevention tool
|
Versions of package workrave |
Release | Version | Architectures |
jessie | 1.10.4-3 | amd64,armel,armhf,i386 |
stretch | 1.10.16-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
sid | 1.10.52-5 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 1.10.52-5 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 1.10.50-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 1.10.44-7.1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 1.10.23-5 | amd64,arm64,armhf,i386 |
Debtags of package workrave: |
hardware | input |
interface | x11 |
role | program |
scope | utility |
suite | gnome |
uitoolkit | gtk |
use | monitor |
x11 | applet, application |
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License: DFSG free
|
Workrave is a program that assists in the recovery and prevention of
Repetitive Strain Injury (RSI). The program frequently alerts you to
take micro-pauses, rest breaks and restricts you to your daily limit.
It includes a system tray applet that works with GNOME and KDE
and has network capabilities to monitor your activity even if
switching back and forth between different computers is part of your
job.
Workrave offers many more configuration options than other similar
tools.
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|
wtdbg2
de novo sequence assembler for long noisy reads
|
Versions of package wtdbg2 |
Release | Version | Architectures |
bullseye | 2.5-7 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 2.5-10 | amd64 |
trixie | 2.5-10 | amd64 |
bookworm | 2.5-9 | amd64 |
|
License: DFSG free
|
Wtdbg2 is a de novo sequence assembler for long noisy reads produced by
PacBio or Oxford Nanopore Technologies (ONT). It assembles raw reads
without error correction and then builds the consensus from intermediate
assembly output. Wtdbg2 is able to assemble the human and even the 32Gb
Axolotl genome at a speed tens of times faster than CANU and FALCON
while producing contigs of comparable base accuracy.
During assembly, wtdbg2 chops reads into 1024bp segments, merges similar
segments into a vertex and connects vertices based on the segment
adjacency on reads. The resulting graph is called fuzzy Bruijn graph
(FBG). It is akin to De Bruijn graph but permits mismatches/gaps and
keeps read paths when collapsing k-mers. The use of FBG distinguishes
wtdbg2 from the majority of long-read assemblers.
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yanagiba
filter low quality Oxford Nanopore reads basecalled with Albacore
|
Versions of package yanagiba |
Release | Version | Architectures |
bullseye | 1.0.0-2 | all |
bookworm | 1.0.0-5 | all |
trixie | 1.0.0-5 | all |
sid | 1.0.0-5 | all |
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License: DFSG free
|
Yanagiba is used to filter short or low quality Oxford Nanopore reads
which have been basecalled with Albacore. It takes fastq.gz and an
Albacore summary file as input. If no Albacore summary file is provided
attempt to calculate mean qscore from directly from fastq file using
NanoMath. Note: Calculated quality scores appear to be lower for reads
called with Metrichor, you may need to lower your minqual setting in
this case.
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yanosim
read simulator nanopore DRS datasets
|
Versions of package yanosim |
Release | Version | Architectures |
bullseye | 0.1-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
trixie | 0.1-5 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
sid | 0.1-5 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64 |
bookworm | 0.1-5 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el |
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License: DFSG free
|
Yanosim has three options:
-
yanosim model:
Creates an model of mismatches, insertions and deletions
based on an alignment of nanopore DRS reads to a
reference. Reads should be aligned to a transcriptome
i.e. without spliced alignment, using minimap2. They
should have the cs tag.
2. yanosim quantify:
Quantify the number of reads mapping to each
transcript in a reference, so that the right number
of reads can be simulated.
3. yanosim simulate:
Given a model created using yanosim model, and
per-transcript read counts created using yanosim
simulate, simulate error-prone long-reads from the
given fasta file.
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Official Debian packages with lower relevance
libsimde-dev
Implementations of SIMD instructions for all systems
|
Versions of package libsimde-dev |
Release | Version | Architectures |
bullseye | 0.7.2-4 | all |
bookworm | 0.7.4~rc2-2 | all |
experimental | 0.8.2~rc1-1 | amd64,arm64,armel,armhf,i386,ppc64el,riscv64,s390x |
trixie | 0.8.2-1 | all |
sid | 0.8.2-1 | all |
|
License: DFSG free
|
SIMDe provides fast, portable implementations of SIMD intrinsics on hardware
which doesn't natively support them, such as calling SSE functions on ARM.
There is no performance penalty if the hardware supports the native
implementation (e.g., SSE/AVX runs at full speed on x86, NEON on ARM, etc.).
This makes porting code to other architectures much easier in a few key ways:
First, instead of forcing you to rewrite everything for each architecture,
SIMDe lets you get a port up and running almost effortlessly. You can then
start working on switching the most performance-critical sections to native
intrinsics, improving performance gradually. SIMDe lets (for example) SSE/AVX
and NEON code exist side-by-side, in the same implementation.
