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planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/meta_proteome_analyzer commit 69cfb20d049ddeccef197865cc07eac5363ea8ea
author | galaxyp |
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date | Sat, 04 Mar 2017 07:00:01 -0500 |
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children | 7fdfbf042ec6 |
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<tool id="meta_proteome_analyzer" name="MetaProteomeAnalyzer" version="1.4.1"> <description> functional and taxonomic characterization of proteins </description> <requirements> <requirement type="package" version="1.4.1">mpa-portable</requirement> </requirements> <command> <![CDATA[ #set $temp_stderr = "mpa_stderr" cwd=`pwd` && mkdir -p output_dir && ## copy mpa conf dir to working dir jar_dir=`mpa-portable -get_jar_dir` && cp -R \$jar_dir/conf . && ## echo the search engines to run #set $search_engines = str($search_engines_options.engines).split(',') echo "$search_engines_options.engines" && echo "DB: ${input_database.display_name} sequences: ${input_database.metadata.sequences}" && #for $mgf in $peak_lists: #set $input_name = $mgf.display_name.split('/')[-1].replace(".mgf", "") + ".mgf" ln -s -f '${mgf}' '${input_name}' && #set $encoded_id = $__app__.security.encode_id($mgf.id) echo "Spectrums:${mgf.display_name}(API:${encoded_id}) " && #end for cp "${input_database}" input_database.fasta && ###################### ## MPA ## ###################### (mpa-portable de.mpa.cli.CmdLineInterface -Djava.awt.headless=true -Xmx2048m -spectrum_files \$cwd -database input_database.fasta -missed_cleav $missed_cleavages -prec_tol ${precursor_options.prec_tol}${precursor_options.prec_tol_units} -frag_tol ${precursor_options.frag_tol}Da -xtandem #if 'X!Tandem' in $search_engines then 1 else 0# -comet #if 'Comet' in $search_engines then 1 else 0# -msgf #if 'MSGF' in $search_engines then 1 else 0# -output_folder output_dir -threads "\${GALAXY_SLOTS:-12}" 2> $temp_stderr) && mv ./output_dir/*_metaproteins.csv metaproteins.csv && mv ./output_dir/*_metaprotein_taxa.csv metaprotein_taxa.csv && mv ./output_dir/*_peptides.csv peptides.csv && mv ./output_dir/*_proteins.csv proteins.csv && mv ./output_dir/*_psms.csv psms.csv && mv ./output_dir/*_spectrum_ids.csv spectrum_ids.csv && exit_code_for_galaxy=\$? && cat $temp_stderr 2>&1 && (exit \$exit_code_for_galaxy) ]]> </command> <inputs> <param format="fasta" name="input_database" type="data" label="Protein Database" help="Select FASTA database from history"/> <param name="peak_lists" format="mgf" type="data" multiple="true" label="Input Peak Lists (mgf)" help="Select appropriate MGF dataset(s) from history" /> <param name="missed_cleavages" type="integer" value="2" label="Maximum Missed Cleavages" help="Allow peptides to contain up to this many missed enzyme cleavage sites."/> <section name="precursor_options" expanded="false" title="Precursor Options"> <param name="prec_tol_units" type="select" label="Precursor Ion Tolerance Units" help="Select based on instrument used, as different machines provide different quality of spectra. ppm is a standard for most precursor ions"> <option value="ppm">Parts per million (ppm)</option> <option value="Da">Daltons</option> </param> <param name="prec_tol" type="float" value="10" label="Percursor Ion Tolerance" help="Provide error value for precursor ion, based on instrument used. 10 ppm recommended for Orbitrap instrument"/> <param name="frag_tol" type="float" value="0.5" label="Fragment Tolerance (Daltons)" help="Provide error value for fragment ions, based on instrument used"/> </section> <!-- Search Engine Selection --> <section name="search_engines_options" expanded="false" title="Search Engine Options"> <param name="engines" type="select" display="checkboxes" multiple="True" label="DB-Search Engines"> <help>Comet and Tide shouldn't both be selected since they use a similar algoritm.</help> <option value="X!Tandem" selected="True">X!Tandem</option> <option value="MSGF">MS-GF+</option> <option value="Comet">Comet</option> </param> </section> <!