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1 <tool id="openms_feature_linker_unlabeled" version="0.1.0" name="Feature Linker (Labeled)">
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2 <description>
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3 Groups corresponding features from multiple maps.
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4 </description>
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5 <macros>
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6 <import>macros.xml</import>
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7 </macros>
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8 <expand macro="stdio" />
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9 <expand macro="requires" />
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10 <command interpreter="python">
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11 openms_wrapper.py --executable 'FeatureLinkedUnlabeled' --config $config
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12 </command>
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13 <configfiles>
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14 <configfile name="config">[simple_options]
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15 in=$input1
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16 out=$output
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17 </configfile>
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18 </configfiles>
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19 <inputs>
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20 <conditional name="type">
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21 <param name="input_type" type="select" label="Input Type">
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22 <option value="featurexml">Features (FeatureXML)</option>
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23 <option value="consensusxml">Consensus (ConsensusXML)</option>
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24 </param>
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25 <when value="featurexml">
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26 <param format="featurexml" name="input1" type="data" label="Input Features" />
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27 </when>
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28 <when value="consensusxml">
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29 <param format="consensusxml" name="input1" type="data" label="Input Consensus" />
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30 </when>
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31 </conditional>
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32 </inputs>
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33 <outputs>
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34 <data format="consensusxml" name="output" />
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35 </outputs>
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36 <help>
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37 **What it does**
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38
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39 This tool provides an algorithm for grouping corresponding features in multiple runs of label-free experiments. For more details and algorithm-specific parameters (set in the INI file) see "Detailed Description" in the algorithm documentation or the INI file table below.
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40
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41 FeatureLinkerUnlabeled takes several feature maps (featureXML files) and stores the corresponding features in a consensus map (consensusXML file). Feature maps can be created from MS experiments (peak data) using one of the FeatureFinder TOPP tools.
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42
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43 Advanced users can convert the consensusXML generated by this tool to EDTA using FileConverter and plot the distribution of distances in RT (or m/z) between different input files (can be done in Excel). The distribution should be Gaussian-like with very few points beyond the tails. Points far away from the Gaussian indicate a too wide tolerance. A Gaussian with its left/right tail trimmed indicates a too narrow tolerance.
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44
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45 **Citation**
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46
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47 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.``
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48
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49 If you use this tool in Galaxy, please cite Chilton J, et al. https://bitbucket.org/galaxyp/galaxyp-toolshed-openms
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50 </help>
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51 </tool>
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