Param getSubsectionDefaults_(const String & section) const
{
if (section == "algorithm")
{
MapAlignmentAlgorithmIdentification algo;
return algo.getParameters();
}
if (section == "model")
{
return TOPPMapAlignerBase::getModelDefaults("b_spline");
}
return Param(); // this shouldn't happen
}
void performAlignment_(MapAlignmentAlgorithmIdentification& algorithm,
vector<DataType>& data,
vector<TransformationDescription>& transformations,
Int reference_index)
{
algorithm.align(data, transformations, reference_index);
// find model parameters:
Param model_params = getParam_().copy("model:", true);
String model_type = model_params.getValue("type");
if (model_type != "none")
{
model_params = model_params.copy(model_type + ":", true);
for (vector<TransformationDescription>::iterator it =
transformations.begin(); it != transformations.end(); ++it)
{
it->fitModel(model_type, model_params);
}
}
for (Size i = 0; i < data.size(); ++i)
{
MapAlignmentTransformer::transformRetentionTimes(data[i],
transformations[i]);
}
}
Int getReference_(MapAlignmentAlgorithmIdentification& algorithm)
{
// consistency of reference parameters has already been checked via
// "TOPPMapAlignerBase::checkParameters_"
Size reference_index = getIntOption_("reference:index");
String reference_file = getStringOption_("reference:file");
if (!reference_file.empty())
{
FileTypes::Type filetype = FileHandler::getType(reference_file);
if (filetype == FileTypes::MZML)
{
PeakMap experiment;
MzMLFile().load(reference_file, experiment);
algorithm.setReference(experiment);
}
else if (filetype == FileTypes::FEATUREXML)
{
FeatureMap features;
FeatureXMLFile().load(reference_file, features);
algorithm.setReference(features);
}
else if (filetype == FileTypes::CONSENSUSXML)
{
ConsensusMap consensus;
ConsensusXMLFile().load(reference_file, consensus);
algorithm.setReference(consensus);
}
else if (filetype == FileTypes::IDXML)
{
vector<ProteinIdentification> proteins;
vector<PeptideIdentification> peptides;
IdXMLFile().load(reference_file, proteins, peptides);
algorithm.setReference(peptides);
}
}
return Int(reference_index) - 1; // internally, we count from zero
}
ExitCodes main_(int, const char**)
{
ExitCodes return_code = TOPPMapAlignerBase::checkParameters_();
if (return_code != EXECUTION_OK) return return_code;
// set up alignment algorithm:
MapAlignmentAlgorithmIdentification algorithm;
Param algo_params = getParam_().copy("algorithm:", true);
algorithm.setParameters(algo_params);
algorithm.setLogType(log_type_);
Int reference_index = getReference_(algorithm);
// handle in- and output files:
StringList input_files = getStringList_("in");
StringList output_files = getStringList_("out");
StringList trafo_files = getStringList_("trafo_out");
FileTypes::Type in_type = FileHandler::getType(input_files[0]);
vector<TransformationDescription> transformations;
//-------------------------------------------------------------
// perform feature alignment
//-------------------------------------------------------------
if (in_type == FileTypes::FEATUREXML)
{
vector<FeatureMap> feature_maps(input_files.size());
FeatureXMLFile fxml_file;
if (output_files.empty())
{
// store only transformation descriptions, not transformed data =>
// we can load only minimum required information:
fxml_file.getOptions().setLoadConvexHull(false);
fxml_file.getOptions().setLoadSubordinates(false);
}
loadInitialMaps_(feature_maps, input_files, fxml_file);
performAlignment_(algorithm, feature_maps, transformations,
reference_index);
if (!output_files.empty())
{
storeTransformedMaps_(feature_maps, output_files, fxml_file);
}
}
//-------------------------------------------------------------
// perform consensus alignment
//-------------------------------------------------------------
else if (in_type == FileTypes::CONSENSUSXML)
{
std::vector<ConsensusMap> consensus_maps(input_files.size());
ConsensusXMLFile cxml_file;
loadInitialMaps_(consensus_maps, input_files, cxml_file);
performAlignment_(algorithm, consensus_maps, transformations,
reference_index);
if (!output_files.empty())
{
storeTransformedMaps_(consensus_maps, output_files, cxml_file);
}
}
//-------------------------------------------------------------
// perform peptide alignment
//-------------------------------------------------------------
else if (in_type == FileTypes::IDXML)
{
vector<vector<ProteinIdentification> > protein_ids(input_files.size());
vector<vector<PeptideIdentification> > peptide_ids(input_files.size());
IdXMLFile idxml_file;
ProgressLogger progresslogger;
progresslogger.setLogType(log_type_);
progresslogger.startProgress(0, input_files.size(),
"loading input files");
for (Size i = 0; i < input_files.size(); ++i)
{
progresslogger.setProgress(i);
idxml_file.load(input_files[i], protein_ids[i], peptide_ids[i]);
}
progresslogger.endProgress();
performAlignment_(algorithm, peptide_ids, transformations,
reference_index);
if (!output_files.empty())
{
progresslogger.startProgress(0, output_files.size(),
"writing output files");
for (Size i = 0; i < output_files.size(); ++i)
{
progresslogger.setProgress(i);
idxml_file.store(output_files[i], protein_ids[i], peptide_ids[i]);
}
progresslogger.endProgress();
}
}
if (!trafo_files.empty())
{
storeTransformationDescriptions_(transformations, trafo_files);
}
return EXECUTION_OK;
}
ExitCodes main_(int, const char**) override
{
ExitCodes return_code = TOPPMapAlignerBase::checkParameters_();