Second, SIMDe makes it easier to write code targeting ISA extensions you don't
have convenient access to. You can run NEON code on your x86 machine without an
emulator. Obviously you'll eventually want to test on the actual hardware
you're targeting, but for most development, SIMDe can provide a much easier
path.
SIMDe takes a very different approach from most other SIMD abstraction layers
in that it aims to expose the entire functionality of the underlying
instruction set. Instead of limiting functionality to the lowest common
denominator, SIMDe tries to minimize the amount of effort required to port
while still allowing you the space to optimize as needed.
The current focus is on writing complete portable implementations, though a
large number of functions already have accelerated implementations using one
(or more) of the following:
SIMD intrinsics from other ISA extensions (e.g., using NEON to implement
SSE).
Compiler-specific vector extensions and built-ins such as
__builtin_shufflevector and __builtin_convertvector
Compiler auto-vectorization hints, using:
OpenMP 4 SIMD
Cilk Plus
GCC loop-specific pragmas
clang pragma loop hint directives
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python3-anndata
annotated gene by sample numpy matrix
|
Versions of package python3-anndata |
Release | Version | Architectures |
bookworm | 0.8.0-4 | all |
bullseye | 0.7.5+ds-3 | all |
sid | 0.10.6-1 | all |
upstream | 0.11.1 |
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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-mmtf
binary encoding of biological structures (Python 3)
|
Versions of package python3-mmtf |
Release | Version | Architectures |
trixie | 1.1.3-1 | all |
sid | 1.1.3-1 | all |
bullseye | 1.1.2-3 | all |
bookworm | 1.1.3-1 | all |
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License: DFSG free
|
The macromolecular transmission format (MMTF) is a binary encoding of
biological structures.
This package installs the library for Python 3.
|
|
r-bioc-rsubread
Subread Sequence Alignment and Counting for R
|
Versions of package r-bioc-rsubread |
Release | Version | Architectures |
trixie | 2.18.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bookworm | 2.12.2-1 | amd64,arm64,mips64el,ppc64el,s390x |
sid | 2.18.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bullseye | 2.4.2-1 | amd64,arm64,mips64el,ppc64el,s390x |
upstream | 2.20.0 |
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License: DFSG free
|
Alignment, quantification and analysis of second and third generation
sequencing data. Includes functionality for read mapping, read counting,
SNP calling, structural variant detection and gene fusion discovery.
Can be applied to all major sequencing techologies and to both short
and long sequence reads.
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|
Debian packages in contrib or non-free
bcbio
toolkit for analysing high-throughput sequencing data
|
Versions of package bcbio |
Release | Version | Architectures |
bullseye | 1.2.5-1 (contrib) | all |
buster | 1.1.2-3 | all |
bookworm | 1.2.9-2 (contrib) | all |
sid | 1.2.9-2 (contrib) | all |
|
License: DFSG free, but needs non-free components
|
This package installs the command line tools 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.
This package builds and having it in Debian unstable helps the Debian
developers to synchronize their efforts. But unless a series of external
dependencies are not installed manually, the functionality of bcbio in
Debian is only a shadow of itself. Please use the official distribution
of bcbio for the time being, which means "use conda". The TODO file in
the Debian directory should give an overview on progress for Debian
packaging.
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python3-seqcluster
analysis of small RNA in NGS data
|
Versions of package python3-seqcluster |
Release | Version | Architectures |
bookworm | 1.2.9+ds-3 (contrib) | all |
bullseye | 1.2.7+ds-1 (contrib) | all |
sid | 1.2.9+ds-4 (contrib) | all |
trixie | 1.2.9+ds-4 (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'.
|
varscan
variant detection in next-generation sequencing data
|
Versions of package varscan |
Release | Version | Architectures |
bookworm | 2.4.3+dfsg-4 (non-free) | amd64 |
bullseye | 2.4.3+dfsg-3 (non-free) | amd64 |
jessie | 2.3.7+dfsg-1 (non-free) | amd64 |
sid | 2.4.3+dfsg-4 (non-free) | amd64 |
trixie | 2.4.3+dfsg-4 (non-free) | amd64 |
stretch | 2.4.3+dfsg-1 (non-free) | amd64 |
buster | 2.4.3+dfsg-3 (non-free) | amd64 |
|
License: non-free
|
Variant detection in massively parallel sequencing. For one sample,
calls SNPs, indels, and consensus genotypes. For tumor-normal pairs,
further classifies each variant as Germline, Somatic, or LOH, and also
detects somatic copy number changes.
