Debian Fun Covid-19 packages

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.

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.

Reads one (or more) alignment files (sorted BAM) and prints a BED with the coverage. It will join consecutive bases with the same coverage, and can be used to only print a BED file with the regions having a specific coverage range.

Acacia is a java program developed to quickly and conservatively correct errors, whilst simultaneously de-replicating, amplicon sequences.

The main purpose of Acacia is to correct the over-call, under-call errors prevalent in Roche 454 GS-FLX data, and more recently, with the Titanium chemistry. Acacia will only ectively correct errors in amplicons - as it assumes that the 5' end of the sequences start at the same position, the MID, followed by the primer. Acacia uses empirically-derived models to identify homopolymer regions where there are more `errors' than expected by chance - these imply that the differences are due to population differences rather than error-induced polymorphisms.

Nat Methods. 2012 Apr 27;9(5):425-6. doi: 10.1038/nmeth.1990. Fast, accurate error-correction of amplicon pyrosequences using Acacia. Bragg L, Stone G, Imelfort M, Hugenholtz P, Tyson GW.