void EDTAFile::store(const String& filename, const ConsensusMap& map) const
{
TextFile tf;
// search for maximum number of sub-features (since this determines the number of columns)
Size max_sub(0);
for (Size i = 0; i < map.size(); ++i)
{
max_sub = std::max(max_sub, map[i].getFeatures().size());
}
// write header
String header("RT\tm/z\tintensity\tcharge");
for (Size i = 1; i <= max_sub; ++i)
{
header += "\tRT" + String(i) + "\tm/z" + String(i) + "\tintensity" + String(i) + "\tcharge" + String(i);
}
tf.addLine(header);
for (Size i = 0; i < map.size(); ++i)
{
ConsensusFeature f = map[i];
// consensus
String entry = String(f.getRT()) + "\t" + f.getMZ() + "\t" + f.getIntensity() + "\t" + f.getCharge();
// sub-features
ConsensusFeature::HandleSetType handle = f.getFeatures();
for (ConsensusFeature::HandleSetType::const_iterator it = handle.begin(); it != handle.end(); ++it)
{
entry += String("\t") + it->getRT() + "\t" + it->getMZ() + "\t" + it->getIntensity() + "\t" + it->getCharge();
}
// missing sub-features
for (Size j = handle.size(); j < max_sub; ++j)
{
entry += "\tNA\tNA\tNA\tNA";
}
tf.addLine(entry);
}
tf.store(filename);
}
// need an instance of FeatureGroupingAlgorithm: String algo_name = Factory<FeatureGroupingAlgorithm>::registeredProducts()[0]; FeatureGroupingAlgorithm* algo = Factory<FeatureGroupingAlgorithm>::create( algo_name); algo->transferSubelements(maps, out); TEST_EQUAL(out.getFileDescriptions().size(), 4); TEST_EQUAL(out.getFileDescriptions()[0].filename, "file1"); TEST_EQUAL(out.getFileDescriptions()[3].filename, "file4"); TEST_EQUAL(out.size(), 1); TEST_EQUAL(out[0].size(), 4); ConsensusFeature::HandleSetType group = out[0].getFeatures(); ConsensusFeature::HandleSetType::const_iterator it = group.begin(); handle3.setMapIndex(2); handle4.setMapIndex(3); TEST_EQUAL(*it++ == handle1, true); TEST_EQUAL(*it++ == handle2, true); TEST_EQUAL(*it++ == handle3, true); TEST_EQUAL(*it++ == handle4, true); } END_SECTION ///////////////////////////////////////////////////////////// ///////////////////////////////////////////////////////////// END_TEST
TEST_EQUAL(result.size(),3); ABORT_IF(result.size()!=3); ConsensusFeature::HandleSetType group1 = result[0].getFeatures(); ConsensusFeature::HandleSetType group2 = result[1].getFeatures(); ConsensusFeature::HandleSetType group3 = result[2].getFeatures(); FeatureHandle ind1(0,feat1); FeatureHandle ind2(0,feat2); FeatureHandle ind3(0,feat3); FeatureHandle ind4(1,feat4); FeatureHandle ind5(1,feat5); FeatureHandle ind6(1,feat6); ConsensusFeature::HandleSetType::const_iterator it; it = group1.begin(); STATUS(*it); STATUS(ind1); TEST_EQUAL(*(it) == ind1, true) ++it; STATUS(*it); STATUS(ind4); TEST_EQUAL(*(it) == ind4, true) it = group2.begin(); STATUS(*it); STATUS(ind2); TEST_EQUAL(*(it) == ind2, true) ++it; STATUS(*it); STATUS(ind5); TEST_EQUAL(*(it) == ind5, true)
void IBSpectraFile::store(const String& filename, const ConsensusMap& cm)
{
// typdefs for shorter code
typedef std::vector<ProteinHit>::iterator ProtHitIt;
// general settings .. do we need to expose these?
