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This plugins is intended to wrap the common software used for Next Generation Sequencing data


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Provides a framework for handling NGS data with Bioruby.

Features & Aims

  • Supports many tools for NGS: SAMtools, BWA, Bowtie, TopHat, Cufflinks
  • Avoids conflicts: required tools and libraries are installed in a sandbox
  • Detect pre insalled software at runtime
  • Reporting: text and graphs
  • Simple API for developing your own scripts in Ruby



Quick Start

gem install bio-ngs
  • Gems dependencies resolved by RubyGems
  • External software will be downloaded, compiled and installed in a sandbox
  • No root grants required, no conflict with pre installed applications

Install third party software (by default this feature is disabled)

gem install bio-ngs -- --install-third-party
  • Using system wide software

Pleas follow the instruction for your own distribution/operating system


We'll try to keep this list updated but just in case type biongs -T to get the most updated list.
We are working on these and other tasks, if you find some bugs, please open an issue on Github.


biongs bwa:aln [PREFIX] [FASTA/Q]                                                      # Run BWA aln (short reads)
biongs bwa:bwasw [PREFIX] [FASTA/Q]                                                    # Run BWA bwasw (long reads)
biongs bwa:fastmap [PREFIX] [FASTA/Q]                                                  # Run BWA Fastmap (identify super-maximal exact matches)
biongs bwa:index [FASTA]                                                               # Create BWA index
biongs bwa:sampe [PREFIX] [SAI-1 FILE] [SAI-2 FILE] [FASTA/Q-1 FILE] [FASTA/Q-2 FILE]  # Run BWA SAM Paired End conversion
biongs bwa:samse [PREFIX] [SAI FILE] [FASTA/Q FILE]                                    # Run BWA SAM Single End conversion


Most of this tasks create sub-processes to speed up conversions

biongs convert:bam:extract_genes BAM GENES --ensembl-release=N -o, --output=OUTPUT  # Extract GENES from bam. It connects to Ensembl Humnan,...
biongs convert:bam:merge -i, --input-bams=one two three                             # Merge multiple bams in a single one, BAMS separated by...
biongs convert:bam:sort BAM [PREFIX]                                                # Sort and create and index for the BAM file name
biongs convert:bcl:fastq:configure_conversion RUNDIR DATAOUTDIR                     # Configure the specific Run to be converted
biongs convert:bcl:fastq:convert RUNDIR DATAOUTDIR [SAMPLESHEET]                    # Convert a bcl dataset in fastq. By default it creates a
                                                                                      directory with the same name of the dir attachin...
biongs convert:bcl:fastq:start_conversion CONF_DATA_DIR                             # Start the conversion
biongs convert:bcl:qseq:convert RUN OUTPUT [JOBS]                                   # Convert a bcl dataset in qseq
biongs convert:illumina:de:gene DIFF GTF                                            # extract the transcripts
biongs convert:illumina:de:isoform DIFF GTF                                         # extract the transcripts
biongs convert:illumina:de:rename_qs DIFF_FILE NAMES                                # rename q1,...,qn with names provided by the user(comma...
biongs convert:illumina:fastq:trim_b FASTQ                                          # perform a trim on all the sequences on B qualities wit...
biongs convert:illumina:humanize:build_compare_kb GTF                               # Build the JSON file with the annoation from the GTF fi...
biongs convert:illumina:humanize:isoform_exp GTF ISOFORM                            # tag the XLOC gathering information from GTF (ensembl)
biongs convert:qseq:fastq:by_file FIRST OUTPUT                                      # Convert a qseq file into fastq
biongs convert:qseq:fastq:by_lane LANE OUTPUT                                       # Convert all the file in the current and descendant dir...
biongs convert:qseq:fastq:by_lane_index LANE INDEX OUTPUT                           # Convert the qseq from a line and index in a fastq file
biongs convert:qseq:fastq:samples_by_lane SAMPLES LANE OUTPUT                       # Convert the qseqs for each sample in a specific lane. 
                                                                                      SAMPLES is an array of index codes separated by commas lane
                                                                                      is an integer


biongs filter:by_list TABLE LIST            # Extract from TABLE the row with a key in LIST
biongs filter:cufflinks:tra_at_idx GTF IDX  # Extract transcript(s) from Cufflinks' GTF at a specific location or givin the transcript name,...
biongs filter:cufflinks:transcripts [GTF]   # Extract transcripts from Cufflinks' GTF


