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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: Alexandra Zerck $
// $Authors: Alexandra Zerck $
// --------------------------------------------------------------------------
#include <OpenMS/FORMAT/FeatureXMLFile.h>
#include <OpenMS/FORMAT/IdXMLFile.h>
#include <OpenMS/FORMAT/MzMLFile.h>
#include <OpenMS/APPLICATIONS/TOPPBase.h>
#include <OpenMS/ANALYSIS/TARGETED/PrecursorIonSelection.h>
#include <OpenMS/ANALYSIS/TARGETED/PrecursorIonSelectionPreprocessing.h>
using namespace OpenMS;
//-------------------------------------------------------------
//Doxygen docu
//-------------------------------------------------------------
/**
@page TOPP_PrecursorIonSelector PrecursorIonSelector
@brief A tool for precursor ion selection based on identification results.
<CENTER>
<table>
<tr>
<td ALIGN = "center" BGCOLOR="#EBEBEB"> pot. predecessor tools </td>
<td VALIGN="middle" ROWSPAN=3> \f$ \longrightarrow \f$ PrecursorIonSelector \f$ \longrightarrow \f$</td>
<td ALIGN = "center" BGCOLOR="#EBEBEB"> pot. successor tools </td>
</tr>
<tr>
<td VALIGN="middle" ALIGN = "center" ROWSPAN=1> @ref TOPP_FeatureFinderCentroided </td>
<td VALIGN="middle" ALIGN = "center" ROWSPAN=2> - </td>
</tr>
</table>
</CENTER>
This tool provides a precursor ion selection based on previous MS/MS
identifications.
Different strategies can be chosen:
<table>
<tr>
<td><b>DEX</b></td>
<td>Dynamic exclusion of features with m/z matching predicted tryptic peptides masses of already identified proteins.</td>
</tr>
<tr>
<td><b>SPS</b></td>
<td>Selection based on score reflecting the feature's suitability for fragmentation.</td>
</tr>
<tr>
<td><b>Downshift</b></td>
<td>Similar to DEX, but features are not excluded, only ranked down in the feature list</td>
</tr>
<tr>
<td><b>Upshift</b></td>
<td>Features with m/z matching predicted tryptic peptide masses of unidentified proteins are ranked up.</td>
</tr>
<tr>
<td><b>IPS</b></td>
<td>Combination of Down- and Upshift.</td>
</tr>
<tr>
<td><b>ILP_IPS</b></td>
<td>Iterative precursor ion selection using LP formulations.</td>
</tr>
</table>
This method is described in: Zerck, A. and Nordhoff, E. and Resemann, A. and Mirgorodskaya, E. and Suckau, D. and Reinert, K. and Lehrach, H. and Gobom, J.:
An iterative strategy for precursor ion selection for LC-MS/MS based shotgun proteomics, J Prot Res, 2009, 8 (7), 3239-3251.
Given the feature map of the LC-MS run and the identification results
the tool determines the next precursors. The precursors are ranked
depending on the chosen strategy.
It is also possible run a simulation of selection strategies
on a complete LC-MS/MS run, e.g. to determine what would have been
the most efficient strategy.
<B>The command line parameters of this tool are:</B>
@verbinclude TOPP_PrecursorIonSelector.cli
<B>INI file documentation of this tool:</B>
@htmlinclude TOPP_PrecursorIonSelector.html
For the parameters of the algorithm section see the algorithm's documentation: @n
@ref OpenMS::PrecursorIonSelection @n
*/
// We do not want this class to show up in the docu:
/// @cond TOPPCLASSES
class TOPPPrecursorIonSelector :
public TOPPBase
{
public:
TOPPPrecursorIonSelector() :
TOPPBase("PrecursorIonSelector", "PrecursorIonSelector")
{
}
protected:
void registerOptionsAndFlags_()
{
registerInputFile_("in", "<input file>", "", "Input feature map file (featureXML)");
setValidFormats_("in", StringList::create("featureXML"));
registerOutputFile_("out", "<output file>", "", "modified feature map", false);
setValidFormats_("out", StringList::create("featureXML"));
registerOutputFile_("next_feat", "<output file>", "", "feature map (featureXML) file with the selected precursors", false);
setValidFormats_("next_feat", StringList::create("featureXML"));
registerStringOption_("ids", "<idxml file>", "", "file containing results of identification (idXML)");
registerIntOption_("num_precursors", "<Int>", 1, "number of precursors to be selected", false);
registerInputFile_("raw_data", "<file>", "", "Input profile data.", false);
setValidFormats_("raw_data", StringList::create("mzML"));
registerFlag_("load_preprocessing", "The preprocessed db is loaded from file, not calculated.");
registerFlag_("store_preprocessing", "The preprocessed db is stored.");
registerFlag_("simulation", "Simulate the whole LC-MS/MS run.");
registerStringOption_("sim_results", "<output file>", "", "File containing the results of the simulation run", false);
registerInputFile_("db_path", "<db-file>", "", "db file", false);
