Mercurial > repos > pieterlukasse > prims_proteomics
diff napq.xml @ 0:d50f079096ee
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author | pieter.lukasse@wur.nl |
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date | Wed, 08 Jan 2014 11:39:16 +0100 |
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children | 73c7c6589202 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/napq.xml Wed Jan 08 11:39:16 2014 +0100 @@ -0,0 +1,93 @@ +<tool name="NapQ" id="napq" version="0.0.1"> + <description>'no alignment'(alignment-free) peptide quantification</description> + <!-- + For remote debugging start you listener on port 8000 and use the following as command interpreter: + java -jar -Xdebug -Xrunjdwp:transport=dt_socket,address=D0100564.wurnet.nl:8000 + ////////////////////////// + --> + <command interpreter="java -jar "> + NapQ.jar + -identificationsConfigFile $identificationsConfigFile + -namingConventionCodesForSamples $namingConventionCodesForSamples + #if $is2D_LC_MS.fractions == True + -namingConventionCodesForFractions $is2D_LC_MS.namingConventionCodesForFractions + #end if + -outputApml $outputApml + -outputTsv $outputTsv + -outReport $htmlReportFile + -outReportPicturesPath $htmlReportFile.files_path + </command> + + <inputs> + + <repeat name="identificationFileList" title="Peptide identification files" help="Full set of MS/MS peptide identification files, including peptides that could not be quantified."> + <param name="identificationsFile" type="data" format="apml,mzidentml,prims.fileset.zip" label="Identifications file (APML or MZIDENTML or MZIDENTML fileSet)" /> + <param name="spectraFile" type="data" format="mzidentml,prims.fileset.zip" optional="true" label="(Optional) Spectra fileSet (mzml file or fileSet)" + help="Select this in case your Identifications file is MZIDENTML or MZIDENTML fileSet" /> + </repeat> + + <param name="namingConventionCodesForSamples" type="text" size="100" value="" + label="Part of run/file name that identifies the sample" + help="Add the CSV list of codes that occur in the file names + and that stand for a sample code. E.g. '_S1,_S2,_S3,etc.' "/> <!-- could do regular expressions as well but this would be hard for biologists, e.g. _F\d\b --> + + + <conditional name="is2D_LC_MS"> + <param name="fractions" type="boolean" truevalue="Yes" falsevalue="No" checked="false" + label="Data is from 2D LC-MS" + help="Data acquisition was done in multiple fractions."/> + <when value="Yes"> + <param name="namingConventionCodesForFractions" type="text" size="100" value="" + label="Part of run/file name that identifies the 2D LC-MS fraction" + help="Add the CSV list of codes that occur in the file names + and that stand for a fraction code. E.g. '_F1,_F2,_F3,etc.' Use this to avoid + that each (fraction) file is seen as a separate run."/> <!-- could do regular expressions as well but this would be hard for biologists, e.g. _F\d\b --> + </when> + </conditional> + + </inputs> + <configfiles> + <configfile name="identificationsConfigFile">## start comment + ## iterate over the selected files and store their names in the config file + #for $i, $s in enumerate( $identificationFileList ) + ${s.identificationsFile}|${s.spectraFile} + ## also print out the datatype in the next line, based on previously configured datatype + #if isinstance( $s.identificationsFile.datatype, $__app__.datatypes_registry.get_datatype_by_extension('apml').__class__): + apml + #else: + mzid + #end if + #end for + ## end comment</configfile> + </configfiles> + <outputs> + <data name="outputApml" format="apml" label="${tool.name} on ${on_string}: peptide quantifications (APML)"/> + <data name="outputTsv" format="tabular" label="${tool.name} on ${on_string}: peptide quantifications (TSV)"/> + <!-- in tsv we can have cols like: pep, avg_m/z, avg rt, m/z window, rt window, i_s1, i_s2, ...--> + <data name="htmlReportFile" format="html" label="${tool.name} on ${on_string} - HTML report"/> + <!-- here we show the samples extracted and the files used to 'build up' each sample --> + </outputs> + <tests> + </tests> + <help> + +.. class:: infomark + +This tool takes in multiple peptide identification result files that have peptide identifications +coupled to some quantification (e.g. precursor intensity information or for example data coming +from MS^E acquisition where peptide identification and quantification are done in the same run and reported together). +Then, based on the given experiment design parameters (i.e. how the result files related back to +replicate runs and samples), it produces a new file in which the peptides are reported with +their calculated quantifications at the sample level. + +The figure below explains this: + +.. image:: $PATH_TO_IMAGES/napq_overview.png + + + + + + + </help> +</tool>