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1 <tool name="FastQC: Comprehensive QC" id="fastqc" version="0.53">
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2 <description>reporting for short read sequence</description>
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3 <command interpreter="python">
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4 rgFastQC.py -i "$input_file" -d "$html_file.files_path" -o "$html_file" -n "$out_prefix" -f "$input_file.ext" -j "$input_file.name"
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5 #if $contaminants.dataset and str($contaminants) > ''
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6 -c "$contaminants"
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7 #end if
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8 -e fastqc
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9 </command>
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10 <requirements>
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11 <requirement type="package" version="0.10.1">fastqc_dist_0_10_1_dependency</requirement>
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12 </requirements>
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13 <inputs>
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14 <param format="fastqsanger,fastq,bam,sam" name="input_file" type="data" label="Short read data from your current history" />
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15 <param name="out_prefix" value="FastQC" type="text" label="Title for the output file - to remind you what the job was for" size="80"
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16 help="Letters and numbers only please - other characters will be removed">
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17 <sanitizer invalid_char="">
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18 <valid initial="string.letters,string.digits"/>
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19 </sanitizer>
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20 </param>
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21 <param name="contaminants" type="data" format="tabular" optional="true" label="Contaminant list"
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22 help="tab delimited file with 2 columns: name and sequence. For example: Illumina Small RNA RT Primer CAAGCAGAAGACGGCATACGA"/>
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23 </inputs>
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24 <outputs>
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25 <data format="html" name="html_file" label="${out_prefix}_${input_file.name}.html" />
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26 </outputs>
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27 <tests>
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28 <test>
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29 <param name="input_file" value="1000gsample.fastq" />
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30 <param name="out_prefix" value="fastqc_out" />
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31 <param name="contaminants" value="fastqc_contaminants.txt" ftype="tabular" />
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32 <output name="html_file" file="fastqc_report.html" ftype="html" lines_diff="100"/>
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33 </test>
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34 </tests>
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35 <help>
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36
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37 .. class:: infomark
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38
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39 **Purpose**
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40
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41 FastQC aims to provide a simple way to do some quality control checks on raw
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42 sequence data coming from high throughput sequencing pipelines.
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43 It provides a modular set of analyses which you can use to give a quick
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44 impression of whether your data has any problems of
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45 which you should be aware before doing any further analysis.
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46
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47 The main functions of FastQC are:
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48
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49 - Import of data from BAM, SAM or FastQ files (any variant)
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50 - Providing a quick overview to tell you in which areas there may be problems
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51 - Summary graphs and tables to quickly assess your data
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52 - Export of results to an HTML based permanent report
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53 - Offline operation to allow automated generation of reports without running the interactive application
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54
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55
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56 -----
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57
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58
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59 .. class:: infomark
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60
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61 **FastQC**
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62
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63 This is a Galaxy wrapper. It merely exposes the external package FastQC_ which is documented at FastQC_
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64 Kindly acknowledge it as well as this tool if you use it.
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65 FastQC incorporates the Picard-tools_ libraries for sam/bam processing.
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66
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67 The contaminants file parameter was borrowed from the independently developed
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68 fastqcwrapper contributed to the Galaxy Community Tool Shed by J. Johnson.
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69
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70 -----
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71
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72 .. class:: infomark
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73
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74 **Inputs and outputs**
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75
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76 FastQC_ is the best place to look for documentation - it's very good.
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77 A summary follows below for those in a tearing hurry.
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78
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79 This wrapper will accept a Galaxy fastq, sam or bam as the input read file to check.
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80 It will also take an optional file containing a list of contaminants information, in the form of
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81 a tab-delimited file with 2 columns, name and sequence.
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82
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83 The tool produces a single HTML output file that contains all of the results, including the following:
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84
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85 - Basic Statistics
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86 - Per base sequence quality
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87 - Per sequence quality scores
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88 - Per base sequence content
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89 - Per base GC content
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90 - Per sequence GC content
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91 - Per base N content
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92 - Sequence Length Distribution
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93 - Sequence Duplication Levels
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94 - Overrepresented sequences
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95 - Kmer Content
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96
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97 All except Basic Statistics and Overrepresented sequences are plots.
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98 .. _FastQC: http://www.bioinformatics.bbsrc.ac.uk/projects/fastqc/
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99 .. _Picard-tools: http://picard.sourceforge.net/index.shtml
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100
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101 </help>
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102 </tool>
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