setValidFormats_("db_path", StringList::create("fasta"));
registerStringOption_("rt_model", "<rt-model-file>", "", "SVM Model for RTPredict", false);
registerStringOption_("dt_model", "<dt-model-file>", "", "SVM Model for PTPredict", false);
registerStringOption_("solver", "<solver-type>", "GLPK", "LP solver type", false, true);
setValidStrings_("solver", StringList::create("GLPK,COINOR"));
registerStringList_("fixed_modifications", "<mods>", StringList(), "the modifications i.e. Carboxymethyl (C)", false);
addEmptyLine_();
registerSubsection_("algorithm", "Settings for the compound list creation and rescoring.");
}
Param getSubsectionDefaults_(const String & /* section*/) const
{
Param param = PrecursorIonSelection().getDefaults();
// param.insert("",PrecursorIonSelection().getDefaults().copy(""));
return param;
}
ExitCodes main_(int, const char **)
{
//-------------------------------------------------------------
// parameter handling
//-------------------------------------------------------------
String in(getStringOption_("in"));
String out(getStringOption_("out"));
String raw_data(getStringOption_("raw_data"));
String next_prec = getStringOption_("next_feat");
String ids = getStringOption_("ids");
String db_path = getStringOption_("db_path");
UInt prec_num = getIntOption_("num_precursors");
bool simulation = getFlag_("simulation");
String sim_results = getStringOption_("sim_results");
bool load_preprocessing = getFlag_("load_preprocessing");
bool store_preprocessing = getFlag_("store_preprocessing");
String rt_model = getStringOption_("rt_model");
String dt_model = getStringOption_("dt_model");
String solver(getStringOption_("solver"));
StringList fixed_mods = getStringList_("fixed_modifications");
//-------------------------------------------------------------
// init pis preprocessing
//-------------------------------------------------------------
Param pisp_param = getParam_().copy("algorithm:Preprocessing:", true);
pisp_param.remove("type");
pisp_param.remove("min_pep_ids");
pisp_param.remove("max_iteration");
writeDebug_("Parameters passed to PrecursorIonSelectionPreprocessing", pisp_param, 3);
PrecursorIonSelectionPreprocessing pisp;
// pisp.setLogType(log_type_);
pisp.setParameters(pisp_param);
pisp.setFixedModifications(fixed_mods);
if (load_preprocessing)
{
pisp.loadPreprocessing();
}
else if (db_path == "")
{
writeLog_("No database file specified. Aborting!");
printUsage_();
return ILLEGAL_PARAMETERS;
}
else if (rt_model == "" || dt_model == "")
{
pisp.dbPreprocessing(db_path, store_preprocessing);
}
else
{
pisp.dbPreprocessing(db_path, rt_model, dt_model, store_preprocessing);
}
MSExperiment<> exp;
if (raw_data != "") MzMLFile().load(raw_data, exp);
//-------------------------------------------------------------
// init pis
//-------------------------------------------------------------
Param pis_param = getParam_().copy("algorithm:", true);
pis_param.removeAll("preprocessing");
writeDebug_("Parameters passed to PrecursorIonSelection", pis_param, 3);
PrecursorIonSelection pis;
// pis.setLogType(log_type_);
pis.setParameters(pis_param);
#if COINOR_SOLVER == 1
if (solver == "GLPK")
{
pis.setLPSolver(LPWrapper::SOLVER_GLPK);
}
else pis.setLPSolver(LPWrapper::SOLVER_COINOR);
#endif
//-------------------------------------------------------------
// loading input
//-------------------------------------------------------------
FeatureMap<> f_map;
FeatureXMLFile f_file;
f_file.load(in, f_map);
std::vector<PeptideIdentification> pep_ids;
std::vector<ProteinIdentification> prot_ids;
String document_id;
IdXMLFile idxml_file;
idxml_file.load(ids, prot_ids, pep_ids, document_id);
//-------------------------------------------------------------
// preprocessing, rescoring
//-------------------------------------------------------------
if (simulation)
{
pis.simulateRun(f_map, pep_ids, prot_ids, pisp, sim_results, exp, "");
}
else
{
pis.rescore(f_map, pep_ids, prot_ids, pisp); // todo: add "rescoring" for LP selection
FeatureMap<> new_precursors;
pis.getNextPrecursors(f_map, new_precursors, prec_num);
//-------------------------------------------------------------
// writing output
//-------------------------------------------------------------
if (next_prec != "") f_file.store(next_prec, new_precursors);
}
if (out != "") f_file.store(out, f_map);
return EXECUTION_OK;
}
};
int main(int argc, const char ** argv)
{
TOPPPrecursorIonSelector tool;
return tool.main(argc, argv);
}
/// @endcond
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