|
vienna-rna
|
Versions of package vienna-rna |
Release | Version | Architectures |
sid | 2.6.4+dfsg-1 (non-free) | amd64,arm64,armel,armhf,mips64el,ppc64el,riscv64,s390x |
bullseye | 2.4.17+dfsg-2 (non-free) | amd64,arm64,armel,armhf,mips64el,mipsel,ppc64el |
bookworm | 2.5.1+dfsg-1 (non-free) | amd64,arm64,mips64el,ppc64el,s390x |
trixie | 2.6.4+dfsg-1 (non-free) | amd64,arm64,armel,armhf,mips64el,ppc64el,riscv64,s390x |
upstream | 2.7.0 |
|
License: non-free
|
The Vienna RNA Package consists of a C code library and several
stand-alone programs for the prediction and comparison of RNA secondary
structures. It is developed and maintained by the group of Ivo Hofacker
in Vienna.
RNA secondary structure prediction through energy minimization is the
most used function in the package. It provides three kinds of dynamic
programming algorithms for structure prediction:
- the minimum free energy algorithm of (Zuker & Stiegler 1981) which
yields a single optimal structure,
- the partition function algorithm of (McCaskill 1990) which calculates
base pair probabilities in the thermodynamic ensemble, and the
suboptimal folding algorithm of (Wuchty et.al 1999) which generates
all suboptimal structures within a given energy range of the optimal
energy.
For secondary structure comparison, the package contains several
measures of distance (dissimilarities) using either string alignment or
tree-editing (Shapiro & Zhang 1990). Finally, is provided an algorithm
to design sequences with a predefined structure (inverse folding).
The RNAforester package is a tool for aligning RNA secondary structures
and it's user interface integrates to those of the tools of the
Vienna RNA package.
Please cite:
Ronny Lorenz, Stephan H. Bernhart, Christian Höner zu Siederdissen, Hakim Tafer, Christoph Flamm, Peter F. Stadler and Ivo L. Hofacker:
ViennaRNA Package 2.0.
(eprint)
Algorithms for Molecular Biology
6(1):26
(2011)
|
Debian packages in experimental
libtensorflow-framework2
Computation using data flow graphs for scalable machine learning
|
Versions of package libtensorflow-framework2 |
Release | Version | Architectures |
experimental | 2.3.1-1 | amd64 |
|
License: DFSG free
|
TensorFlow is an open source software library for numerical computation
using data flow graphs. The graph nodes represent mathematical operations,
while the graph edges represent the multidimensional data arrays (tensors)
that flow between them. This flexible architecture enables you to deploy
computation to one or more CPUs or GPUs in a desktop, server, or mobile
device without rewriting code.
This package ships shared object libtensorflow_framework.so.2.0
A shared object which includes registration mechanisms for ops and
kernels. Does not include the implementations of any ops or kernels.
Instead, the library which loads libtensorflow_framework.so
(e.g. _pywrap_tensorflow_internal.so for Python, libtensorflow.so for the C
API) is responsible for registering ops with libtensorflow_framework.so. In
addition to this core set of ops, user libraries which are loaded (via
TF_LoadLibrary/tf.load_op_library) register their ops and kernels with this
shared object directly.
For example, from Python tf.load_op_library loads a custom op library (via
dlopen() on Linux), the library finds libtensorflow_framework.so (no
filesystem search takes place, since libtensorflow_framework.so has already
been loaded by pywrap_tensorflow) and registers its ops and kernels via
REGISTER_OP and REGISTER_KERNEL_BUILDER (which use symbols from
libtensorflow_framework.so), and pywrap_tensorflow can then use these
ops. Since other languages use the same libtensorflow_framework.so, op
libraries are language agnostic.
Please cite:
Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Rafal Jozefowicz, Yangqing Jia, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dan Mané, Mike Schuster, Rajat Monga, Sherry Moore, Derek Murray, Chris Olah, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda Viégas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu and and Xiaoqiang Zheng:
TensorFlow: Large-scale machine learning on heterogeneous systems..
(2015)
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|
Packaging has started and developers might try the packaging code in VCS
arvados
managing and analyzing biomedical big data
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Versions of package arvados |
Release | Version | Architectures |
VCS | 2.0.3-1 | all |
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License: Apache-2.0 #FIXME
Debian package not available
Version: 2.0.3-1
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Arvados is an open source platform for managing, processing, and sharing
genomic and other large scientific and biomedical data. With Arvados,
bioinformaticians run and scale compute-intensive workflows, developers
create biomedical applications, and IT administrators manage large
compute and storage resources.
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auspice
web app for visualizing pathogen evolution
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Versions of package auspice |
Release | Version | Architectures |
VCS | 2.10.0-1 | all |
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License: AGPL-3
Debian package not available
Version: 2.10.0-1
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Nextstrain is an open-source project to harness the scientific and
public health potential of pathogen genome data. We provide a continually-
updated view of publicly available data with powerful analytics and
visualizations showing pathogen evolution and epidemic spread. Our goal
is to aid epidemiological understanding and improve outbreak response.