biongs history:clear  # Wipe out the tasks history


biongs homology:convert:blast2text [XML FILE] --file-out=FILE_OUT  # Convert Blast output to tab-separated file
biongs homology:convert:go2json                                    # Convert the GO annotations from the db into a JSON file
biongs homology:db:export [TABLE] --fileout=FILEOUT                # Export the data from a table to a tab-separated file
biongs homology:db:init                                            # Initialize Homology DB
biongs homology:download:all                                       # Download the Uniprot and GO Annotation file
biongs homology:download:goannotation                              # Download the Uniprot GeneOntology Annotation file
biongs homology:download:uniprot                                   # Download the Uniprot-SwissProt file from UniprotKB
biongs homology:load:blast [FILE]                                  # Parse Blast XML output and load the results into Homology DB
biongs homology:load:goa                                           # Import GO Annotation file
biongs homology:report:blast                                       # Output a graphical report on the Blast homology search


biongs install:tools  # Download and install NGS tools


biongs ontology:db:export [TABLE] --fileout=FILEOUT  # Export the data from a table to a tab-separated file
biongs ontology:db:init                              # Initialize Ontology DB
biongs ontology:download:all                         # Download the GO files
biongs ontology:download:go                          # Download the GeneOntology file
biongs ontology:download:goslim                      # Download the Uniprot GeneOntology Slim file
biongs ontology:load:genego [FILE]                   # Import Gene-GO file (JSON)
biongs ontology:load:go [FILE]                       # Import GO definition file
biongs ontology:report:go                            # Output a graphical report on the GO for the sequences annotated in the db


biongs pre:illumina_filter [DIR(s)]  # Filter the data using Y/N flag in FastQ headers (Illumina). Search for fastq.gz files within director...
biongs pre:merge [file(s)]           # Merge together fastQ files (accepts wildcards)
biongs pre:paired_merge [file(s)]    # Merge together FastQ files while checking for correct pairing (accepts wildcards)
biongs pre:trim [fastq(s)]           # Calulate quality profile and trim the all the reads using FastX (accepts wildcards)
biongs pre:uncompress [file(s)]      # Uncompress multiple files in parallel (accepts wildcards)


biongs project:new [NAME]     # Create a new NGS project directory


biongs quality:boxplot FASTQ_QUALITY_STATS                   # plot reads quality as boxplot
biongs quality:fastq_stats FASTQ                             # Reports quality of FASTQ file
biongs quality:illumina_b_profile_raw FASTQ --read-length=N  # perform a profile for reads coming fom Illumina 1.5+ and write the report in ...
biongs quality:illumina_b_profile_svg FASTQ --read-length=N  # perform a profile for reads coming fom Illumina 1.5+
biongs quality:illumina_projects_stats                       # Reports quality of FASTQ files in an Illumina project directory
biongs quality:nucleotide_distribution FASTQ_QUALITY_STATS   # plot reads quality as boxplot
biongs quality:quality_trim FASTQ                            # Trim all the sequences using quality information
biongs quality:reads FASTQ                                   # perform quality check for NGS reads
biongs quality:reads_coverage FASTQ_QUALITY_STATS            # plot reads coverage in bases
biongs quality:scatterplot EXPR1 EXPR2 OUTPUT                # plot quantification values as scatterplot in png format


biongs rna:compare GTF_REF OUTPUTDIR GTFS_QUANTIFICATION  # GTFS_QUANTIFICATIONS, use a comma separated list of gtf
biongs rna:idx2fasta INDEX FASTA                          # Create a fasta file from an indexed genome, using bowtie-inspect
biongs rna:mapquant DIST INDEX OUTPUTDIR FASTQS           # map and quantify
biongs rna:merge GTF_REF FASTA_REF ASSEMBLY_GTF_LIST      # GTFS_QUANTIFICATIONS, use a comma separated list of gtf
biongs rna:quant GTF OUTPUTDIR BAM                        # Genes and transcripts quantification
biongs rna:quantdenovo GTF_guide OUTPUTDIR BAM            # Genes and transcripts quantification discovering de novo transcripts
biongs rna:tophat DIST INDEX OUTPUTDIR FASTQS             # run tophat as from command line, default 6 processors and then create a sorted b...


biongs sff:extract [FILE]  # Run sff_extract on a SFF file



Extract gene(s) alignment from a BAM

biongs convert:bam:extract_genes your_original.bam BLID,GATA3,PTPRC --ensembl_release=61 --ensembl_specie=homo_sapiens

Demultiplex an Illumina Run.

