int main()
{
// create a peak map containing 4 dummy spectra and peaks
MSExperiment exp;
// The following examples creates a MSExperiment containing four MSSpectrum instances.
for (Size i = 0; i < 4; ++i)
{
MSSpectrum spectrum;
spectrum.setRT(i);
spectrum.setMSLevel(1);
for (float mz = 500.0; mz <= 900; mz += 100.0)
{
Peak1D peak;
peak.setMZ(mz + i);
spectrum.push_back(peak);
}
exp.addSpectrum(spectrum);
}
// Iteration over the RT range (2,3) and the m/z range (603,802) and print the peak positions.
for (auto it = exp.areaBegin(2.0, 3.0, 603.0, 802.0); it != exp.areaEnd(); ++it)
{
cout << it.getRT() << " - " << it->getMZ() << endl;
}
// Iteration over all peaks in the experiment.
// Output: RT, m/z, and intensity
// Note that the retention time is stored in the spectrum (not in the peak object)
for (auto s_it = exp.begin(); s_it != exp.end(); ++s_it)
{
for (auto p_it = s_it->begin(); p_it != s_it->end(); ++p_it)
{
cout << s_it->getRT() << " - " << p_it->getMZ() << " " << p_it->getIntensity() << endl;
}
}
// We could store the spectra to a mzML file with:
// MzMLFile mzml;
// mzml.store(filename, exp);
// And load it with
// mzml.load(filename, exp);
// If we wanted to load only the MS2 spectra we could speed up reading by setting:
// mzml.getOptions().addMSLevel(2);
// before executing: mzml.load(filename, exp);
return 0;
} //end of main
void OpenSwathDataAccessHelper::convertToOpenMSSpectrum(const OpenSwath::SpectrumPtr sptr, OpenMS::MSSpectrum<> & spectrum)
{
// recreate a spectrum from the data arrays!
OpenSwath::BinaryDataArrayPtr mz_arr = sptr->getMZArray();
OpenSwath::BinaryDataArrayPtr int_arr = sptr->getIntensityArray();
spectrum.reserve(mz_arr->data.size());
for (Size i = 0; i < mz_arr->data.size(); i++)
{
Peak1D p;
p.setMZ(mz_arr->data[i]);
p.setIntensity(int_arr->data[i]);
spectrum.push_back(p);
}
}
void getSwathFile(PeakMap& exp, int nr_swathes=32, bool ms1=true)
{
if (ms1)
{
MSSpectrum s;
s.setMSLevel(1);
Peak1D p; p.setMZ(100); p.setIntensity(200);
s.push_back(p);
exp.addSpectrum(s);
}
for (int i = 0; i< nr_swathes; i++)
{
MSSpectrum s;
s.setMSLevel(2);
std::vector<Precursor> prec(1);
prec[0].setIsolationWindowLowerOffset(12.5);
prec[0].setIsolationWindowUpperOffset(12.5);
prec[0].setMZ(400 + i*25 + 12.5);
s.setPrecursors(prec);
Peak1D p; p.setMZ(101 + i); p.setIntensity(201 + i);
s.push_back(p);
exp.addSpectrum(s);
}
}
bool IDEvaluationBase::getPoints(std::vector<PeptideIdentification>& peptides /* cannot be const, to avoid copy */,
const std::vector<double>& q_value_thresholds, MSSpectrum<>& points)
{
points.clear(true);
FalseDiscoveryRate fdr;
fdr.setParameters(param_.copy("fdr:", true));
try
{
fdr.apply(peptides); // computes a q-value (if its params are correct)
}
catch (Exception::MissingInformation)
{
LOG_FATAL_ERROR << "Tool failed due to missing information (see above)." << std::endl;
return false;
}
// get list of q-values and sort them
std::vector<double> q_values;
q_values.reserve(peptides.size());
for (vector<PeptideIdentification>::iterator it = peptides.begin(); it != peptides.end(); ++it)
{
it->assignRanks();
if (it->getHits().size() > 0)
q_values.push_back(it->getHits()[0].getScore());
}
std::sort(q_values.begin(), q_values.end());
for (Size i = 0; i < q_value_thresholds.size(); ++i)
{
// get position in sorted q-values where cutoff is reached
std::vector<double>::iterator pos = std::upper_bound(q_values.begin(), q_values.end(), q_value_thresholds[i]);
Peak1D p;
p.setMZ(q_value_thresholds[i] * 100);
p.setIntensity(std::distance(q_values.begin(), pos));
points.push_back(p);
}
return true;
}
Int main()
{
MSSpectrum<> spectrum;
Peak1D peak;
for (float mz = 1500.0; mz >= 500; mz -= 100.0)
{
peak.setMZ(mz);
spectrum.push_back(peak);
}
spectrum.sortByPosition();
MSSpectrum<>::Iterator it;
for (it = spectrum.MZBegin(800.0); it != spectrum.MZEnd(1000.0); ++it)
{
cout << it->getMZ() << endl;
}
return 0;
} //end of main
void PeakPickerHiRes::pick(const MSChromatogram& input, MSChromatogram& output, std::vector<PeakBoundary>& boundaries) const
{
// copy meta data of the input chromatogram
output.clear(true);
output.ChromatogramSettings::operator=(input);
output.MetaInfoInterface::operator=(input);
output.setName(input.getName());
MSSpectrum input_spectrum;
MSSpectrum output_spectrum;
for (MSChromatogram::const_iterator it = input.begin(); it != input.end(); ++it)
{
Peak1D p;
p.setMZ(it->getRT());
p.setIntensity(it->getIntensity());
input_spectrum.push_back(p);
}
pick(input_spectrum, output_spectrum, boundaries, false); // no spacing checks!