-- -generate_metaproteins Turn meta-protein generation (aka. protein grouping) on or off (1: on, 0: off, default is '1'). -peptide_rule The peptide rule chosen for meta-protein generation (-1: off, 0: share-one-peptide, 1: shared-peptide-subset, default is '0'). -cluster_rule The sequence cluster rule chosen for meta-protein generation (-1: off, 0: UniRef100, 1: UniRef90, 2: UniRef50, default is '-1'). -taxonomy_rule The taxonomy rule chosen for meta-protein generation (-1: off, 0: on superkingdom or lower, 1: on kingdom or lower, 2: on phylum or lower, 3: on class or lower, 4: on order or lower, 5: on family or lower, 6: on genus or lower, 7: on species or lower, 8: on subspecies, default is '-1'). -iterative_search Turn iterative (aka. two-step) searching on or off (1: on, 0: off, default is '0'). -fdr_threshold The applied FDR threshold for filtering the results (default is 0.05 == 5% FDR). --> </inputs> <outputs> <data format="tabular" name="output_proteins" from_work_dir="proteins.csv" label="${tool.name} on ${on_string}: proteins"> <actions> <action name="comment_lines" type="metadata" default="1" /> <action name="column_names" type="metadata" default="Protein_No,Protein_Accession,Protein_Description,Protein_Taxonomy,Sequence_Coverage,Peptide_Count,NSAF,emPAI,Spectral_Count,Isoelectric_Point,Molecular_Weight,Protein_Sequence,Peptides" /> </actions> </data> <data format="tabular" name="output_peptides" from_work_dir="peptides.csv" label="${tool.name} on ${on_string}: peptides"> <actions> <action name="comment_lines" type="metadata" default="1" /> <action name="column_names" type="metadata" default="Peptide_Num,Protein_Accessions,Peptide_Sequence,Protein_Count,Spectral_Count,Taxonomic_Group,Taxonomic_Rank,NCBI_Taxonomy_ID" /> </actions> </data> <data format="tabular" name="output_PSMs" from_work_dir="psms.csv" label="${tool.name} on ${on_string}: PSMs"> <actions> <action name="comment_lines" type="metadata" default="1" /> <action name="column_names" type="metadata" default="PSM_Num,Protein_Accessions,Peptide_Sequence,Spectrum_Title,Charge,Search_Engine,q-value,Score" /> </actions> </data> <data format="tabular" name="output_spectrum_ids" from_work_dir="spectrum_ids.csv" label="${tool.name} on ${on_string}: spectrum_ids"> <actions> <action name="comment_lines" type="metadata" default="1" /> <action name="column_names" type="metadata" default="Spectrum_Number,Spectrum_ID,Spectrum_Title,Peptides,Protein_Accessions" /> </actions> </data> <data format="tabular" name="output_metaproteins" from_work_dir="metaproteins.csv" label="${tool.name} on ${on_string}: metaproteins"> <actions> <action name="comment_lines" type="metadata" default="1" /> <action name="column_names" type="metadata" default="Meta-Protein_Num,Meta-Protein_Accession,Meta-Protein_Description,Meta-Protein_Taxonomy,Meta-Protein_UniRef100,Meta-Protein_UniRef90,Meta-Protein_UniRef50,Meta-Protein_KO,Meta-Protein_EC,Peptide_Count,Spectral_Count,Proteins,Peptides" /> </actions> </data> <data format="tabular" name="output_metaprotein_taxa" from_work_dir="metaprotein_taxa.csv" label="${tool.name} on ${on_string}: metaprotein_taxa"> <actions> <action name="comment_lines" type="metadata" default="1" /> <action name="column_names" type="metadata" default="Unclassified,Superkingdom,Kingdom,Phylum,Class,Order,Family,Genus,Species,Subspecies,Num_Peptides,Spectral_Count" /> </actions> </data> </outputs> <tests> <test> <param name="peak_lists" value="Test416Ebendorf.mgf" ftype="mgf"/> <param name="input_database" value="searchdb.fa" ftype="fasta"/> <param name="missed_cleavages" value="2"/> <param name="prec_tol" value="ppm"/> <param name="prec_tol" value="10"/> <param name="frag_tol" value="0.5"/> <param name="engines" value="X!Tandem,MSGF,Comet"/> <output name="output_PSMs"> <assert_contents> <has_text text="A2SPK1" /> </assert_contents> </output> </test> </tests> <help> **What it does** ======= MetaProteomeAnalyzer (MPA) performs identification of proteins and in-depth analysis of metaproteomics (and also proteomics) data. The MPA software currently supports the database search engines Comet, MS-GF+ and X!Tandem taking MGF spectrum files as input data. User-provided FASTA databases (preferably downloaded from UniProtKB) are formatted automatically. https://github.com/compomics/meta-proteome-analyzer ---- Outputs ======= MPA generates 6 tabular outputs: * psms * peptides * proteins * spectrum_ids * metaproteins * metaprotein_taxa ------ </help> <citations> <citation type="doi">10.1021/pr501246w</citation> </citations> </tool>