Mercurial > repos > iuc > fastqc
view rgFastQC.xml @ 1:39b1c10532a4 draft
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author | iuc |
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date | Sat, 18 Jan 2014 22:33:24 -0500 |
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<tool name="FastQC: Comprehensive QC" id="fastqc" version="0.53"> <description>reporting for short read sequence</description> <command interpreter="python"> rgFastQC.py -i "$input_file" -d "$html_file.files_path" -o "$html_file" -n "$out_prefix" -f "$input_file.ext" -j "$input_file.name" #if $contaminants.dataset and str($contaminants) > '' -c "$contaminants" #end if -e fastqc </command> <requirements> <requirement type="package" version="0.10.1">fastqc_dist_0_10_1</requirement> </requirements> <inputs> <param format="fastqsanger,fastq,bam,sam" name="input_file" type="data" label="Short read data from your current history" /> <param name="out_prefix" value="FastQC" type="text" label="Title for the output file - to remind you what the job was for" size="80" help="Letters and numbers only please - other characters will be removed"> <sanitizer invalid_char=""> <valid initial="string.letters,string.digits"/> </sanitizer> </param> <param name="contaminants" type="data" format="tabular" optional="true" label="Contaminant list" help="tab delimited file with 2 columns: name and sequence. For example: Illumina Small RNA RT Primer CAAGCAGAAGACGGCATACGA"/> </inputs> <outputs> <data format="html" name="html_file" label="${out_prefix}_${input_file.name}.html" /> </outputs> <tests> <test> <param name="input_file" value="1000gsample.fastq" /> <param name="out_prefix" value="fastqc_out" /> <param name="contaminants" value="fastqc_contaminants.txt" ftype="tabular" /> <output name="html_file" file="fastqc_report.html" ftype="html" lines_diff="100"/> </test> </tests> <help> .. class:: infomark **Purpose** Quote from FastQC_ 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 FastQC_ is the best place to look for documentation - it's very good. Some features of the Galaxy wrapper you are using are described below. ----- .. class:: infomark **This Galaxy Tool** You are using FastQC_ in Galaxy. This is easy because it has been packaged into a Galaxy tool by the Intergalactic Utilities Commission. It exposes the external package FastQC_ which is documented at FastQC_ Kindly acknowledge it as well as this tool if you use it. FastQC incorporates the Picard-tools_ libraries for sam/bam processing. The contaminants file parameter was borrowed from the independently developed fastqcwrapper contributed to the Galaxy Community Tool Shed by Jim Johnson. ----- .. class:: infomark **Inputs and outputs** This wrapper will accept a Galaxy fastq, sam or bam as the input read file to check. It will also take an optional file containing a list of contaminants information, in the form of a tab-delimited file with 2 columns, name and sequence. FastQC_ produces a single HTML output file which is slightly adjusted so it looks good in Galaxy that contains all of the results, including the following: - Basic Statistics - Per base sequence quality - Per sequence quality scores - Per base sequence content - Per base GC content - Per sequence GC content - Per base N content - Sequence Length Distribution - Sequence Duplication Levels - Overrepresented sequences - Kmer Content All except Basic Statistics and Overrepresented sequences are plots. .. _FastQC: http://www.bioinformatics.bbsrc.ac.uk/projects/fastqc/ .. _Picard-tools: http://picard.sourceforge.net/index.shtml </help> </tool>