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blat
BLAST-Like Alignment Tool
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Versions of package blat |
Release | Version | Architectures |
VCS | 35-1 | all |
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License: FreeForScientificUse
Debian package not available
Version: 35-1
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BLAT on DNA is designed to quickly find sequences of 95% and greater
similarity of length 25 bases or more. It may miss more divergent or shorter
sequence alignments. It will find perfect sequence matches of 25 bases, and
sometimes find them down to 20 bases. BLAT on proteins finds sequences of 80%
and greater similarity of length 20 amino acids or more. In practice DNA BLAT
works well on primates, and protein blat on land vertebrates.
BLAT is not BLAST. DNA BLAT works by keeping an index of the entire genome in
memory. The index consists of all non-overlapping 11-mers except for those
heavily involved in repeats. The index takes up a bit less than a gigabyte of
RAM. The genome itself is not kept in memory, allowing BLAT to deliver high
performance on a reasonably priced Linux box. The index is used to find areas
of probable homology, which are then loaded into memory for a detailed
alignment. Protein BLAT works in a similar manner, except with 4-mers rather
than 11-mers. The protein index takes a little more than 2 gigabytes.
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chime
COVID-19 Hospital Impact Model for Epidemics
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Versions of package chime |
Release | Version | Architectures |
VCS | 0.2.1-1 | all |
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License: MIT
Debian package not available
Version: 0.2.1-1
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Penn Medicine - COVID-19 Hospital Impact Model for Epidemics
This tool was developed by the Predictive Healthcare team at Penn
Medicine. For questions and comments please see our contact page. Code
can be found on Github. Join our Slack channel if you would like to
get involved!
The estimated number of currently infected individuals is 533. The 91
confirmed cases in the region imply a 17% rate of detection. This is
based on current inputs for Hospitalizations (4), Hospitalization rate
(5%), Region size (4119405), and Hospital market share (15%).
An initial doubling time of 6 days and a recovery time of 14.0 days
imply an R_0 of 2.71.
Mitigation: A 0% reduction in social contact after the onset of the
outbreak reduces the doubling time to 6.0 days, implying an effective
R_t of 2.712.712.71.
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covpipe
pipeline to generate consensus sequences from NGS reads
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Versions of package covpipe |
Release | Version | Architectures |
VCS | 3.0.6-1 | all |
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License: GPL-3+
Debian package not available
Version: 3.0.6-1
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CovPipe is a pipeline to generate consensus sequences from NGS reads
based on a reference sequence. The pipeline is tailored to be used for
SARS-CoV-2 data, but may be used for other viruses.
Genomic variants of your NGS data in comparison to a reference will be
determined. These variants will be included into the reference and form
the consensus sequences. See below for further details on the determined
set of consensus sequences.
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ensembl-vep
Variant Effect Predictor predicting the functional effects of genomic variants
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Versions of package ensembl-vep |
Release | Version | Architectures |
VCS | 100.2-1 | all |
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License: Apache-2.0
Debian package not available
Version: 100.2-1
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The Ensembl Variant Effect Predictor predicts the functional effects of
genomic variants. It has three components:
- VEP (Variant Effect Predictor) predicts the functional effects of
genomic variants.
- Haplosaurus uses phased genotype data to predict whole-transcript
haplotype sequences.
- Variant Recoder translates between different variant encodings.
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fieldbioinformatics
pipeline with virus identification with Nanopore sequencer
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Versions of package fieldbioinformatics |
Release | Version | Architectures |
VCS | 1.1.3-1 | all |
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License: MIT
Debian package not available
Version: 1.1.3-1
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This is the ARTIC bioinformatics pipeline for working with virus sequencing
data, sequenced with nanopore. It implements a complete bioinformatics
protocol to take the output from the Nanopore sequencer and determine consensus
genome sequences. Includes basecalling, de-multiplexing, mapping, polishing
and consensus generation.
An outbreak of SARS-CoV-2, Ebola, ... something unknown? This
software is field-proven.
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flappie
flip-flop basecaller for Oxford Nanopore reads
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Versions of package flappie |
Release | Version | Architectures |
VCS | 2.1.3+ds-1 | all |
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License: Oxford-Nanopore-PL-1.0
Debian package not available
Version: 2.1.3+ds-1
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Basecall Fast5 reads using flip-flop basecalling.