for (MSSpectrum::const_iterator it = output_spectrum.begin(); it != output_spectrum.end(); ++it)
{
ChromatogramPeak p;
p.setRT(it->getMZ());
p.setIntensity(it->getIntensity());
output.push_back(p);
}
// copy float data arrays (for FWHM)
output.getFloatDataArrays().resize(output_spectrum.getFloatDataArrays().size());
for (Size i = 0; i < output_spectrum.getFloatDataArrays().size(); ++i)
{
output.getFloatDataArrays()[i].insert(output.getFloatDataArrays()[i].begin(), output_spectrum.getFloatDataArrays()[i].begin(), output_spectrum.getFloatDataArrays()[i].end());
output.getFloatDataArrays()[i].setName(output_spectrum.getFloatDataArrays()[i].getName());
}
}
ExitCodes main_(int, const char**)
{
//-------------------------------------------------------------
// parsing parameters
//-------------------------------------------------------------
String in(getStringOption_("in"));
String out(getStringOption_("out"));
String pair_in(getStringOption_("pair_in"));
String feature_out(getStringOption_("feature_out"));
double precursor_mass_tolerance(getDoubleOption_("precursor_mass_tolerance"));
double RT_tolerance(getDoubleOption_("RT_tolerance"));
double expansion_range(getDoubleOption_("expansion_range"));
Size max_isotope(getIntOption_("max_isotope"));
Int debug(getIntOption_("debug"));
//-------------------------------------------------------------
// reading input
//-------------------------------------------------------------
PeakMap exp;
MzMLFile().load(in, exp);
exp.sortSpectra();
exp.updateRanges();
// read pair file
ifstream is(pair_in.c_str());
String line;
vector<SILAC_pair> pairs;
while (getline(is, line))
{
line.trim();
if (line.empty() || line[0] == '#')
{
continue;
}
vector<String> split;
line.split(' ', split);
if (split.size() != 4)
{
cerr << "missformated line ('" << line << "') should be (space separated) 'm/z-light m/z-heavy charge rt'" << endl;
}
SILAC_pair p;
p.mz_light = split[0].toDouble();
p.mz_heavy = split[1].toDouble();
p.charge = split[2].toInt();
p.rt = split[3].toDouble();
pairs.push_back(p);
}
is.close();
//-------------------------------------------------------------
// calculations
//-------------------------------------------------------------
ConsensusMap results_map;
results_map.getFileDescriptions()[0].label = "light";
results_map.getFileDescriptions()[0].filename = in;
results_map.getFileDescriptions()[1].label = "heavy";
results_map.getFileDescriptions()[1].filename = in;
FeatureFinderAlgorithmIsotopeWavelet iso_ff;
Param ff_param(iso_ff.getParameters());
ff_param.setValue("max_charge", 3);
ff_param.setValue("intensity_threshold", -1.0);
iso_ff.setParameters(ff_param);
FeatureFinder ff;
ff.setLogType(ProgressLogger::NONE);
vector<SILACQuantitation> quantlets;
FeatureMap all_features;
for (PeakMap::ConstIterator it = exp.begin(); it != exp.end(); ++it)
{
if (it->size() == 0 || it->getMSLevel() != 1 || !it->getInstrumentSettings().getZoomScan())
{
continue;
}
PeakSpectrum new_spec = *it;
// get spacing from data
double min_spacing(numeric_limits<double>::max());
double last_mz(0);
for (PeakSpectrum::ConstIterator pit = new_spec.begin(); pit != new_spec.end(); ++pit)
{
if (pit->getMZ() - last_mz < min_spacing)
{
min_spacing = pit->getMZ() - last_mz;
}
last_mz = pit->getMZ();
}
writeDebug_("Min-spacing=" + String(min_spacing), 1);
// split the spectrum into two subspectra, by using different hypothesis of
// the SILAC pairs
Size idx = 0;
for (vector<SILAC_pair>::const_iterator pit = pairs.begin(); pit != pairs.end(); ++pit, ++idx)
{
// in RT window?
if (fabs(it->getRT() - pit->rt) >= RT_tolerance)
{
continue;
}
// now excise the two ranges for the pair, complete isotope distributions of both, light and heavy
PeakSpectrum light_spec, heavy_spec;
light_spec.setRT(it->getRT());
heavy_spec.setRT(it->getRT());
for (PeakSpectrum::ConstIterator sit = it->begin(); sit != it->end(); ++sit)
{
double mz(sit->getMZ());
if (mz - (pit->mz_light - precursor_mass_tolerance) > 0 &&
(pit->mz_light + (double)max_isotope * Constants::NEUTRON_MASS_U / (double)pit->charge + precursor_mass_tolerance) - mz > 0)
{
light_spec.push_back(*sit);
}
if (mz - (pit->mz_heavy - precursor_mass_tolerance) > 0 &&
(pit->mz_heavy + (double)max_isotope * Constants::NEUTRON_MASS_U / (double)pit->charge + precursor_mass_tolerance) - mz > 0)
{
heavy_spec.push_back(*sit);
}
}
// expand light spectrum
Peak1D p;
p.setIntensity(0);
if (light_spec.size() > 0)
{
double lower_border = light_spec.begin()->getMZ() - expansion_range;
for (double pos = light_spec.begin()->getMZ(); pos > lower_border; pos -= min_spacing)
{
p.setMZ(pos);
light_spec.insert(light_spec.begin(), p);
}
double upper_border = light_spec.begin()->getMZ() - expansion_range;
for (double pos = light_spec.rbegin()->getMZ(); pos < upper_border; pos += min_spacing)
{
p.setMZ(pos);
light_spec.push_back(p);
}
}
if (heavy_spec.size() > 0)
{
// expand heavy spectrum