By default Illumina uses SampleSheet.csv in the your_run/Data/Intensities/BaseCalls file to describe the layout of your run


We expect to find SampleSheet.csv in your run directory, in case of a custom name user can pass it as last parameter --sample_sheet=your_sample_sheet.csv.
To demultiplex your experiment

ngs biongs convert:bcl:fastq:convert /bio/ngs/raw/110321_H001_0100_AD10TMACXX/ /bio/ngs/data/110321_H001_0100_AD10TMACXX_DATA --cpu=8 > 110321_H125_0100_AD10TMACXX.log 2>&1

This command will save the stdout on a log file in the current directory. You must specify the source directory and the destination. You can select the number of CPU to use for demultiplexing, 8 is the maximum value becase 8 lanes.
Typing biongs help convert:bcl:fastq:convert you can have a list of sub tasks. Where biongs convert:bcl:fastq:configure_conversion RUNDIR DATAOUTDIR corresponds to configureBclToFastq.pland biongs convert:bcl:fastq:start_conversion to make in the demultiplexed directory.


When you have your mapped reads to a reference genome, you can decide to filter the output (GTF) to extract only those transcripts which have your desired requirements. You can filter for lenght, if it's multi or mono exon, the coverage, if it's a brand new transcript or an altrady annotated gene but with a new isoform or just the annotated transcripts.

Scenario: filtering transcripts
Having a transcripts.gtf dataset generated from CufflinksQuantification
I want a only the new transcripts (also with an annotated gene)
Which are multi exons
With a lenght greater than 1340
With minimum coverage greater than 10
Then I want to save them in my_filtered_data.gtf

biongs filter:cufflinks:transcripts your_original.gtf -m -l 1340 -c 10.0 -n -o my_filtered_data.gtf

Then in some case I need to extract only some of them or maybe parsing them from external programs. Biongs has a specific trask for this:

Having my_filtered_data.gtf
Generated by "filtering transcripts"
I want to extract transcript number 10
Then I want to save it in BED format
Using UCSC notation

biongs filter:cufflinks:tra_at_idx my_filtered_data.gtf #of_the_transcript_to_retrieve -u 

The first time tra_at_idx is used, it will take more time than usual becase it creates an internal index: a simple HASH mashalled and dumped, stored in a file with the name similar to the imput with an idx as postfix.

Interacting with the FileSystem

Following the concept of convention over configuration BioNGS can discover types of files in your project directory. Suppose you have trimmed fastq (rtf) from a project and you want to select just the forward trimmed fastq files:

biongs smart:data Project rtf "|:Sample1:Sample2:Sample3:Sample4:Sample5" --root path_to_your_data_directory

you'll get the list of files with this this features. To speed up the search, discovered and tagged files are dumped locally in path_to_your_data_directory under conf directory.

Type of files

Biongs has predefined tag system. In the future it will be more general and a custom configuration file will be accepted. In the mean time, these are the predefined tags

