view protein_inference.xml @ 2:cf0d72c7b482 draft

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author galaxyp
date Fri, 10 May 2013 17:31:05 -0400
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<tool id="openms_protein_inference" version="0.1.0" name="Protein Inference">
  <description>
    Computes a protein identification based on the number of identified peptides.
  </description>
  <macros>
    <import>macros.xml</import>
  </macros>
  <expand macro="stdio" />
  <expand macro="requires" />
  <command interpreter="python">
    openms_wrapper.py --executable 'PeptideIndexer' --config $config
  </command>
  <configfiles>
    <configfile name="config">[simple_options]
in=$input1
out=$output
min_peptides_per_protein=${min_peptides_per_protein}
treat_charge_variants_separately=${treat_charge_variants_separately}
treat_modification_variants_separately=${treat_modification_variants_separately}
</configfile>
  </configfiles>
  <inputs>
    <param name="input1" label="Identification Input" type="data" format="idxml" />
    <param name="min_peptides_per_protein" type="integer" value="2" label="Minimum Number of Peptides per Protein Identification" />    
    <param name="treat_charge_variants_separately" label="Treat Charge Variants Separately" type="boolean" truevalue="true" falsevalue="false" checked="false" help="If this flag is set, different charge variants of the same peptide sequence count as inidividual evidences." />
    <param name="treat_modification_variants_separately" label="Treat Modification Variants Separately" type="boolean" truevalue="true" falsevalue="false" checked="false" help="If this flag is set, different modification variants of the same peptide sequence count as individual evidences." />
  </inputs>
  <outputs>
    <data format="idxml" name="output" />
  </outputs>
  <help>
**What it does**

This tool counts the peptide sequences that match a protein accession. From this count for all protein hits in the respective id run, only those proteins are accepted that have at least a given number of peptides sequences identified. The peptide identifications should be prefiltered with respect to false discovery rate and the score in general to remove bad identifications.

**Citation**

For the underlying tool, please cite ``Marc Sturm, Andreas Bertsch, Clemens Gröpl, Andreas Hildebrandt, Rene Hussong, Eva Lange, Nico Pfeifer, Ole Schulz-Trieglaff, Alexandra Zerck, Knut Reinert, and Oliver Kohlbacher, 2008. OpenMS – an Open-Source Software Framework for Mass Spectrometry. BMC Bioinformatics 9: 163. doi:10.1186/1471-2105-9-163.``

If you use this tool in Galaxy, please cite Chilton J, et al. https://bitbucket.org/galaxyp/galaxyp-toolshed-openms
  </help>
</tool>