double lower_border = heavy_spec.begin()->getMZ() - expansion_range;
for (double pos = heavy_spec.begin()->getMZ(); pos > lower_border; pos -= min_spacing)
{
p.setMZ(pos);
heavy_spec.insert(heavy_spec.begin(), p);
}
double upper_border = heavy_spec.begin()->getMZ() - expansion_range;
for (double pos = heavy_spec.rbegin()->getMZ(); pos < upper_border; pos += min_spacing)
{
p.setMZ(pos);
heavy_spec.push_back(p);
}
}
// create experiments for feature finding
PeakMap new_exp_light, new_exp_heavy;
new_exp_light.addSpectrum(light_spec);
new_exp_heavy.addSpectrum(heavy_spec);
if (debug > 9)
{
MzMLFile().store(String(it->getRT()) + "_debugging_light.mzML", new_exp_light);
MzMLFile().store(String(it->getRT()) + "_debugging_heavy.mzML", new_exp_heavy);
}
writeDebug_("Spectrum-id: " + it->getNativeID() + " @ " + String(it->getRT()) + "s", 1);
new_exp_light.updateRanges();
new_exp_heavy.updateRanges();
FeatureMap feature_map_light, feature_map_heavy, seeds;
if (light_spec.size() > 0)
{
ff.run("isotope_wavelet", new_exp_light, feature_map_light, ff_param, seeds);
}
writeDebug_("#light_features=" + String(feature_map_light.size()), 1);
if (heavy_spec.size() > 0)
{
ff.run("isotope_wavelet", new_exp_heavy, feature_map_heavy, ff_param, seeds);
}
writeDebug_("#heavy_features=" + String(feature_map_heavy.size()), 1);
// search if feature maps to m/z value of pair
vector<MatchedFeature> light, heavy;
for (FeatureMap::const_iterator fit = feature_map_light.begin(); fit != feature_map_light.end(); ++fit)
{
all_features.push_back(*fit);
light.push_back(MatchedFeature(*fit, idx));
}
for (FeatureMap::const_iterator fit = feature_map_heavy.begin(); fit != feature_map_heavy.end(); ++fit)
{
all_features.push_back(*fit);
heavy.push_back(MatchedFeature(*fit, idx));
}
if (!heavy.empty() && !light.empty())
{
writeDebug_("Finding best feature pair out of " + String(light.size()) + " light and " + String(heavy.size()) + " heavy matching features.", 1);
// now find "good" matches, means the pair with the smallest m/z deviation
Feature best_light, best_heavy;
double best_deviation(numeric_limits<double>::max());
Size best_idx(pairs.size());
for (vector<MatchedFeature>::const_iterator fit1 = light.begin(); fit1 != light.end(); ++fit1)
{
for (vector<MatchedFeature>::const_iterator fit2 = heavy.begin(); fit2 != heavy.end(); ++fit2)
{
if (fit1->idx != fit2->idx || fit1->f.getCharge() != fit2->f.getCharge() ||
fabs(fit1->f.getMZ() - pairs[fit1->idx].mz_light) > precursor_mass_tolerance ||
fabs(fit2->f.getMZ() - pairs[fit2->idx].mz_heavy) > precursor_mass_tolerance)
{
continue;
}
double deviation(0);
deviation = fabs((fit1->f.getMZ() - pairs[fit1->idx].mz_light) - (fit2->f.getMZ() - pairs[fit2->idx].mz_heavy));
if (deviation < best_deviation && deviation < precursor_mass_tolerance)
{
best_light = fit1->f;
best_heavy = fit2->f;
best_idx = fit1->idx;
}
}
}
if (best_idx == pairs.size())
{
continue;
}
writeDebug_("Ratio: " + String(best_heavy.getIntensity() / best_light.getIntensity()), 1);
ConsensusFeature SILAC_feature;
SILAC_feature.setMZ((best_light.getMZ() + best_heavy.getMZ()) / 2.0);
SILAC_feature.setRT((best_light.getRT() + best_heavy.getRT()) / 2.0);
SILAC_feature.insert(0, best_light);
SILAC_feature.insert(1, best_heavy);
results_map.push_back(SILAC_feature);
quantlets.push_back(SILACQuantitation(best_light.getIntensity(), best_heavy.getIntensity(), best_idx));
}
}
}
// now calculate the final quantitation values from the quantlets
Map<Size, vector<SILACQuantitation> > idx_to_quantlet;
for (vector<SILACQuantitation>::const_iterator it = quantlets.begin(); it != quantlets.end(); ++it)
{
idx_to_quantlet[it->idx].push_back(*it);
}
for (Map<Size, vector<SILACQuantitation> >::ConstIterator it1 = idx_to_quantlet.begin(); it1 != idx_to_quantlet.end(); ++it1)
{
SILAC_pair silac_pair = pairs[it1->first];
// simply add up all intensities and calculate the final ratio
double light_sum(0), heavy_sum(0);
vector<double> light_ints, heavy_ints, ratios;
for (vector<SILACQuantitation>::const_iterator it2 = it1->second.begin(); it2 != it1->second.end(); ++it2)
{
light_sum += it2->light_intensity;
light_ints.push_back(it2->light_intensity);
heavy_sum += it2->heavy_intensity;
heavy_ints.push_back(it2->heavy_intensity);
ratios.push_back(it2->heavy_intensity / it2->light_intensity * (it2->heavy_intensity + it2->light_intensity));
}
double absdev_ratios = Math::absdev(ratios.begin(), ratios.begin() + (ratios.size()) / (heavy_sum + light_sum));
cout << "Ratio: " << silac_pair.mz_light << " <-> " << silac_pair.mz_heavy << " @ " << silac_pair.rt << " s, ratio(h/l) " << heavy_sum / light_sum << " +/- " << absdev_ratios << " (#scans for quantation: " << String(it1->second.size()) << " )" << endl;
}
//-------------------------------------------------------------
// writing output
//-------------------------------------------------------------