            :cufflinks=>{rules:[/genes\.fpkm_traking/, #same for denovo
                         /isoforms\.fpkm_traking/, #same for denovo
                         /transcripts\.gtf/, #same for denovo
                         /isoforms\.fpkm_tracking/]}, #same for denovo
            :quantification =>{rules:[/quantification/]},
            :cuffcompare =>{rules:[/.*(compare).*\.tracking/,
            :tophat => {rules:[/accepted_hits\.bam$/,
            :rtfc => {rules:[/_L\d{3,3}_R1_\d{3,3}\.trimmed\.fastq\.gz/]}, #reads_trimmed_forward_chunks
            :rtrc => {rules:[/_L\d{3,3}_R2_\d{3,3}\.trimmed\.fastq\.gz/]}, #reads_trimmed_reverse_chunks
            :rtf => {rules:[/_R1\.trimmed\.fastq\.gz/]}, #reads_trimmed_forward
            :rtr => {rules:[/_R2\.trimmed\.fastq\.gz/]}, #reads_trimmed_reverse
            :rtufc => {rules:[/_L\d{3,3}_R1_\d{3,3}\.unpaired\.fastq\.gz/]}, #reads_trimemd_unpaired_forward_chunks
            :rturc => {rules:[/_L\d{3,3}_R2_\d{3,3}\.unpaired\.fastq\.gz/]}, #reads_trimmed_unpaired_reverse_chunks
            :rtuf => {rules:[/_R1\.unpaired\.fastq\.gz/]}, #reads_trimmed_unpaired_forward
            :rtur => {rules:[/_R2\.unpaired\.fastq\.gz/]}, #reads_trimmed_unpaired_reverse
            :rfc => {rules:[/_L\d{3,3}_R1_\d{3,3}\.fastq\.gz/]}, #reads_forward_chunks
            # elsif file=~/trimmed/ && file=~/_L\d+_R._\d+\./
            #   :trimmed_splitted
            # elsif file=~/trimmed/ 
            #   :trimmed
            :rrc => {rules:[/_L\d{3,3}_R2_\d{3,3}\.fastq\.gz/]}, #reads_reverse_chunks                
            :rf => {rules:[/_R1\.fastq\.gz/]}, #reads_forward  
            :rr => {rules:[/_R2\.fastq\.gz/]}, #reads_reverse                
            :logs => {rules:[/logs/]},
            :denovo => {rules:[/denovo/]},
            :rawdata => {rules:[/raw_data/,/rawdata/]},
            :mapquant => {rules:[/MAPQUANT/]},
            :mapquant_projects => {rules:[/MAPQUANT_Projects/]},
            :project => {rules:[/Project_/],{|file_name| $1.to_sym if file_name=~/Project_(.*?)\//}},
            :sample => {rules:[/Sample_/],{|file_name| $1.to_sym if file_name=~/Sample_(.*?)\//}},
            :sample_sheet => {rules:[/SampleSheet.csv/]}

Like for :project and :sample the user can also associate a Proc to have a more complex tagging strategy.

Converting data to RDF

After quantification with Cufflinks data can be converted into RDF and this is a simple example of it biongs convert:cuff:quant_to_ttl transcripts.gtf --output=transcripts.ttl --sample=SQ_0080 --project=Naive_T0 --run=110908_H125_0119_AB01W2ABXX

in case the user do not want to specify sample, project, run and the path of the file reflects this structure: 110908_H125_0119_AB01W2ABXX_DATA/Project_Naive_T0/Sample_SQ_0080

the software can extract those information automatically, just selecting the option --get_info_from_path



  1. Clone Main Repository
    git clone This command will create a local copy of the main repository

  2. Install Bioinformatics Tools into the repository directory
    rake devenv:bio_tools


Bio-Ngs comes with a build-in wrapper to map binary software directly in BioRuby as objects. From this wrapper object is possible to create Thor task as well, with a lot of sugar.

Wrapping a binary

We want wrap TopHat the famous tool for NGS analyses.

  1. The first step is to include the Wrapping module

  2. set the name of the binary to call. Note: if you avid to set the program name it would not be possible to create a thor task and/or run the program

  3. add the options that the binary accepts, usually if preferred to declare all the options, discover them typing your_program_name -h

    module Bio module Ngs
    class Tophat include Bio::Command::Wrapper

       set_program Bio::Ngs::Utils.binary("tophat/tophat")
       add_option "output-dir",:type => :string, :aliases => '-o'
       add_option "min-anchor", :type => :numeric, :aliases => '-a'
       add_option "splice-mismatches", :type => :numeric, :aliases => '-m'
       #all other options that you want to expose with the wrapping
     end #Tophat

    end #Ngs end #Bio

is possible to use specify in the class
use_aliases if you want to give a priority to short notation or if your program has only the short notation but you want to extend the task with the long one as well. We defined a new property for add_option called :collapse => true is used only with use_aliases and it collapse the passed parameter to the short notation. An example coming from fastx.rb wrapper, note last row:

module Bio
  module Ngs    
    module Fastx
      class Trim
        include Bio::Command::Wrapper
        set_program Bio::Ngs::Utils.binary("fastq_quality_trimmer")
        add_option :min_size, :type=>:numeric, :default=>20, :aliases => "-l", :desc=>"Minimum length - sequences shorter than this (after trimming)
        will be discarded. Default = 0 = no minimum length."
        add_option :min_quality, :type=>:numeric, :default=>10, :aliases => "-t", :desc=>"Quality threshold - nucleotides with lower 
        quality will be trimmed (from the end of the sequence)."
        add_option :output, :type=>:string, :aliases => "-o", :desc => "FASTQ output file.", :collapse=>true
        add_option :input, :type=>:string, :aliases => "-i", :desc => "FASTQ input file.", :collapse=>true
        add_option :gzip, :type => :boolean, :aliases => "-z", :desc => "Compress output with GZIP."
        add_option :verbose, :type => :boolean, :aliases => "-v", :desc => "[-v]         = Verbose - report number of sequences.
        If [-o] is specified,  report will be printed to STDOUT.
        If [-o] is not specified (and output goes to STDOUT),
        report will be printed to STDERR."
        add_option :quality_type,  :type=>:numeric, :default => 33, :aliases => "-Q", :desc=>"Quality of fastq file"

fastq_quality_trimmer accepts only short notation options and we need to pass an input file, but for some reason popen used internally doesn't work properly with the standard behavior so using :collapse=>true the application will be called:

fastq_quality_trimmer -t 20 -t 10 -Q 33 -iinput_file_name.fastq -ooutput_file_name.fastq_trim

running the program by hand form the command line using a space as separator after -i and -o works as expected. :collapse is a work around for this problem.

In case you program work like git which has a main program and the sub_programs for each feature you can use specify the sub program name with

set_sub_program "sub_name"

The wrapper will run the command composing:

set_program set_sub_program options arguments

A practical example of this behavior is samtools which has multiple sub programs view, merge, sort, .... SamTools is a particular case because in biongs we are using bio-samtools a binding with FFI and the wrapper because the merge function was too complicated for the binding or at least we do not spent enough time on it, so we make the wrapping for this functionality.

This step is very similar to define a Thor task, add_option is grabbed/inspired from Thor. Then you can user this binary also from a bioruby script just calling:

tophat =
tophat.params = {"mate-inner-dist"=>dist, "output-dir"=>outputdir, "num-threads"=>1, "solexa1.3-quals"=>true}

very important: you can pass parameters that have a name which has been previously declared in the Tophat's class. if you want to pass not declared parameters/options please use arguments. :arguments=>[index, "#{fastqs}" ]

Define the Task

With our new wrapper, let's define a Thor task on the fly

class MyTasks < Thor
  desc "tophat DIST INDEX OUTPUTDIR FASTQS", "run tophat as from command line, default 6 processors", :tophat) do |wrapper, task, dist, index, outputdir, fastqs|
    wrapper.params = {"mate-inner-dist"=>dist, "output-dir"=>outputdir, "num-threads"=>1, "solexa1.3-quals"=>true} :arguments=>[index, "#{fastqs}" ], :separator=>"="
    #you tasks here

Now is you list the tasks with thor -T you will see the new task.

You can create a new wrapper and configure it and run it from inside a Thor's tasks, like in biongs quality:boxplot

desc "boxplot FASTQ_QUALITY_STATS", "plot reads quality as boxplot"
method_option :title, :type=>:string, :aliases =>"-t", :desc  => "Title (usually the solexa file name) - will be plotted on the graph."
method_option :output, :type=>:string, :aliases =>"-o", :desc => "Output file name. default is input file_name with .txt."
def boxplot(fastq_quality_stats)
  output_file = options.output || "#{fastq_quality_stats}.png"
  boxplot =
  boxplot.params={input:fastq_quality_stats, output:output_file}

Override the run command when the binary dosen't behave normally

module Bio
  module Ngs    
    module Samtools
      class View
        include Bio::Command::Wrapper
        set_program Bio::Ngs::Utils.binary("samtools")
        add_option "output", :type => :string, :aliases => '-o'

        alias :original_run :run
        def run(opts = {:options=>{}, :arguments=>[], :output_file=>nil, :separator=>"="})
      end #View
    end #Samtools
  end #Ngs
end #Bio

Disable binary check at load time

When a wrapping is defined BioNGS verify that the program is installed on the local system, if it is not it thrown an warning message and the task is disabled by default. This check is made for each binary wrapped, so it could takes long the first time you load BioNGS. To skip this check the user can define an environment variable assigning one of these terms "true yes ok 1" to BIONGS_SKIP_CHECK_BINARIES


you can also add this setting to the .bashrc or .profile in the user home directory.