if (return_code != EXECUTION_OK) return return_code;
// set up alignment algorithm:
MapAlignmentAlgorithmIdentification algorithm;
Param algo_params = getParam_().copy("algorithm:", true);
algorithm.setParameters(algo_params);
algorithm.setLogType(log_type_);
Int reference_index = getReference_(algorithm);
// handle in- and output files:
StringList input_files = getStringList_("in");
StringList output_files = getStringList_("out");
StringList trafo_files = getStringList_("trafo_out");
FileTypes::Type in_type = FileHandler::getType(input_files[0]);
vector<TransformationDescription> transformations;
//-------------------------------------------------------------
// perform feature alignment
//-------------------------------------------------------------
if (in_type == FileTypes::FEATUREXML)
{
vector<FeatureMap> feature_maps(input_files.size());
FeatureXMLFile fxml_file;
if (output_files.empty())
{
// store only transformation descriptions, not transformed data =>
// we can load only minimum required information:
fxml_file.getOptions().setLoadConvexHull(false);
fxml_file.getOptions().setLoadSubordinates(false);
}
loadInitialMaps_(feature_maps, input_files, fxml_file);
//-------------------------------------------------------------
// Extract (optional) fraction identifiers and associate with featureXMLs
//-------------------------------------------------------------
String design_file = getStringOption_("design");
// determine map of fractions to runs
map<unsigned, vector<String> > frac2files;
// TODO: check if can be put in common helper function
if (!design_file.empty())
{
// parse design file and determine fractions
ExperimentalDesign ed = ExperimentalDesignFile::load(design_file, false);
// determine if design defines more than one fraction (note: fraction and run IDs are one-based)
frac2files = ed.getFractionToMSFilesMapping();
// check if all fractions have the same number of MS runs associated
if (!ed.sameNrOfMSFilesPerFraction())
{
writeLog_("Error: Number of runs must match for every fraction!");
return ILLEGAL_PARAMETERS;
}
}
else // no design file given
{
for (Size i = 0; i != input_files.size(); ++i)
{
// TODO: read proper MS file name from meta data
frac2files[1].push_back("file" + String(i)); // associate each file with fraction 1
}
}
// TODO: check and handle if featureXML order differs from run order
// perform fraction-based alignment
if (frac2files.size() == 1) // group one fraction
{
performAlignment_(algorithm, feature_maps, transformations,
reference_index);
applyTransformations_(feature_maps, transformations);
}
else // group multiple fractions
{
for (Size i = 1; i <= frac2files.size(); ++i)
{
vector<FeatureMap> fraction_maps;
vector<TransformationDescription> fraction_transformations;
size_t n_fractions = frac2files.size();
// TODO FRACTIONS: determine map index based on annotated MS files (getPrimaryMSRuns())
for (size_t feature_map_index = 0;
feature_map_index != n_fractions;
++feature_map_index)
{
fraction_maps.push_back(feature_maps[feature_map_index]);
}
performAlignment_(algorithm, fraction_maps, fraction_transformations,
reference_index);
applyTransformations_(fraction_maps, fraction_transformations);
// copy into transformations and feature maps
transformations.insert(transformations.end(), fraction_transformations.begin(), fraction_transformations.end());
Size f = 0;
for (size_t feature_map_index = 0;
feature_map_index != n_fractions;
++feature_map_index,
++f)
{
feature_maps[feature_map_index].swap(fraction_maps[f]);
}
}
}
if (!output_files.empty())
{
storeTransformedMaps_(feature_maps, output_files, fxml_file);
}
}
//-------------------------------------------------------------
// perform consensus alignment
//-------------------------------------------------------------
else if (in_type == FileTypes::CONSENSUSXML)
{
std::vector<ConsensusMap> consensus_maps(input_files.size());
ConsensusXMLFile cxml_file;
loadInitialMaps_(consensus_maps, input_files, cxml_file);
performAlignment_(algorithm, consensus_maps, transformations,
reference_index);
applyTransformations_(consensus_maps, transformations);
if (!output_files.empty())
{
storeTransformedMaps_(consensus_maps, output_files, cxml_file);
}
}
//-------------------------------------------------------------
// perform peptide alignment
//-------------------------------------------------------------
else if (in_type == FileTypes::IDXML)
{
vector<vector<ProteinIdentification> > protein_ids(input_files.size());
vector<vector<PeptideIdentification> > peptide_ids(input_files.size());
IdXMLFile idxml_file;
ProgressLogger progresslogger;
progresslogger.setLogType(log_type_);
progresslogger.startProgress(0, input_files.size(),
"loading input files");
for (Size i = 0; i < input_files.size(); ++i)
{
progresslogger.setProgress(i);
idxml_file.load(input_files[i], protein_ids[i], peptide_ids[i]);
}
progresslogger.endProgress();
performAlignment_(algorithm, peptide_ids, transformations,
reference_index);
applyTransformations_(peptide_ids, transformations);
if (!output_files.empty())
{
progresslogger.startProgress(0, output_files.size(),
"writing output files");
for (Size i = 0; i < output_files.size(); ++i)
{
progresslogger.setProgress(i);
idxml_file.store(output_files[i], protein_ids[i], peptide_ids[i]);
}
progresslogger.endProgress();
}
}
if (!trafo_files.empty())
{
storeTransformationDescriptions_(transformations, trafo_files);
}
return EXECUTION_OK;
}