if (feature_out != "")
{
FeatureXMLFile().store(feature_out, all_features);
}
writeDebug_("Writing output", 1);
ConsensusXMLFile().store(out, results_map);
return EXECUTION_OK;
}
ExitCodes main_(int, const char**)
{
//-------------------------------------------------------------
// parameter handling
//-------------------------------------------------------------
StringList in = getStringList_("in");
String edta = getStringOption_("pos");
String out = getStringOption_("out");
String out_sep = getStringOption_("out_separator");
String out_TIC_debug = getStringOption_("auto_rt:out_debug_TIC");
StringList in_header = getStringList_("in_header");
// number of out_debug_TIC files and input files must be identical
/*if (out_TIC_debug.size() > 0 && in.size() != out_TIC_debug.size())
{
LOG_FATAL_ERROR << "Error: number of input file 'in' and auto_rt:out_debug_TIC files must be identical!" << std::endl;
return ILLEGAL_PARAMETERS;
}*/
// number of header files and input files must be identical
if (in_header.size() > 0 && in.size() != in_header.size())
{
LOG_FATAL_ERROR << "Error: number of input file 'in' and 'in_header' files must be identical!" << std::endl;
return ILLEGAL_PARAMETERS;
}
if (!getFlag_("auto_rt:enabled") && !out_TIC_debug.empty())
{
LOG_FATAL_ERROR << "Error: TIC output file requested, but auto_rt is not enabled! Either do not request the file or switch on 'auto_rt:enabled'." << std::endl;
return ILLEGAL_PARAMETERS;
}
double rttol = getDoubleOption_("rt_tol");
double mztol = getDoubleOption_("mz_tol");
Size rt_collect = getIntOption_("rt_collect");
//-------------------------------------------------------------
// loading input
//-------------------------------------------------------------
MzMLFile mzml_file;
mzml_file.setLogType(log_type_);
MSExperiment<Peak1D> exp, exp_pp;
EDTAFile ed;
ConsensusMap cm;
ed.load(edta, cm);
StringList tf_single_header0, tf_single_header1, tf_single_header2; // header content, for each column
std::vector<String> vec_single; // one line for each compound, multiple columns per experiment
vec_single.resize(cm.size());
for (Size fi = 0; fi < in.size(); ++fi)
{
// load raw data
mzml_file.load(in[fi], exp);
exp.sortSpectra(true);
if (exp.empty())
{
LOG_WARN << "The given file does not contain any conventional peak data, but might"
" contain chromatograms. This tool currently cannot handle them, sorry." << std::endl;
return INCOMPATIBLE_INPUT_DATA;
}
// try to detect RT peaks (only for the first input file -- all others should align!)
// cm.size() might change in here...
if (getFlag_("auto_rt:enabled") && fi == 0)
{
ConsensusMap cm_local = cm; // we might have different RT peaks for each map if 'auto_rt' is enabled
cm.clear(false); // reset global list (about to be filled)
// compute TIC
MSChromatogram<> tic = exp.getTIC();
MSSpectrum<> tics, tic_gf, tics_pp, tics_sn;
for (Size ic = 0; ic < tic.size(); ++ic)
{ // rewrite Chromatogram to MSSpectrum (GaussFilter requires it)
Peak1D peak;
peak.setMZ(tic[ic].getRT());
peak.setIntensity(tic[ic].getIntensity());
tics.push_back(peak);
}
// smooth (no PP_CWT here due to efficiency reasons -- large FWHM take longer!)
double fwhm = getDoubleOption_("auto_rt:FHWM");
GaussFilter gf;
Param p = gf.getParameters();
p.setValue("gaussian_width", fwhm * 2); // wider than FWHM, just to be sure we have a fully smoothed peak. Merging two peaks is unlikely
p.setValue("use_ppm_tolerance", "false");
gf.setParameters(p);
tic_gf = tics;
gf.filter(tic_gf);
// pick peaks
PeakPickerHiRes pp;
p = pp.getParameters();
p.setValue("signal_to_noise", getDoubleOption_("auto_rt:SNThreshold"));
pp.setParameters(p);
pp.pick(tic_gf, tics_pp);
if (tics_pp.size())
{
LOG_INFO << "Found " << tics_pp.size() << " auto-rt peaks at: ";
for (Size ipp = 0; ipp != tics_pp.size(); ++ipp) LOG_INFO << " " << tics_pp[ipp].getMZ();
}
else
{
LOG_INFO << "Found no auto-rt peaks. Change threshold parameters!";
}
LOG_INFO << std::endl;
if (!out_TIC_debug.empty()) // if debug file was given
{ // store intermediate steps for debug
MSExperiment<> out_debug;
out_debug.addChromatogram(toChromatogram(tics));
out_debug.addChromatogram(toChromatogram(tic_gf));
SignalToNoiseEstimatorMedian<MSSpectrum<> > snt;
snt.init(tics);
for (Size is = 0; is < tics.size(); ++is)
{
Peak1D peak;
peak.setMZ(tic[is].getMZ());
peak.setIntensity(snt.getSignalToNoise(tics[is]));
tics_sn.push_back(peak);
}
out_debug.addChromatogram(toChromatogram(tics_sn));
out_debug.addChromatogram(toChromatogram(tics_pp));
// get rid of "native-id" missing warning
for (Size id = 0; id < out_debug.size(); ++id) out_debug[id].setNativeID(String("spectrum=") + id);
mzml_file.store(out_TIC_debug, out_debug);
LOG_DEBUG << "Storing debug AUTO-RT: " << out_TIC_debug << std::endl;
}
// add target EICs: for each m/z with no/negative RT, add all combinations of that m/z with auto-RTs
// duplicate m/z entries will be ignored!
