<tool id="openms_map_aligner_identification" version="0.1.0" name="Map Aligner (Identification)">
  <description>
    Corrects retention time distortions between maps based on common peptide identifications.
  </description>
  <macros>
    <import>macros.xml</import>
  </macros>
  <expand macro="stdio" />
  <expand macro="requires" />
  <command interpreter="python">
    openms_wrapper.py --executable 'MapAlignerIdentification' --config $config
  </command>
  <configfiles>
    <configfile name="config">[simple_options]
#set $inputs_as_str = ",".join(map(str, $type.input))
in=$inputs_as_str
out=@MULTI_OUTPUT($output.extra_files_path,$inputs_as_str)@
#if $generate_transformations
trafo_out=@MULTI_OUTPUT($transformations.extra_files_path,$inputs_as_str)@
#end if
algorithm!peptide_score_threshold=$peptide_score_threshold
algorithm!min_run_occur=$min_run_occur
algorithm!max_rt_shift=$max_rt_shift
algorithm!use_unassigned_peptides=$use_unassigned_peptides
algorithm!use_feature_rt=$use_feature_rt
#set $model_type = $model.model_type
model!type=$model_type
#if $model_type == "interpolated"
model!interpolated!interpolation_type=$model.interpolation_type
#end if
</configfile>
  </configfiles>
  <inputs>
    <conditional name="type">
      <param name="input_type" type="select" label="Input Type">
        <option value="featurexml">Features (FeatureXML)</option>
        <option value="consensusxml">Consensus (ConsensusXML)</option>
        <option value="idxml">Identifications (IdXML)</option>
      </param>
      <when value="featurexml">
        <param format="m:featurexml" name="input" type="data" label="Input Features" />
      </when>
      <when value="consensusxml">
        <param format="m:consensusxml" name="input" type="data" label="Input Consensus Files" />
      </when>
      <when value="idxml">
        <param format="m:idxml" name="input" type="data" label="Input Identifications" />
      </when>
    </conditional>
    <param name="generate_transformations" type="boolean" label="Generate Transformations" />
    <param name="peptide_score_threshold" type="float" value="0" label="Peptide Score Threshold" help="Score threshold for peptide hits to be used in the alignment. Select a value that allows only 'high confidence' matches." />
    <param name="min_run_occur" type="integer" value="2" label="Minimum Runs" help="Minimum number of runs (incl. reference, if any) a peptide must occur in to be used for the alignment. Unless you have very few runs or identifications, increase this value to focus on more informative peptides." />
    <param name="max_rt_shift" type="float" value="0.5" label="Max RT Shift" help="Maximum realistic RT difference for a peptide (median per run vs. reference). Peptides with higher shifts (outliers) are not used to compute the alignment. If 0, no limit (disable filter); if &gt; 1, the final value in seconds; if &lt;= 1, taken as a fraction of the range of the reference RT scale." />
    <param name="use_unassigned_peptides" type="boolean" label="Use Unassigned Peptides" help="Should unassigned peptide identifications be used when computing an alignment of feature maps? If 'false', only peptide IDs assigned to features will be used." truevalue="true" falsevalue="false" checked="true" />
    <param name="use_feature_rt" type="boolean" label="Use Feature RT" help="When aligning feature maps, don't use the retention time of a peptide identification directly; instead, use the retention time of the centroid of the feature (apex of the elution profile) that the peptide was matched to. If different identifications are matched to one feature, only the peptide closest to the centroid in RT is used. Precludes 'use_unassigned_peptides'." truevalue="true" falsevalue="false" checked="false" />
    <expand macro="aligner_model" />
  </inputs>
  <outputs>
    <data format="m:consensusxml" name="output" label="Alignment of ${on_string}">
      <change_format>
        <when input="type.input_type" value="featurexml" format="m:featurexml" />
        <when input="type.input_type" value="idxml" format="m:idxml" />
      </change_format>
    </data>
    <data format="m:trafoxml" name="transformations" label="Aligned Transformations for ${on_string}">
      <filter>generate_transformations</filter>
    </data>
  </outputs>
  <help>
**What it does**

This tool provides an algorithm to align the retention time scales of multiple input files, correcting shifts and distortions between them. Retention time adjustment may be necessary to correct for chromatography differences e.g. before data from multiple LC-MS runs can be combined (feature grouping), or when one run should be annotated with peptide identifications obtained in a different run.

All map alignment tools (MapAligner...) collect retention time data from the input files and - by fitting a model to this data - compute transformations that map all runs to a common retention time scale. 

The map alignment tools differ in how they obtain retention time data for the modeling of transformations, and consequently what types of data they can be applied to. The alignment algorithm implemented here is based on peptide identifications, and thus applicable to files containing peptide IDs (idXML, annotated featureXML/consensusXML). It finds peptide sequences that different input files have in common and uses them as points of correspondence between the inputs.

Note that alignment is based on the sequence including modifications, thus an exact match is required. I.e., a peptide with oxidised methionine will not be matched to its unmodified version. For some applications this behaviour is desired, while for others its not, but you can always remove all modifications from the input files if you want to ignore modifications.

**Citation**

For the underlying tool, please cite ``Weisser et al.: An automated pipeline for high-throughput label-free quantitative proteomics (J. Proteome Res., 2013, PMID: 23391308).``

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