// ----------------------------------------------------------------------
/// Allow also non-unique peptides to be exported
bool allow_non_unique = true;
/// Intensities below this value will be set to 0.0 to avoid numerical problems when quantifying
double intensity_threshold = 0.00001;
// ----------------------------------------------------------------------
// guess experiment type
boost::shared_ptr<IsobaricQuantitationMethod> quantMethod = guessExperimentType_(cm);
// we need the protein identifications to reference the protein names
ProteinIdentification protIdent;
bool has_proteinIdentifications = false;
if (cm.getProteinIdentifications().size() > 0)
{
protIdent = cm.getProteinIdentifications()[0];
has_proteinIdentifications = true;
}
// start the file by adding the tsv header
TextFile textFile;
textFile.addLine(ListUtils::concatenate(constructHeader_(*quantMethod), "\t"));
for (ConsensusMap::ConstIterator cm_iter = cm.begin();
cm_iter != cm.end();
++cm_iter)
{
const ConsensusFeature& cFeature = *cm_iter;
std::vector<IdCSV> entries;
/// 1st we extract the identification information from the consensus feature
if (cFeature.getPeptideIdentifications().size() == 0 || !has_proteinIdentifications)
{
// we store unidentified hits anyway, because the iTRAQ quant is still helpful for normalization
entries.push_back(IdCSV());
}
else
{
// protein name:
const PeptideHit& peptide_hit = cFeature.getPeptideIdentifications()[0].getHits()[0];
std::set<String> protein_accessions = peptide_hit.extractProteinAccessions();
if (protein_accessions.size() != 1)
{
if (!allow_non_unique) continue; // we only want unique peptides
}
for (std::set<String>::const_iterator prot_ac = protein_accessions.begin(); prot_ac != protein_accessions.end(); ++prot_ac)
{
IdCSV entry;
entry.charge = cFeature.getPeptideIdentifications()[0].getHits()[0].getCharge();
entry.peptide = cFeature.getPeptideIdentifications()[0].getHits()[0].getSequence().toUnmodifiedString();
entry.theo_mass = cFeature.getPeptideIdentifications()[0].getHits()[0].getSequence().getMonoWeight(Residue::Full, cFeature.getPeptideIdentifications()[0].getHits()[0].getCharge());
// write modif
entry.modif = getModifString_(cFeature.getPeptideIdentifications()[0].getHits()[0].getSequence());
ProtHitIt proteinHit = protIdent.findHit(*prot_ac);
if (proteinHit == protIdent.getHits().end())
{
std::cerr << "Protein referenced in peptide not found...\n";
continue; // protein not found
}
entry.accession = proteinHit->getAccession();
entries.push_back(entry);
}
}
// 2nd we add the quantitative information of the channels
// .. skip features with 0 intensity
if (cFeature.getIntensity() == 0)
{
continue;
}
for (std::vector<IdCSV>::iterator entry = entries.begin();
entry != entries.end();
++entry)
{
// set parent intensity
entry->parent_intens = cFeature.getIntensity();
entry->retention_time = cFeature.getRT();
entry->spectrum = cFeature.getUniqueId();
entry->exp_mass = cFeature.getMZ();
// create output line
StringList currentLine;
// add entry to currentLine
entry->toStringList(currentLine);
// extract channel intensities and positions
std::map<Int, double> intensityMap;
ConsensusFeature::HandleSetType features = cFeature.getFeatures();
for (ConsensusFeature::HandleSetType::const_iterator fIt = features.begin();
fIt != features.end();
++fIt)
{
intensityMap[Int(fIt->getMZ())] = (fIt->getIntensity() > intensity_threshold ? fIt->getIntensity() : 0.0);
}
for (IsobaricQuantitationMethod::IsobaricChannelList::const_iterator it = quantMethod->getChannelInformation().begin();
it != quantMethod->getChannelInformation().end();
++it)
{
currentLine.push_back(String(it->center));
}
for (IsobaricQuantitationMethod::IsobaricChannelList::const_iterator it = quantMethod->getChannelInformation().begin();
it != quantMethod->getChannelInformation().end();
++it)
{
currentLine.push_back(String(intensityMap[int(it->center)]));
}
textFile.addLine(ListUtils::concatenate(currentLine, "\t"));
}
}
// write to file
textFile.store(filename);
}