// all other lines with positive RT values are copied unaffected
//do not allow doubles
std::set<double> mz_doubles;
for (ConsensusMap::Iterator cit = cm_local.begin(); cit != cm_local.end(); ++cit)
{
if (cit->getRT() < 0)
{
if (mz_doubles.find(cit->getMZ()) == mz_doubles.end())
{
mz_doubles.insert(cit->getMZ());
}
else
{
LOG_INFO << "Found duplicate m/z entry (" << cit->getMZ() << ") for auto-rt. Skipping ..." << std::endl;
continue;
}
ConsensusMap cm_RT_multiplex;
for (MSSpectrum<>::ConstIterator itp = tics_pp.begin(); itp != tics_pp.end(); ++itp)
{
ConsensusFeature f = *cit;
f.setRT(itp->getMZ());
cm.push_back(f);
}
}
else
{ // default feature with no auto-rt
LOG_INFO << "copying feature with RT " << cit->getRT() << std::endl;
cm.push_back(*cit);
}
}
// resize, since we have more positions now
vec_single.resize(cm.size());
}
// search for each EIC and add up
Int not_found(0);
Map<Size, double> quant;
String description;
if (fi < in_header.size())
{
HeaderInfo info(in_header[fi]);
description = info.header_description;
}
if (fi == 0)
{ // two additional columns for first file (theoretical RT and m/z)
tf_single_header0 << "" << "";
tf_single_header1 << "" << "";
tf_single_header2 << "RT" << "mz";
}
// 5 entries for each input file
tf_single_header0 << File::basename(in[fi]) << "" << "" << "" << "";
tf_single_header1 << description << "" << "" << "" << "";
tf_single_header2 << "RTobs" << "dRT" << "mzobs" << "dppm" << "intensity";
for (Size i = 0; i < cm.size(); ++i)
{
//std::cerr << "Rt" << cm[i].getRT() << " mz: " << cm[i].getMZ() << " R " << cm[i].getMetaValue("rank") << "\n";
double mz_da = mztol * cm[i].getMZ() / 1e6; // mz tolerance in Dalton
MSExperiment<>::ConstAreaIterator it = exp.areaBeginConst(cm[i].getRT() - rttol / 2,
cm[i].getRT() + rttol / 2,
cm[i].getMZ() - mz_da,
cm[i].getMZ() + mz_da);
Peak2D max_peak;
max_peak.setIntensity(0);
max_peak.setRT(cm[i].getRT());
max_peak.setMZ(cm[i].getMZ());
for (; it != exp.areaEndConst(); ++it)
{
if (max_peak.getIntensity() < it->getIntensity())
{
max_peak.setIntensity(it->getIntensity());
max_peak.setRT(it.getRT());
max_peak.setMZ(it->getMZ());
}
}
double ppm = 0; // observed m/z offset
if (max_peak.getIntensity() == 0)
{
++not_found;
}
else
{
// take median for m/z found
std::vector<double> mz;
MSExperiment<>::Iterator itm = exp.RTBegin(max_peak.getRT());
SignedSize low = std::min<SignedSize>(std::distance(exp.begin(), itm), rt_collect);
SignedSize high = std::min<SignedSize>(std::distance(itm, exp.end()) - 1, rt_collect);
MSExperiment<>::AreaIterator itt = exp.areaBegin((itm - low)->getRT() - 0.01, (itm + high)->getRT() + 0.01, cm[i].getMZ() - mz_da, cm[i].getMZ() + mz_da);
for (; itt != exp.areaEnd(); ++itt)
{
mz.push_back(itt->getMZ());
//std::cerr << "ppm: " << itt.getRT() << " " << itt->getMZ() << " " << itt->getIntensity() << std::endl;
}
if ((SignedSize)mz.size() > (low + high + 1)) LOG_WARN << "Compound " << i << " has overlapping peaks [" << mz.size() << "/" << low + high + 1 << "]" << std::endl;
if (!mz.empty())
{
double avg_mz = std::accumulate(mz.begin(), mz.end(), 0.0) / double(mz.size());
//std::cerr << "avg: " << avg_mz << "\n";
ppm = (avg_mz - cm[i].getMZ()) / cm[i].getMZ() * 1e6;
}
}
// appending the second column set requires separator
String append_sep = (fi == 0 ? "" : out_sep);
vec_single[i] += append_sep; // new line
if (fi == 0)
{
vec_single[i] += String(cm[i].getRT()) + out_sep +
String(cm[i].getMZ()) + out_sep;
}
vec_single[i] += String(max_peak.getRT()) + out_sep +
String(max_peak.getRT() - cm[i].getRT()) + out_sep +
String(max_peak.getMZ()) + out_sep +
String(ppm) + out_sep +
String(max_peak.getIntensity());
}
if (not_found) LOG_INFO << "Missing peaks for " << not_found << " compounds in file '" << in[fi] << "'.\n";
}
//-------------------------------------------------------------
// create header
//-------------------------------------------------------------
vec_single.insert(vec_single.begin(), ListUtils::concatenate(tf_single_header2, out_sep));
vec_single.insert(vec_single.begin(), ListUtils::concatenate(tf_single_header1, out_sep));
vec_single.insert(vec_single.begin(), ListUtils::concatenate(tf_single_header0, out_sep));
//-------------------------------------------------------------
// writing output
//-------------------------------------------------------------
TextFile tf;
for (std::vector<String>::iterator v_it = vec_single.begin(); v_it != vec_single.end(); ++v_it)
{
tf.addLine(*v_it);
}
tf.store(out);
return EXECUTION_OK;
}
ExitCodes main_(int, const char**)
{
//-------------------------------------------------------------
// parameter handling
//-------------------------------------------------------------
StringList in_spec = getStringList_("in");
StringList out = getStringList_("out");
String in_lib = getStringOption_("lib");
String compare_function = getStringOption_("compare_function");
Int precursor_mass_multiplier = getIntOption_("round_precursor_to_integer");
float precursor_mass_tolerance = getDoubleOption_("precursor_mass_tolerance");
//Int min_precursor_charge = getIntOption_("min_precursor_charge");
//Int max_precursor_charge = getIntOption_("max_precursor_charge");
float remove_peaks_below_threshold = getDoubleOption_("filter:remove_peaks_below_threshold");
