Mercurial > repos > pieterlukasse > primo_multiomics
view term_mapper.xml @ 7:ce9228263148
renamed to TermMapper
author | pieter.lukasse@wur.nl |
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date | Mon, 23 Mar 2015 21:02:01 +0100 |
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children | 97e10319d86f |
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<tool name="TermMapperTool" id="TermMapperTool1" version="0.0.2"> <description>use cross-reference lookup tables to annotate results</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 --> <!-- similar to "join two datasets" tool http://galaxy.wur.nl/galaxy_production/root?tool_id=join1 but this one is probably having more powerful features like supporting multiple ';' codes in key fields and the feature in termColName(s) supporting direct hierarchy like annotation --> <command interpreter="java -jar "> TermMapperTool.jar -inputFileName $inputFileName -inputIdColumnName "$inputIdColumnName" #if $inputIdCol.inputIdHasPrefix == True -inputIdPrefix "$inputIdCol.inputIdPrefix" #end if -mappingFileName $mappingFileName -mappingFileIdColName "$mappingFileIdColName" #if $mappingIdCol.mappingIdHasPrefix == True -mappingIdPrefix "$mappingIdCol.mappingIdPrefix" #end if -mappingFileTermColName "$mappingFileTermColName" -outputFileName $outputFileName #if $genObservations.genObservationsFile == True -outputObservationsFileName $outputObservationsFileName -quantifColumn "$genObservations.quantifColumn" #end if -mappedTermsColName $mappedTermsColName </command> <inputs> <param name="inputFileName" type="data" format="tabular,csv" label="Target file (TSV/CSV)" /> <param name="inputIdColumnName" type="text" size="50" value="" label="ID column name" help="Name of the column containing the identification codes (in the given input file)"/> <conditional name="inputIdCol"> <param name="inputIdHasPrefix" type="boolean" truevalue="Yes" falsevalue="No" checked="false" label="ID values have a prefix"/> <when value="Yes"> <param name="inputIdPrefix" type="text" size="50" value="" label="Prefix in ID column" help="Fill in if any prefix is found in the ID column values (e.g. in some files the value is preceded by a fixed value like for example 'lipidmaps:LMFA00000007' instead of just 'LMFA00000007' - in this example one would fill in 'lipidmaps:' as prefix)"/> </when> <when value="No"> </when> </conditional> <!-- =================== cross-reference part ============== --> <param name="mappingFileName" type="data" format="tabular,csv" label="Lookup table (TSV/CSV)" help="Simple mapping file between the coding scheme used to another scheme"/> <param name="mappingFileIdColName" type="text" size="50" value="" label="ID column name (in lookup table)" help="Name of the ID column for the lookup"/> <conditional name="mappingIdCol"> <param name="mappingIdHasPrefix" type="boolean" truevalue="Yes" falsevalue="No" checked="false" label="ID values have a prefix"/> <when value="Yes"> <param name="mappingIdPrefix" type="text" size="50" value="" label="Prefix in ID column" help="Fill in if any prefix is found in the ID column values (e.g. in some files the value is preceded by a fixed value like for example 'lipidmaps:LMFA00000007' instead of just 'LMFA00000007' - in this example one would fill in 'lipidmaps:' as prefix)"/> </when> <when value="No"> </when> </conditional> <param name="mappingFileTermColName" type="text" size="50" value="" label="Term column name(s) or number(s)" help="Name(s) or number(s) of the column(s) containing the term(s) in the lookup table (and which will be transfered to the target file based on ID match in 'ID column name'). For using multiple term column names, set the names separated by comma (,). If multiple columns are specified, the algorithm will look for an annotation in the first one, if none found it will try the second one, and so forth. "/> <param name="mappedTermsColName" type="text" size="50" value="Mapped terms" label="Name to give to the new column:" help="Name to give to the new column that will be added to the target file. This new column is the one that will contain the respectively mapped terms."/> <conditional name="genObservations"> <param name="genObservationsFile" type="boolean" truevalue="Yes" falsevalue="No" checked="false" label="Generate also observations file"/> <when value="Yes"> <param name="quantifColumn" type="text" size="50" value="" label="(Optional) Values column name" help="Name of the column containing the quantification values (in the given input file)"/> </when> <when value="No"> </when> </conditional> </inputs> <outputs> #if isinstance( $inputFileName.datatype, $__app__.datatypes_registry.get_datatype_by_extension('tabular').__class__): <data name="outputFileName" format="tabular" label="${tool.name} on ${on_string}: annotated file " ></data> #else: <data name="outputFileName" format="csv" label="${tool.name} on ${on_string}: annotated file " ></data> #end if <data name="outputObservationsFileName" format="tabular" label="${tool.name} on ${on_string}: term observations file (TSV)"> <!-- If the expression is false, the file is not created --> <filter>( genObservations.genObservationsFile == True )</filter> </data> </outputs> <tests> <!-- find out how to use --> <test> </test> </tests> <help> .. class:: infomark This tool is responsible for annotating the given target file with the terms given in a lookup table. This lookup table maps the items found in the target file (e.g. protein identifications coded in common protein coding formats such as UniProt ) to their respective terms (e.g. GO terms). It enables users to use the cross-reference information now available from different repositories (like uniprot and KEGG - see for example http://www.uniprot.org/taxonomy/ or http://www.genome.jp/linkdb/ ) to map their data to other useful coding schemes or to ontologies and functional annotations. .. class:: infomark **NB:** Currently the tool will do "smart parsing" of hierarchy based fields in the target file ID column. This means that if the colum contains a ".", the trailing part of the ID after the "." is ignored if the full ID does not get a match in the lookup table while the part before the "." does. .. class:: infomark Examples of usage: annotate protein identifications with Gene Ontology[GO] terms annotate metabolite CAS identifications with chebi codes add KEGG gene codes to a file containing UNIPROT codes add KEGG compound codes to a file containing chebi codes etc As an example for transcripts and proteins, users can check http://www.uniprot.org/taxonomy/ to see if their organism has been mapped to GO terms by Uniprot. For example the link http://www.uniprot.org/uniprot/?query=taxonomy:2850 will show the Uniprot repository and cross-references for the taxonomy 2850. When the organism being studied is not available, then other strategies could be tried (like Blast2GO for example). Despite the specific examples above, this class is generic and can be used to map any values to new terms according to a given lookup table. .. class:: infomark *Omics cross-reference resources on the web:* LinkDB: http://www.genome.jp/linkdb/ *Ready to use metabolomics links:* http://rest.genome.jp/link/compound/chebi http://rest.genome.jp/link/compound/lipidmaps http://rest.genome.jp/link/compound/lipidbank http://rest.genome.jp/link/compound/hmdb *Ready to use proteomics links:* http://rest.genome.jp/link/uniprot/pti (Phaeodactylum Tri.) http://rest.genome.jp/link/uniprot/hsa (Homo Sapiens) (for organism code list see: ) Uniprot to GO http://www.uniprot.org/taxonomy/ ----- **Output** This method will read in the given input file and for each line it will add a new column containing the terms found for the ID in that line. So the output file is the same as the input file + extra terms column (separated by ; ). ----- **Link to ontology viewer** A second summarized "terms observations" file can also be generated. In case the terms are ontology terms, this file can be used for visualizing the results in the ontology viewer "OntologyAndObservationsViewer". </help> </tool>