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// --------------------------------------------------------------------------
// OpenMS -- Open-Source Mass Spectrometry
// --------------------------------------------------------------------------
// Copyright The OpenMS Team -- Eberhard Karls University Tuebingen,
// ETH Zurich, and Freie Universitaet Berlin 2002-2013.
//
// This software is released under a three-clause BSD license:
// * Redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
// * Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
// * Neither the name of any author or any participating institution
// may be used to endorse or promote products derived from this software
// without specific prior written permission.
// For a full list of authors, refer to the file AUTHORS.
// --------------------------------------------------------------------------
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
// ARE DISCLAIMED. IN NO EVENT SHALL ANY OF THE AUTHORS OR THE CONTRIBUTING
// INSTITUTIONS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
// EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
// PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
// OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
// WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
// OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF
// ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
//
// --------------------------------------------------------------------------
// $Maintainer: Lars Nilse $
// $Authors: Hendrik Brauer, Oliver Kohlbacher, Johannes Junker $
// --------------------------------------------------------------------------
#include <OpenMS/FORMAT/FileHandler.h>
#include <OpenMS/FORMAT/FileTypes.h>
#include <OpenMS/FORMAT/ConsensusXMLFile.h>
#include <OpenMS/APPLICATIONS/TOPPBase.h>
#include <OpenMS/ANALYSIS/MAPMATCHING/ConsensusMapNormalizerAlgorithmThreshold.h>
#include <OpenMS/ANALYSIS/MAPMATCHING/ConsensusMapNormalizerAlgorithmMedian.h>
#include <OpenMS/ANALYSIS/MAPMATCHING/ConsensusMapNormalizerAlgorithmQuantile.h>
using namespace OpenMS;
using namespace std;
//-------------------------------------------------------------
//Doxygen docu
//-------------------------------------------------------------
/**
@page TOPP_ConsensusMapNormalizer ConsensusMapNormalizer
@brief Normalization of intensities in a set of maps using robust regression.
<CENTER>
<table>
<tr>
<td ALIGN = "center" BGCOLOR="#EBEBEB"> potential predecessor tools </td>
<td VALIGN="middle" ROWSPAN=3> \f$ \longrightarrow \f$ ConsensusMapNormalizer \f$ \longrightarrow \f$</td>
<td ALIGN = "center" BGCOLOR="#EBEBEB"> potential successor tools </td>
</tr>
<tr>
<td VALIGN="middle" ALIGN = "center" ROWSPAN=2> @ref TOPP_FeatureLinkerUnlabeled @n (or another feature grouping tool) </td>
<td VALIGN="middle" ALIGN = "center" ROWSPAN=1> @ref TOPP_ProteinQuantifier </td>
</tr>
<tr>
<td VALIGN="middle" ALIGN = "center" ROWSPAN=1> @ref TOPP_TextExporter </td>
</tr>
</table>
</CENTER>
The tool normalizes the intensities of a set of maps (consensusXML file). The following normalization algorithms are available:
- Robust regression: Maps are normalized pair-wise relative to the map with the most features. Given two maps, peptide featues are classified as non-outliers (ratio_threshold < intensity ratio < 1/ratio_threshold) or outliers. From the non-outliers an average intensity ratio is calculated and used for normalization.
- Median correction: The median of all maps is set to the median of the map with the most features.
- Quantile normalization: Performs an exact quantile normalization if the number of features is equal across all maps. Otherwise, an approximate quantile normalization using resampling is applied.
<B>The command line parameters of this tool are:</B>
@verbinclude TOPP_ConsensusMapNormalizer.cli
<B>INI file documentation of this tool:</B>
@htmlinclude TOPP_ConsensusMapNormalizer.html
*/
// We do not want this class to show up in the docu:
/// @cond TOPPCLASSES
class TOPPConsensusMapNormalizer :
public TOPPBase
{
public:
TOPPConsensusMapNormalizer() :
TOPPBase("ConsensusMapNormalizer", "Normalizes maps of one consensusXML file")
{
}
protected:
void registerOptionsAndFlags_()
{
registerInputFile_("in", "<file>", "", "input file");
setValidFormats_("in", StringList::create("consensusXML"));
registerOutputFile_("out", "<file>", "", "output file");
setValidFormats_("out", StringList::create("consensusXML"));
addEmptyLine_();
registerStringOption_("algorithm_type", "<type>", "robust_regression", "The normalization algorithm that is applied.", false, false);
setValidStrings_("algorithm_type", StringList::create("robust_regression,median,quantile"));
registerDoubleOption_("ratio_threshold", "<ratio>", 0.67, "Only for 'robust_regression': the parameter is used to distinguish between non-outliers (ratio_threshold < intensity ratio < 1/ratio_threshold) and outliers.", false);
setMinFloat_("ratio_threshold", 0.001);
setMaxFloat_("ratio_threshold", 1.0);
}
ExitCodes main_(int, const char **)
{
String in = getStringOption_("in");
String out = getStringOption_("out");
String algo_type = getStringOption_("algorithm_type");
double ratio_threshold = getDoubleOption_("ratio_threshold");
ConsensusXMLFile infile;
infile.setLogType(log_type_);
ConsensusMap map;
infile.load(in, map);
//map normalization
if (algo_type == "robust_regression")
{
map.sortBySize();
vector<double> results = ConsensusMapNormalizerAlgorithmThreshold::computeCorrelation(map, ratio_threshold);
ConsensusMapNormalizerAlgorithmThreshold::normalizeMaps(map, results);
}
else if (algo_type == "median")
{
ConsensusMapNormalizerAlgorithmMedian::normalizeMaps(map);
}
else if (algo_type == "quantile")
{
ConsensusMapNormalizerAlgorithmQuantile::normalizeMaps(map);
}
else
{
cerr << "Unknown algorithm type '" << algo_type.c_str() << "'." << endl;
return ILLEGAL_PARAMETERS;
}
//annotate output with data processing info and save output file
addDataProcessing_(map, getProcessingInfo_(DataProcessing::NORMALIZATION));
infile.store(out, map);
return EXECUTION_OK;
}
};
int main(int argc, const char ** argv)
{
TOPPConsensusMapNormalizer tool;
return tool.main(argc, argv);
}
/// @endcond
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