UInt min_peaks = getIntOption_("filter:min_peaks");
UInt max_peaks = getIntOption_("filter:max_peaks");
Int cut_peaks_below = getIntOption_("filter:cut_peaks_below");
StringList fixed_modifications = getStringList_("fixed_modifications");
StringList variable_modifications = getStringList_("variable_modifications");
Int top_hits = getIntOption_("top_hits");
if (top_hits < -1)
{
writeLog_("top_hits (should be >= -1 )");
return ILLEGAL_PARAMETERS;
}
//-------------------------------------------------------------
// loading input
//-------------------------------------------------------------
if (out.size() != in_spec.size())
{
writeLog_("out (should be as many as input files)");
return ILLEGAL_PARAMETERS;
}
time_t prog_time = time(NULL);
MSPFile spectral_library;
RichPeakMap query, library;
//spectrum which will be identified
MzMLFile spectra;
spectra.setLogType(log_type_);
time_t start_build_time = time(NULL);
//-------------------------------------------------------------
//building map for faster search
//-------------------------------------------------------------
//library containing already identified peptide spectra
vector<PeptideIdentification> ids;
spectral_library.load(in_lib, ids, library);
map<Size, vector<PeakSpectrum> > MSLibrary;
{
RichPeakMap::iterator s;
vector<PeptideIdentification>::iterator i;
ModificationsDB* mdb = ModificationsDB::getInstance();
for (s = library.begin(), i = ids.begin(); s < library.end(); ++s, ++i)
{
double precursor_MZ = (*s).getPrecursors()[0].getMZ();
Size MZ_multi = (Size)precursor_MZ * precursor_mass_multiplier;
map<Size, vector<PeakSpectrum> >::iterator found;
found = MSLibrary.find(MZ_multi);
PeakSpectrum librar;
bool variable_modifications_ok = true;
bool fixed_modifications_ok = true;
const AASequence& aaseq = i->getHits()[0].getSequence();
//variable fixed modifications
if (!fixed_modifications.empty())
{
for (Size i = 0; i < aaseq.size(); ++i)
{
const Residue& mod = aaseq.getResidue(i);
for (Size s = 0; s < fixed_modifications.size(); ++s)
{
if (mod.getOneLetterCode() == mdb->getModification(fixed_modifications[s]).getOrigin() && fixed_modifications[s] != mod.getModification())
{
fixed_modifications_ok = false;
break;
}
}
}
}
//variable modifications
if (aaseq.isModified() && (!variable_modifications.empty()))
{
for (Size i = 0; i < aaseq.size(); ++i)
{
if (aaseq.isModified(i))
{
const Residue& mod = aaseq.getResidue(i);
for (Size s = 0; s < variable_modifications.size(); ++s)
{
if (mod.getOneLetterCode() == mdb->getModification(variable_modifications[s]).getOrigin() && variable_modifications[s] != mod.getModification())
{
variable_modifications_ok = false;
break;
}
}
}
}
}
if (variable_modifications_ok && fixed_modifications_ok)
{
PeptideIdentification& translocate_pid = *i;
librar.getPeptideIdentifications().push_back(translocate_pid);
librar.setPrecursors(s->getPrecursors());
//library entry transformation
for (UInt l = 0; l < s->size(); ++l)
{
Peak1D peak;
if ((*s)[l].getIntensity() > remove_peaks_below_threshold)
{
const String& info = (*s)[l].getMetaValue("MSPPeakInfo");
if (info[0] == '?')
{
peak.setIntensity(sqrt(0.2 * (*s)[l].getIntensity()));
}
else
{
peak.setIntensity(sqrt((*s)[l].getIntensity()));
}
peak.setMZ((*s)[l].getMZ());
peak.setPosition((*s)[l].getPosition());
librar.push_back(peak);
}
}
if (found != MSLibrary.end())
{
found->second.push_back(librar);
}
else
{
vector<PeakSpectrum> tmp;
tmp.push_back(librar);
MSLibrary.insert(make_pair(MZ_multi, tmp));
}
}
}
}
time_t end_build_time = time(NULL);
cout << "Time needed for preprocessing data: " << (end_build_time - start_build_time) << "\n";
//compare function
PeakSpectrumCompareFunctor* comparor = Factory<PeakSpectrumCompareFunctor>::create(compare_function);
//-------------------------------------------------------------
// calculations
//-------------------------------------------------------------
double score;
StringList::iterator in, out_file;
for (in = in_spec.begin(), out_file = out.begin(); in < in_spec.end(); ++in, ++out_file)
{
time_t start_time = time(NULL);
spectra.load(*in, query);
//Will hold valuable hits
vector<PeptideIdentification> peptide_ids;
vector<ProteinIdentification> protein_ids;
// Write parameters to ProteinIdentifcation
ProteinIdentification prot_id;
//Parameters of identificaion
prot_id.setIdentifier("test");
prot_id.setSearchEngineVersion("SpecLibSearcher");
prot_id.setDateTime(DateTime::now());
prot_id.setScoreType(compare_function);
ProteinIdentification::SearchParameters searchparam;
searchparam.precursor_tolerance = precursor_mass_tolerance;
prot_id.setSearchParameters(searchparam);
/***********SEARCH**********/
for (UInt j = 0; j < query.size(); ++j)
{
//Set identifier for each identifications
PeptideIdentification pid;
pid.setIdentifier("test");
pid.setScoreType(compare_function);
ProteinHit pr_hit;
pr_hit.setAccession(j);
prot_id.insertHit(pr_hit);
//RichPeak1D to Peak1D transformation for the compare function query
PeakSpectrum quer;
bool peak_ok = true;
query[j].sortByIntensity(true);
double min_high_intensity = 0;
if (query[j].empty() || query[j].getMSLevel() != 2)
{
continue;
}
if (query[j].getPrecursors().empty())
{