Features
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graphmap2
highly sensitive and accurate mapper for long, error-prone reads
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Versions of package graphmap2 |
Release | Version | Architectures |
VCS | 0.6.4-1 | all |
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License: MIT
Debian package not available
Version: 0.6.4-1
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GraphMap2 is a highly sensitive and accurate mapper for long, error-
prone reads. The mapping algorithm is designed to analyse nanopore
sequencing reads, which progressively refines candidate alignments to
robustly handle potentially high-error rates and a fast graph traversal
to align long reads with speed and high precision (>95%). Evaluation on
MinION sequencing data sets against short- and long-read mappers
indicates that GraphMap increases mapping sensitivity by 10–80% and maps
95% of bases. GraphMap alignments enabled single-nucleotide variant
calling on the human genome with increased sensitivity (15%) over the
next best mapper, precise detection of structural variants from length
100 bp to 4 kbp, and species and strain-specific identification of
pathogens using MinION reads.
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manta
structural variant and indel caller for mapped sequencing data
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Versions of package manta |
Release | Version | Architectures |
VCS | 1.6.0+dfsg-1 | all |
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License: GPL-3+
Debian package not available
Version: 1.6.0+dfsg-1
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Manta calls structural variants (SVs) and indels from mapped paired-end
sequencing reads. It is optimized for analysis of germline variation in
small sets of individuals and somatic variation in tumor/normal sample
pairs. Manta discovers, assembles and scores large-scale SVs, medium-
sized indels and large insertions within a single efficient workflow.
The method is designed for rapid analysis on standard compute hardware:
NA12878 at 50x genomic coverage is analyzed in less than 20 minutes on a
20 core server, and most WGS tumor/normal analyses can be completed
within 2 hours. Manta combines paired and split-read evidence during SV
discovery and scoring to improve accuracy, but does not require split-
reads or successful breakpoint assemblies to report a variant in cases
where there is strong evidence otherwise. It provides scoring models for
germline variants in small sets of diploid samples and somatic variants
in matched tumor/normal sample pairs. There is experimental support for
analysis of unmatched tumor samples as well. Manta accepts input read
mappings from BAM or CRAM files and reports all SV and indel inferences
in VCF 4.1 format.
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medaka
sequence correction provided by ONT Research
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Versions of package medaka |
Release | Version | Architectures |
VCS | 1.0.3+dfsg-1 | all |
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License: MPL-2.0
Debian package not available
Version: 1.0.3+dfsg-1
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Medaka is a tool to create a consensus sequence from nanopore sequencing
data. This task is performed using neural networks applied from a pileup
of individual sequencing reads against a draft assembly. It outperforms
graph-based methods operating on basecalled data, and can be competitive
with state-of-the-art signal-based methods, whilst being much faster.
Features
- Requires only basecalled data. (.fasta or .fastq)
- Improved accurary over graph-based methods (e.g. Racon).
- 50X faster than Nanopolish (and can run on GPUs).
- Methylation aggregation from Guppy .fast5 files.
- Benchmarks are provided here.
- Includes extras for implementing and training bespoke
correction networks.
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nanoplot
plotting scripts for long read sequencing data
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Versions of package nanoplot |
Release | Version | Architectures |
VCS | 1.36.2-1 | all |
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License: MIT
Debian package not available
Version: 1.36.2-1
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NanoPlot provides plotting scripts for long read sequencing data.
These scripts perform data extraction from Oxford Nanopore sequencing data
in the following formats:
- fastq files (optionally compressed)
- fastq files generated by albacore, guppy or MinKNOW containing additional
information (optionally compressed)
- sorted bam files
- sequencing_summary.txt output table generated by albacore, guppy or
MinKnow basecalling (optionally compressed)
- fasta files (optionally compressed)
- multiple files of the same type can be offered simultaneously
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ncbi-magicblast
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Versions of package ncbi-magicblast |
Release | Version | Architectures |
VCS | 1.5.0+ds-1 | all |
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License: PD
Debian package not available
Version: 1.5.0+ds-1
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Magic-BLAST is a tool for mapping large next-generation RNA or DNA
sequencing runs against a whole genome or transcriptome. Each alignment
optimizes a composite score, taking into account simultaneously the two
reads of a pair, and in case of RNA-seq, locating the candidate introns
and adding up the score of all exons. This is very different from other
versions of BLAST, where each exon is scored as a separate hit and read-
pairing is ignored.
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nextflow
DSL for data-driven computational pipelines
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Versions of package nextflow |
Release | Version | Architectures |
VCS | 23.10.1+dfsg-1 | all |
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License: Apache-2.0
Debian package not available
Version: 23.10.1+dfsg-1
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Nextflow is a bioinformatics workflow manager that enables the
development of portable and reproducible workflows. It supports
deploying workflows on a variety of execution platforms including local,
HPC schedulers, AWS Batch, Google Genomics Pipelines, and Kubernetes.
Additionally, it provides support for manage your workflow dependencies
through built-in support for Conda, Docker, Singularity, and Modules.
