<tool id="openms_feature_finder_centroided" version="0.1.0" name="Feature Finder (Centroided)">
  <description>
    The feature detection application for quantitation (centroided).
  </description>
  <macros>
    <import>macros.xml</import>
  </macros>
  <expand macro="stdio" />
  <expand macro="requires" />
  <command interpreter="python">
    openms_wrapper.py --executable 'FeatureFinderCentroided' --config $config
  </command>
  <configfiles>
    <configfile name="config">[simple_options]
in=$input1
out=$output
algorithm!intensity!bins=$bins
algorithm!mass_trace!mz_tolerance=$trace_mz_tolerance
algorithm!mass_trace!min_spectra=$min_spectra
algorithm!mass_trace!max_missing=$max_missing
algorithm!seed!min_score=$seed_min_score
algorithm!feature!min_score=$feature_min_score
algorithm!feature!reported_mz=$reported_mz
algorithm!isotopic_pattern!mz_tolerance=$isotopic_mz_tolerance
algorithm!isotopic_pattern!charge_low=$charge_low
algorithm!isotopic_pattern!charge_high=$charge_high
#if $advanced_isotopic_pattern.specify
algorithm!isotopic_pattern!abundance_12C=$abundance_12C
algorithm!isotopic_pattern!abundance_14N=$abundance_14N
#end if
</configfile>
  </configfiles>
  <inputs>
    <param name="input1" label="mzML Input" type="data" format="mzml" />
    <param name="bins" label="Bins" type="integer" help="Number of bins per dimension (RT and m/z). The higher this value, the more local the intensity significance score is. This parameter should be decreased, if the algorithm is used on small regions of a map." value="10" />
    <param name="trace_mz_tolerance" type="float" label="m/z Tolerance (Trace)" help="Tolerated m/z deviation of peaks belonging to the same mass trace. It should be larger than the m/z resolution of the instument. This value must be smaller than that 1/charge_high!" value="0.03" />
    <param name="min_spectra" label="Minimum Number of Spectra" help="Number of spectra that have to show a similar peak mass in a mass trace." value="10" type="integer" />
    <param name="max_missing" label="Max Missing" help="Number of consecutive spectra where a high mass deviation or missing peak is acceptable. This parameter should be well below 'min_spectra'!" value="1" type="integer" />
    <param name="seed_min_score" label="Seed Minimum Score" help="Minimum seed score a peak has to reach to be used as seed. The seed score is the geometric mean of intensity score, mass trace score and isotope pattern score. If your features show a large deviation from the averagene isotope distribution or from an gaussian elution profile, lower this score." type="float" value="0.8" />
    <param name="feature_min_score" label="Feature Minimum Score" help="Feature score threshold for a feature to be reported. The feature score is the geometric mean of the average relative deviation and the correlation between the model and the observed peaks." value="0.7" type="float" />
    <param name="reported_mz" label="Reported m/z" help="The mass type that is reported for features. 'maximum' returns the m/z value of the highest mass trace. 'average' returns the intensity-weighted average m/z value of all contained peaks. 'monoisotopic' returns the monoisotopic m/z value derived from the fitted isotope model." type="select">
      <option value="monoisotopic">monoisotopic</option>
      <option value="average">average</option>
      <option value="maximum">maximum</option>
    </param>
    <param name="charge_low" label="Minimum Charge" type="integer" value="1" />
    <param name="charge_high" label="Maximum Charge" type="integer" value="4" />
    <param name="isotopic_mz_tolerance" label="m/z Tolerance (Isotopic Pattern)" type="float" value="0.03" help="Tolerated m/z deviation from the theoretical isotopic pattern. It should be larger than the m/z resolution of the instument. This value must be smaller than that 1/charge_high!" />
    <conditional name="advanced_isotopic_pattern">
      <param type="boolean" name="specify" label="Specify Advanced Isotopic Pattern Parameters" />
      <when value="true">
        <param name="abundance_12C" label="12C Abundance" type="float" value="98.93" help="Rel. abundance of the light carbon. Modify if labeled." />
        <param name="abundance_14N" label="14N Abundance" type="float" value="99.632" help="Rel. abundance of the light nitrogen. Modify if labeled." />
      </when>
      <when value="false">
      </when>
    </conditional>
  </inputs>
  <outputs>
    <data format="featurexml" name="output" />
  </outputs>
  <help>
**What it does**

The mapping is based on retention times and mass-to-charge values. Roughly, a peptide identification is assigned to a (consensus) feature if its position lies within the boundaries of the feature or close enough to the feature centroid. Peptide identifications that don't match anywhere are still recorded in the resulting map, as "unassigned peptides". Protein identifications are annotated to the whole map, i.e. not to any particular (consensus) feature.

In all cases, tolerance in RT and m/z dimension is applied according to the parameters rt_tolerance and mz_tolerance. Tolerance is understood as "plus or minus x", so the matching range is actually increased by twice the tolerance value.

If several features or consensus features overlap the position of a peptide identification (taking the allowed tolerances into account), the identification is annotated to all of them.

Annotation of feature maps (featureXML input):
If all features have at least one convex hull, peptide positions are matched against the bounding boxes of the convex hulls (of individual mass traces, if available) by default. If not, the positions of the feature centroids are used. The respective coordinates of the centroids are also used for matching (in place of the corresponding ranges from the bounding boxes) if feature:use_centroid_rt or feature:use_centroid_mz are true.

Annotation of consensus maps (consensusXML input):
Peptide positions are always matched against centroid positions. By default, the consensus centroids are used. However, if consensusfeature:use_subelements is set, the centroids of sub-features are considered instead. In this case, a peptide identification is mapped to a consensus feature if any of its sub-features matches.

**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>