annotate peak_picker_hi_res.xml @ 3:8fa16707e162 draft

Update.

<tool id="openms_peak_picker_hi_res" version="0.1" name="Peak Peaker (Hi Res)">
  <description>
  </description>
  <macros>
    <import>macros.xml</import>
  </macros>
  <expand macro="stdio" />
  <expand macro="requires" />
  <command>
    openms_wrapper.py --executable 'PeakPickerHiRes' --config $config
  </command>
  <configfiles>
    <configfile name="config">[simple_options]
in=${input}
out=${out}
algorithm!signal_to_noise=${signal_to_noise}
algorithm!ms1_only=${ms1_only}
</configfile>
  </configfiles>  
  <inputs>
    <param format="mzML" name="input" type="data" label="Input profile peak list"/>
    <param type="float" name="signal_to_noise" value="1" label="Signal-to-noise ratio" help="Minimal signal-to-noise ratio for a peak to be picked (0.0 disables SNT estimation!)" />
    <param type="boolean" name="ms1_only" label="MS1 Only" help="If checked, peak picking is only applied to MS1 scans. Other scans are copied to the output without changes." />
  </inputs>
  <outputs>
    <data format="mzML" name="out" />
  </outputs>
  <help>
**What it does**

This peak-picking algorithm detects ion signals in raw data and reconstructs the corresponding peak shape by cubic spline interpolation. Signal detection depends on the signal-to-noise ratio which is adjustable by the user (see parameter signal_to_noise). A picked peak's m/z and intensity value is given by the maximum of the underlying peak spline. Please notice that this method is still experimental since it has not been tested thoroughly yet.

The algorithm used by this tool is best suited for high-resolution MS data (FT-ICR-MS, Orbitrap). In high-resolution data, the signals of ions with similar mass-to-charge ratios (m/z) exhibit little or no overlapping and therefore allow for a clear separation. Furthermore, ion signals tend to show well-defined peak shapes with narrow peak width. These properties faciliate a fast computation of picked peaks so that even large data sets can be processed very quickly.

**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>