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nextstrain-ncov
Nextstrain build for novel coronavirus (nCoV)
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Versions of package nextstrain-ncov |
Release | Version | Architectures |
VCS | 0.0+git20200320.392dc1c-1 | all |
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License: MIT
Debian package not available
Version: 0.0+git20200320.392dc1c-1
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This is a Nextstrain build for novel coronavirus, alternately known as
hCoV-19 or SARS-CoV-2, visible at https://nextstrain.org/ncov .
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nf-core-artic
nf-core ARTIC field bioinformatics viral genome pipeline
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Versions of package nf-core-artic |
Release | Version | Architectures |
VCS | 0.0+git20200324.9edd884-1 | all |
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License: free
Debian package not available
Version: 0.0+git20200324.9edd884-1
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RNA-seq workflow for nextflow, meant to form a a bioinformatics pipeline
for working with virus sequencing data sequenced with nanopore. This is
a reimplementation for the nextflow workflow suite of the ARTIC
fieldbioinformatics protocol.
This package at the very moment is not much more than a technical exercise.
Upstream tagged it as "under development" - and that is what it is here,
too.
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oncofuse
predicting oncogenic potential of gene fusions
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Versions of package oncofuse |
Release | Version | Architectures |
VCS | 1.1.1-1 | all |
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License: Apache-2.0
Debian package not available
Version: 1.1.1-1
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Oncofuse is a framework designed to estimate the oncogenic potential of
de-novo discovered gene fusions. It uses several hallmark features and
employs a bayesian classifier to provide the probability of a given gene
fusion being a driver mutation.
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optitype
precision HLA typing from next-generation sequencing data
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Versions of package optitype |
Release | Version | Architectures |
VCS | 1.3.2-1 | all |
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License: <license>
Debian package not available
Version: 1.3.2-1
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OptiType is a novel HLA genotyping algorithm based on integer linear
programming, capable of producing accurate 4-digit HLA genotyping
predictions from NGS data by simultaneously selecting all major and
minor HLA Class I alleles.
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pangolin
Phylogenetic Assignment of Named Global Outbreak LINeages
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Versions of package pangolin |
Release | Version | Architectures |
VCS | 4.3.1-1 | all |
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License: GPL-3+
Debian package not available
Version: 4.3.1-1
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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.
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pomoxis
analysis components from Oxford Nanopore Research
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Versions of package pomoxis |
Release | Version | Architectures |
VCS | 0.3.4-1 | all |
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License: MPL-2.0
Debian package not available
Version: 0.3.4-1
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Pomoxis comprises a set of basic bioinformatic tools tailored to
nanopore sequencing. Notably tools are included for generating and
analysing draft assemblies. Many of these tools are used by the research
data analysis group at Oxford Nanopore Technologies.
Features
- Wraps third party tools with known good default parameters and
methods of use.
- Creates an isolated environment with all third-party tools.
- Streamlines common short analysis chains.
- Integrates into katuali for performing more complex analysis
pipelines.
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python3-idseq-dag
Pipeline engine for IDseq (Python 3)
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Versions of package python3-idseq-dag |
Release | Version | Architectures |
VCS | 4.2.3-1 | all |
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License: MIT
Debian package not available
Version: 4.2.3-1
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Idseq_dag is the pipeline execution engine for idseq
(see idseq.net). It is a pipelining system that implements
a directed acyclic graph (DAG) where the nodes (steps)
correspond to individual python classes. The graph is
defined using JSON.
The pipeline would be executed locally with local machine
resources. idseq-dag could be installed inside a docker
container and run inside the container.
This package installs the library for Python 3.
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python3-scanpy
Single-Cell Analysis in Python
|
Versions of package python3-scanpy |
Release | Version | Architectures |
VCS | 1.9.6-1 | all |
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License: BSD-3-Clause
Debian package not available
Version: 1.9.6-1
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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.
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qualimap
evaluating next generation sequencing alignment data
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Versions of package qualimap |
Release | Version | Architectures |
VCS | 2.2.1+dfsg-1 | all |
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License: GPL-2+
Debian package not available
Version: 2.2.1+dfsg-1
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Qualimap 2 provides both a Graphical User Interface (GUI) and a
command-line interface to facilitate the quality control of alignment
sequencing data and its derivatives like feature counts.
Supported types of experiments include:
- Whole-genome sequencing
- Whole-exome sequencing
- RNA-seq (speical mode available)
- ChIP-seq
Qualimap examines sequencing alignment data in SAM/BAM files according
to the features of the mapped reads and provides an overall view of the
data that helps to the detect biases in the sequencing and/or mapping of
the data and eases decision-making for further analysis.
Qualimap provides multi-sample comparison of alignment and counts data.