Warning messages

Prior to version 0.7.0 was not possible to skip warning messages and biongs was a bit slow in staring. From 0.7.0 warnin messages are disable by default. To reenable warning messages is enough

export BIONGS_VERBOS=true

this setting to the .bashrc or .profile in the user home directory.


Iterators for output files

Example CuffDiff. In this class is possible to define an iterator for a specific set of output files: genes, isoforms, tss_groups, cds. To activate the iterator is just a matter of call a class method in the class definition

class Bio::Ngs::Cufflinks::Diff
  #... all the previous definitions
  #define iterators
  add_iterator_for :genes
  add_iterator_for :isoforms
  add_iterator_for :cds
  add_iterator_for :tss_groups

This is an example of CuffDiff, parsing genes.fpkm_tracking file:

Bio::Ngs::Cufflinks::Diff.foreach_gene_tracked("path_to_cuffdiff_output_directory") do |gene_fpkm_track|
  expression_profile = (1..7).map do |sample_idx|
  #do your stuff accessing this tabular file with gene_fpkm_track["name of the field"]

In this case internally CSV library has been used to parse in an easy way the file, there is a lack of performances with huge files, gaining in flexibility.

Loading or Not tasks from outside

If in your external library or binary you define LoadBaseTasks in Bio::Ngs (as a costant) requiring 'bio-ngs' bio-ngs's tasks will not load but only the libraries.

module Bio
  module Ngs
    LoadBaseTasks = true

This is something useful if you want to develop a separate binary which uses bio-ngs libraries. Is not yet possible to define a list of desired tasks to load.


  • It's possible to add more sugar and we are working hard on it
  • aliases are not well supported at this time. ToDo


  • Write Tutorial for Wrapper & Pipes
  • Write Tutorial for handling Illumina/Fastq.gz with BioNGS Bio::Ngs::Illumina::FastqGz
  • Report the version of every software installed/used from bio-ngs
  • Develop fastq quality reports with RibuVis ?
  • Write documentation
  • DONE: Wrapper: better support for aliases and Wrapper#params
  • Convert: re factor code to use ::Daemons
  • DONE:misk_tasks? Extract genes/regions of interest from a bam file and create a smaller bam
  • BRANCH:misk_tasks Explore possibility to user DelayedJobs
  • biongs ann:ensembl:gtf:features:categorize GTF GTF categorize also by chromosome not only by BioType
  • configuration file input,output, experimental design
  • DONE: include fastx toolkit, download and compile
  • ANSWER: how to put in background tasks that can be run in parallel? Use Parallel (see code for quality:illumina_project_stats)
  • is it possible to establish a relation between input data and output data ? like fastq task_selected output/s
  • add description for developers on howto include news external tool with versions.yaml


  • 2011.05-26: Bump to version 0.2.0 Complete support for installing fastx and possibly other downloadable tool, inside the gem
  • 2011-05-25: Bump to version 0.1.0 Update Cufflinks toolkit 1.0.2. Added initial support to fastx tool kit (binaries not included)
  • 2011-04-08: Tasks for filtering Ensembl annotation and create classifications. (misk_tasks branch)

Contributing to bio-ngs

Please do not hesitate to contact us:

Raoul J.P. Bonnal,, r -at- bioruby -dot- org Francesco Strozzi,

Post issues on

  • Check out the latest master to make sure the feature hasn't been implemented or the bug hasn't been fixed yet
  • Check out the issue tracker to make sure someone already hasn't requested it and/or contributed it
  • Fork the project
  • Start a feature/bugfix branch
  • Commit and push until you are happy with your contribution
  • Pull request to BioNGS
  • Make sure to add tests for it. This is important so I don't break it in a future version unintentionally.
  • Please try not to mess with the Rakefile, version, or history. If you want to have your own version, or is otherwise necessary, that is fine, but please isolate to its own commit so I can cherry-pick around it.


Copyright (c) 2011 Francesco Strozzi and Raoul J.P. Bonnal. See LICENSE.txt for further details.


This plugins is intended to wrap the common software used for Next Generation Sequencing data







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