Task: Next Generation Sequencing
Metapackage: false
Description: Debian Med bioinformatics applications usable in Next Generation Sequencing
 It aims at gettting packages which specializes in alignment of
 sequences produced by next generation sequencing.

Comment: Do not build a metapackage because it is not clear in how far this set of
 packages is complete regarding NGS.

Depends:
	bedtools,
	bwa,
	bowtie,
	blasr,
	daligner,
	mhap,
	fastx-toolkit,
	filo,
	last-align,
	maq,
	picard-tools,
	r-bioc-edger,
	r-bioc-hilbertvis,
	rna-star,
	samtools,
	sra-toolkit,
	ssake,
	tabix,
	tophat,
	bcftools,
	vcftools,
	velvet

Depends: sprai

Depends: mothur

Depends: qiime

Depends: cufflinks

Depends: mira-assembler

X-Mark: Prospective packages are starting here.

Depends: kissplice

X-Mark: Packages in Vcs - Information about these is queried from UDD as well

Depends: scoary

Depends: umap

Depends: dindel

Depends: mosaik-aligner

Depends: forge
Homepage: http://combiol.org/forge/
License: Apache 2.0
Pkg-Description: genome assembler for mixed read types
 Forge Genome Assembler is a parallel, MPI based genome assembler for
 mixed read types.
 .
 Forge is a classic "Overlap layout consensus" genome assembler written
 by Darren Platt and Dirk Evers. Implemented in C++ and using the
 parallel MPI library, it runs on one or more machines in a network and
 can scale to very large numbers of reads provided there is enough
 collective memory on the machines used. It generates a full consensus
 alignment of all reads, can handle mixtures of sanger, 454 and illumina
 reads. There is some support for solid color space and it includes built
 in tools for vector trimming and contamination screening.
 .
 Forge and was originally developed at Exelixis and they have kindly
 agreed to place the software which underwent much subsequent development
 outside Exelixis, into the public domain. Forge works with most of the
 common MPI implementations.
Remark: Competitor to MIRA2 and wgs-assembler
 This package was requested by William Spooner <whs@eaglegenomics.com> as
 a competitor to MIRA2 and wgs-assembler.

Depends: uc-echo

Depends: annovar
Homepage: http://www.openbioinformatics.org/annovar/
License: Open Source for non-profit
Pkg-Description: annotate genetic variants detected from diverse genomes
 ANNOVAR is an efficient software tool to utilize update-to-date information
 to functionally annotate genetic variants detected from diverse genomes
 (including human genome hg18, hg19, as well as mouse, worm, fly, yeast and
 many others). Given a list of variants with chromosome, start position, end
 position, reference nucleotide and observed nucleotides, ANNOVAR can perform:
 .
  1. Gene-based annotation: identify whether SNPs or CNVs cause protein coding
     changes and the amino acids that are affected. Users can flexibly use RefSeq
     genes, UCSC genes, ENSEMBL genes, GENCODE genes, or many other gene definition
     systems.
  2. Region-based annotations: identify variants in specific genomic regions,
     for example, conserved regions among 44 species, predicted transcription
     factor binding sites, segmental duplication regions, GWAS hits, database
     of genomic variants, DNAse I hypersensitivity sites, ENCODE
     H3K4Me1/H3K4Me3/H3K27Ac/CTCF sites, ChIP-Seq peaks, RNA-Seq peaks, or many
     other annotations on genomic intervals.
  3. Filter-based annotation: identify variants that are reported in dbSNP,
     or identify the subset of common SNPs (MAF>1%) in the 1000 Genome Project,
     or identify subset of non-synonymous SNPs with SIFT score>0.05, or many
     other annotations on specific mutations.
  4. Other functionalities: Retrieve the nucleotide sequence in any
     user-specific genomic positions in batch, identify a candidate gene list
     for Mendelian diseases from exome data, identify a list of SNPs from
     1000 Genomes that are in strong LD with a GWAS hit, and many other
     creative utilities.
 .
 In a modern desktop computer (3GHz Intel Xeon CPU, 8Gb memory), for
 4.7 million variants, ANNOVAR requires ~4 minutes to perform
 gene-based functional annotation, or ~15 minutes to perform stepwise
 "variants reduction" procedure, making it practical to handle hundreds
 of human genomes in a day.