- Fast analysis accross the reference of genome coverage and nucleotide
distribution;
- Easy to interpret summary of the main properties of the
alignment data;
- Analysis of the reads mapped inside/outside of the regions provided
in GFF format;
- Computation and analysis of read counts obtained from intersectition
of read alignments with genomic features;
- Analysis of the adequasy of the sequencing depth in RNA-seq
experiments;
- Multi-sample comparison of alignment and counts data;
- Clustering of epigenomic profiles.
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quast
Quality Assessment Tool for Genome Assemblies
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Versions of package quast |
Release | Version | Architectures |
VCS | 5.0.2+dfsg-1 | all |
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License: GPL-2
Debian package not available
Version: 5.0.2+dfsg-1
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QUAST evaluates genome assemblies. For metagenomes, please see MetaQUAST
project. It works both with and without a given reference genome.
The tool accepts multiple assemblies, thus it allows for comparisons.
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r-cran-covid19
GNU R Coronavirus COVID-19 data acquisition and visualization
|
Versions of package r-cran-covid19 |
Release | Version | Architectures |
VCS | 0.2.1-1 | all |
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License: GPL-3
Debian package not available
Version: 0.2.1-1
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This GNU R package provides pre-processed, ready-to-use, tidy format
datasets of the 2019 Novel Coronavirus COVID-19 (2019-nCoV) epidemic. The
latest data are downloaded in real-time, processed and merged with
demographic indicators from several trusted sources. The package
implements advanced data visualization across the space and time
dimensions by means of animated mapping. Besides worldwide data,
the package includes granular data for Italy, Switzerland and the
Diamond Princess.
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r-other-fastbaps
A fast genetic clustering algorithm that approximates a Dirichlet Process Mixture model
|
Versions of package r-other-fastbaps |
Release | Version | Architectures |
VCS | 1.0.4-1 | all |
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License: MIT
Debian package not available
Version: 1.0.4-1
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Takes a multiple sequence alignment as input and clusters according to the 'no-admixture' model.
It combines ideas from the Bayesian Hierarchical Clustering algorithm of Heller et al.
and hierBAPS to produce a rapid and accurate clustering algorithm.
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rosa
Removal of Spurious Antisense in biological RNA sequences
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Versions of package rosa |
Release | Version | Architectures |
VCS | 1.0-1 | all |
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License: GPL-3.0+
Debian package not available
Version: 1.0-1
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In stranded RNA-Seq experiments it is possible to detect and
measure antisense transcription, important since antisense transcripts
impact gene transcription in several different ways. Stranded RNA-Seq
determines the strand from which an RNA fragment originates, and so can
be used to identify where antisense transcription may be implicated in
gene regulation.
However, spurious antisense reads are often present in experiments, and
can manifest at levels greater than 1% of sense transcript levels. This
is enough to disrupt analyses by causing false antisense counts to
dominate the set of genes with high antisense transcription levels.
The RoSA (Removal of Spurious Antisense) tool detects the presence of
high levels of spurious antisense transcripts, by:
- analysing ERCC spike-in data to find the ratio of antisense:sense
transcripts in the spike-ins; or
- using antisense and sense counts around splice sites to provide a
set of gene-specific estimates; or
- both.
Once RoSA has an estimate of the spurious antisense, expressed as a
ratio of antisense:sense counts, RoSA will calculate a correction to
the antisense counts based on the ratio. Where a gene-specific estimate
is available for a gene, it will be used in preference to the global
estimate obtained from either spike-ins or spliced reads.
This package provides the library for the statistics suite R.
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sailfish
RNA-seq expression estimation
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Versions of package sailfish |
Release | Version | Architectures |
VCS | 0.10.1+dfsg-1 | all |
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License: GPL-3.0+
Debian package not available
Version: 0.10.1+dfsg-1
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RNA-seq is a technology to read at least parts of individual RNA
sequences of a tissue sample. After assigning these reads to genes
that are likely responsible to have coded for them (mapping), this
gives an insight (estimate) about how much these genes have been
active (expressed) in that sample. The trickier bits in that process
to address is the similarity of genes and the genes being capable to
variably but deterministically skip parts of their sequence to be read
(introns). A single variantly spliced gene may then yield different
sequences (isoforms) and the RNA-seq evaluation better informs about
this. It may be relevant for a disease.
Sailfish is particularly good (efficient) in this process. It tricks
the complexity by introducing an intermediate level of artificial very
short reads to which the alternative splicing is of no concern. That
can then be addressed by "telephone-book"-like hashing techniques that
are easy and lightning fast. The final presentation is then found to
be competitive with established mappers like eXpress and Cufflinks.