writeLog_("Warning MS2 spectrum without precursor information");
continue;
}
min_high_intensity = (1 / cut_peaks_below) * query[j][0].getIntensity();
query[j].sortByPosition();
for (UInt k = 0; k < query[j].size() && k < max_peaks; ++k)
{
if (query[j][k].getIntensity() > remove_peaks_below_threshold && query[j][k].getIntensity() >= min_high_intensity)
{
Peak1D peak;
peak.setIntensity(sqrt(query[j][k].getIntensity()));
peak.setMZ(query[j][k].getMZ());
peak.setPosition(query[j][k].getPosition());
quer.push_back(peak);
}
}
if (quer.size() >= min_peaks)
{
peak_ok = true;
}
else
{
peak_ok = false;
}
double query_MZ = query[j].getPrecursors()[0].getMZ();
if (peak_ok)
{
bool charge_one = false;
Int percent = (Int) Math::round((query[j].size() / 100.0) * 3.0);
Int margin = (Int) Math::round((query[j].size() / 100.0) * 1.0);
for (vector<RichPeak1D>::iterator peak = query[j].end() - 1; percent >= 0; --peak, --percent)
{
if (peak->getMZ() < query_MZ)
{
break;
}
}
if (percent > margin)
{
charge_one = true;
}
float min_MZ = (query_MZ - precursor_mass_tolerance) * precursor_mass_multiplier;
float max_MZ = (query_MZ + precursor_mass_tolerance) * precursor_mass_multiplier;
for (Size mz = (Size)min_MZ; mz <= ((Size)max_MZ) + 1; ++mz)
{
map<Size, vector<PeakSpectrum> >::iterator found;
found = MSLibrary.find(mz);
if (found != MSLibrary.end())
{
vector<PeakSpectrum>& library = found->second;
for (Size i = 0; i < library.size(); ++i)
{
float this_MZ = library[i].getPrecursors()[0].getMZ() * precursor_mass_multiplier;
if (this_MZ >= min_MZ && max_MZ >= this_MZ && ((charge_one == true && library[i].getPeptideIdentifications()[0].getHits()[0].getCharge() == 1) || charge_one == false))
{
PeptideHit hit = library[i].getPeptideIdentifications()[0].getHits()[0];
PeakSpectrum& librar = library[i];
//Special treatment for SpectraST score as it computes a score based on the whole library
if (compare_function == "SpectraSTSimilarityScore")
{
SpectraSTSimilarityScore* sp = static_cast<SpectraSTSimilarityScore*>(comparor);
BinnedSpectrum quer_bin = sp->transform(quer);
BinnedSpectrum librar_bin = sp->transform(librar);
score = (*sp)(quer, librar); //(*sp)(quer_bin,librar_bin);
double dot_bias = sp->dot_bias(quer_bin, librar_bin, score);
hit.setMetaValue("DOTBIAS", dot_bias);
}
else
{
score = (*comparor)(quer, librar);
}
DataValue RT(library[i].getRT());
DataValue MZ(library[i].getPrecursors()[0].getMZ());
hit.setMetaValue("RT", RT);
hit.setMetaValue("MZ", MZ);
hit.setScore(score);
PeptideEvidence pe;
pe.setProteinAccession(pr_hit.getAccession());
hit.addPeptideEvidence(pe);
pid.insertHit(hit);
}
}
}
}
}
pid.setHigherScoreBetter(true);
pid.sort();
if (compare_function == "SpectraSTSimilarityScore")
{
if (!pid.empty() && !pid.getHits().empty())
{
vector<PeptideHit> final_hits;
final_hits.resize(pid.getHits().size());
SpectraSTSimilarityScore* sp = static_cast<SpectraSTSimilarityScore*>(comparor);
Size runner_up = 1;
for (; runner_up < pid.getHits().size(); ++runner_up)
{
if (pid.getHits()[0].getSequence().toUnmodifiedString() != pid.getHits()[runner_up].getSequence().toUnmodifiedString() || runner_up > 5)
{
break;
}
}
double delta_D = sp->delta_D(pid.getHits()[0].getScore(), pid.getHits()[runner_up].getScore());
for (Size s = 0; s < pid.getHits().size(); ++s)
{
final_hits[s] = pid.getHits()[s];
final_hits[s].setMetaValue("delta D", delta_D);
final_hits[s].setMetaValue("dot product", pid.getHits()[s].getScore());
final_hits[s].setScore(sp->compute_F(pid.getHits()[s].getScore(), delta_D, pid.getHits()[s].getMetaValue("DOTBIAS")));
//final_hits[s].removeMetaValue("DOTBIAS");
}
pid.setHits(final_hits);
pid.sort();
pid.setMZ(query[j].getPrecursors()[0].getMZ());
pid.setRT(query_MZ);
}
}
if (top_hits != -1 && (UInt)top_hits < pid.getHits().size())
{
vector<PeptideHit> hits;
hits.resize(top_hits);
for (Size i = 0; i < (UInt)top_hits; ++i)
{
hits[i] = pid.getHits()[i];
}
pid.setHits(hits);
}
peptide_ids.push_back(pid);
}
protein_ids.push_back(prot_id);
//-------------------------------------------------------------
// writing output
//-------------------------------------------------------------
IdXMLFile id_xml_file;
id_xml_file.store(*out_file, protein_ids, peptide_ids);
time_t end_time = time(NULL);
cout << "Search time: " << difftime(end_time, start_time) << " seconds for " << *in << "\n";
}
time_t end_time = time(NULL);
cout << "Total time: " << difftime(end_time, prog_time) << " secconds\n";
return EXECUTION_OK;
}
void PeakPickerHiRes::pick(const MSSpectrum& input, MSSpectrum& output, std::vector<PeakBoundary>& boundaries, bool check_spacings) const
{
// copy meta data of the input spectrum
output.clear(true);
output.SpectrumSettings::operator=(input);
output.MetaInfoInterface::operator=(input);
output.setRT(input.getRT());
output.setMSLevel(input.getMSLevel());
output.setName(input.getName());
output.setType(SpectrumSettings::CENTROID);
if (report_FWHM_)
{
output.getFloatDataArrays().resize(1);
output.getFloatDataArrays()[0].setName( report_FWHM_as_ppm_ ? "FWHM_ppm" : "FWHM");
}
// don't pick a spectrum with less than 5 data points
if (input.size() < 5) return;
// if both spacing constraints are disabled, don't check spacings at all:
if ((spacing_difference_ == std::numeric_limits<double>::infinity()) &&