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seqwish
alignment to variation graph inducer
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Versions of package seqwish |
Release | Version | Architectures |
VCS | 0.7.1-1 | all |
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License: MIT
Debian package not available
Version: 0.7.1-1
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Seqwish implements a lossless conversion from pairwise alignments
between sequences to a variation graph encoding the sequences and their
alignments. As input we typically take all-versus-all alignments, but
the exact structure of the alignment set may be defined in an
application specific way. This algorithm uses a series of disk-backed
sorts and passes over the alignment and sequence inputs to allow the
graph to be constructed from very large inputs that are commonly
encountered when working with large numbers of noisy input sequences.
Memory usage during construction and traversal is limited by the use of
sorted disk-backed arrays and succinct rank/select dictionaries to
record a queryable version of the graph.
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signalalign
HMM-HDP models for MinION signal alignments
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Versions of package signalalign |
Release | Version | Architectures |
VCS | 0.0+git20170131.3293fad+dfsg-1 | all |
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License: MIT
Debian package not available
Version: 0.0+git20170131.3293fad+dfsg-1
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MinION signal-level alignment and methylation detection using hidden
Markov Models with hierarchical Dirichlet process kmer learning.
Nanopore sequencing is based on the principal of isolating a nanopore in
a membrane separating buffered salt solutions, then applying a voltage
across the membrane and monitoring the ionic current through the
nanopore. The Oxford Nanopore Technologies (ONT) MinION sequences DNA by
recording the ionic current as DNA strands are enzymatically guided
through the nanopore. SignalAlign will align the ionic current from the
MinION to a reference sequence using a trainable hidden Markov model
(HMM). The emissions model for the HMM can either be the table of
parametric normal distributions provided by ONT or a hierarchical
Dirichlet process (HDP) mixture of normal distributions. The HDP models
enable mapping of methylated bases to your reference sequence.
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streamlit
fast way to build custom ML tools
|
Versions of package streamlit |
Release | Version | Architectures |
VCS | 0.56.0-1 | all |
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License: Apache-2.0
Debian package not available
Version: 0.56.0-1
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Streamlit lets you create apps for your machine learning projects with
deceptively simple Python scripts. It supports hot-reloading, so your
app updates live as you edit and save your file. No need to mess with
HTTP requests, HTML, JavaScript, etc. All you need is your favorite
editor and a browser.
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strelka
strelka2 germline and somatic small variant caller
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Versions of package strelka |
Release | Version | Architectures |
VCS | 2.9.10+dfsg-1 | all |
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License: GPL-3+
Debian package not available
Version: 2.9.10+dfsg-1
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Strelka2 is a fast and accurate small variant caller optimized for
analysis of germline variation in small cohorts and somatic variation in
tumor/normal sample pairs. The germline caller employs an efficient
tiered haplotype model to improve accuracy and provide read-backed
phasing, adaptively selecting between assembly and a faster alignment-
based haplotyping approach at each variant locus. The germline caller
also analyzes input sequencing data using a mixture-model indel error
estimation method to improve robustness to indel noise. The somatic
calling model improves on the original Strelka method for liquid and late-
stage tumor analysis by accounting for possible tumor cell contamination
in the normal sample. A final empirical variant re-scoring step using
random forest models trained on various call quality features has been
added to both callers to further improve precision.
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ufasta
utility to manipulate fasta files
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Versions of package ufasta |
Release | Version | Architectures |
VCS | 0.0.3+git20190131.85d60d1-1 | all |
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License: to_be_clarified
Debian package not available
Version: 0.0.3+git20190131.85d60d1-1
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Description of ufasta subcommands:
- one: remove the new lines in the data section. Hence, all the
sequences are written on one line. In some sense, it is the opposite
of the format subcommand.
- format: reformat the data sections. The data is written in lines of
the same length, it can changes the content in upper/lower case.
- sizes: print the amount of sequence in each section
- head: like UNIX head. Display the first 10 sequences
- tail: like UNIX tail. Display the last 10 sequences
- rc: reverse complement every sequence
- n50, stats: display stats about the sequences: N50, E size, total
size, etc.
- extract: extract a sequence whose header match given names
- hsort, sort: sort file based on header content
- dsort: sort the data sections
- hgreap: output sequences whose header match the regular expression
- dgresp: output sequences whose sequence match the regular expression
- split: split a fasta file into many files
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vadr
classification and annotation of viral sequences
|
Versions of package vadr |
Release | Version | Architectures |
VCS | 1.2.1-1 | all |
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License: public_domain
Debian package not available
Version: 1.2.1-1
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VADR (Viral Annotation DefineR) is a suite of tools for classifying and
analyzing sequences homologous to a set of reference models of viral
genomes or gene families. It has been mainly tested for analysis of
Norovirus and Dengue virus sequences in preparation for submission to
the GenBank database and finds its application also for the ongoing
pandemics.
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