(spacing_difference_gap_ == std::numeric_limits<double>::infinity()))
{
check_spacings = false;
}
// signal-to-noise estimation
SignalToNoiseEstimatorMedian<MSSpectrum > snt;
snt.setParameters(param_.copy("SignalToNoise:", true));
if (signal_to_noise_ > 0.0)
{
snt.init(input);
}
// find local maxima in profile data
for (Size i = 2; i < input.size() - 2; ++i)
{
double central_peak_mz = input[i].getMZ(), central_peak_int = input[i].getIntensity();
double left_neighbor_mz = input[i - 1].getMZ(), left_neighbor_int = input[i - 1].getIntensity();
double right_neighbor_mz = input[i + 1].getMZ(), right_neighbor_int = input[i + 1].getIntensity();
// do not interpolate when the left or right support is a zero-data-point
if (std::fabs(left_neighbor_int) < std::numeric_limits<double>::epsilon()) continue;
if (std::fabs(right_neighbor_int) < std::numeric_limits<double>::epsilon()) continue;
// MZ spacing sanity checks
double left_to_central = 0.0, central_to_right = 0.0, min_spacing = 0.0;
if (check_spacings)
{
left_to_central = central_peak_mz - left_neighbor_mz;
central_to_right = right_neighbor_mz - central_peak_mz;
min_spacing = (left_to_central < central_to_right) ? left_to_central : central_to_right;
}
double act_snt = 0.0, act_snt_l1 = 0.0, act_snt_r1 = 0.0;
if (signal_to_noise_ > 0.0)
{
act_snt = snt.getSignalToNoise(input[i]);
act_snt_l1 = snt.getSignalToNoise(input[i - 1]);
act_snt_r1 = snt.getSignalToNoise(input[i + 1]);
}
// look for peak cores meeting MZ and intensity/SNT criteria
if ((central_peak_int > left_neighbor_int) &&
(central_peak_int > right_neighbor_int) &&
(act_snt >= signal_to_noise_) &&
(act_snt_l1 >= signal_to_noise_) &&
(act_snt_r1 >= signal_to_noise_) &&
(!check_spacings ||
((left_to_central < spacing_difference_ * min_spacing) &&
(central_to_right < spacing_difference_ * min_spacing))))
{
// special case: if a peak core is surrounded by more intense
// satellite peaks (indicates oscillation rather than
// real peaks) -> remove
double act_snt_l2 = 0.0, act_snt_r2 = 0.0;
if (signal_to_noise_ > 0.0)
{
act_snt_l2 = snt.getSignalToNoise(input[i - 2]);
act_snt_r2 = snt.getSignalToNoise(input[i + 2]);
}
// checking signal-to-noise?
if ((i > 1) &&
(i + 2 < input.size()) &&
(left_neighbor_int < input[i - 2].getIntensity()) &&
(right_neighbor_int < input[i + 2].getIntensity()) &&
(act_snt_l2 >= signal_to_noise_) &&
(act_snt_r2 >= signal_to_noise_) &&
(!check_spacings ||
((left_neighbor_mz - input[i - 2].getMZ() < spacing_difference_ * min_spacing) &&
(input[i + 2].getMZ() - right_neighbor_mz < spacing_difference_ * min_spacing))))
{
++i;
continue;
}
std::map<double, double> peak_raw_data;
peak_raw_data[central_peak_mz] = central_peak_int;
peak_raw_data[left_neighbor_mz] = left_neighbor_int;
peak_raw_data[right_neighbor_mz] = right_neighbor_int;
// peak core found, now extend it
// to the left
Size k = 2;
bool previous_zero_left(false); // no need to extend peak if previous intensity was zero
Size missing_left(0);
Size left_boundary(i - 1); // index of the left boundary for the spline interpolation
while ((k <= i) && // prevent underflow
(i - k + 1 > 0) &&
!previous_zero_left &&
(missing_left <= missing_) &&
(input[i - k].getIntensity() <= peak_raw_data.begin()->second) &&
(!check_spacings ||
(peak_raw_data.begin()->first - input[i - k].getMZ() < spacing_difference_gap_ * min_spacing)))
{
double act_snt_lk = 0.0;
if (signal_to_noise_ > 0.0)
{
act_snt_lk = snt.getSignalToNoise(input[i - k]);
}
if ((act_snt_lk >= signal_to_noise_) &&
(!check_spacings ||
(peak_raw_data.begin()->first - input[i - k].getMZ() < spacing_difference_ * min_spacing)))
{
peak_raw_data[input[i - k].getMZ()] = input[i - k].getIntensity();
}
else
{
++missing_left;
if (missing_left <= missing_)
{
peak_raw_data[input[i - k].getMZ()] = input[i - k].getIntensity();
}
}
previous_zero_left = (input[i - k].getIntensity() == 0);
left_boundary = i - k;
++k;
}
// to the right
k = 2;
bool previous_zero_right(false); // no need to extend peak if previous intensity was zero
Size missing_right(0);
Size right_boundary(i+1); // index of the right boundary for the spline interpolation
while ((i + k < input.size()) &&
!previous_zero_right &&
(missing_right <= missing_) &&
(input[i + k].getIntensity() <= peak_raw_data.rbegin()->second) &&
(!check_spacings ||
(input[i + k].getMZ() - peak_raw_data.rbegin()->first < spacing_difference_gap_ * min_spacing)))
{
double act_snt_rk = 0.0;
if (signal_to_noise_ > 0.0)
{
act_snt_rk = snt.getSignalToNoise(input[i + k]);
}
if ((act_snt_rk >= signal_to_noise_) &&
(!check_spacings ||
(input[i + k].getMZ() - peak_raw_data.rbegin()->first < spacing_difference_ * min_spacing)))
{
peak_raw_data[input[i + k].getMZ()] = input[i + k].getIntensity();
}
else
{
++missing_right;
if (missing_right <= missing_)
{
peak_raw_data[input[i + k].getMZ()] = input[i + k].getIntensity();
}
}
previous_zero_right = (input[i + k].getIntensity() == 0);
right_boundary = i + k;
++k;
}
// skip if the minimal number of 3 points for fitting is not reached
if (peak_raw_data.size() < 3) continue;
CubicSpline2d peak_spline (peak_raw_data);
// calculate maximum by evaluating the spline's 1st derivative
// (bisection method)
double max_peak_mz = central_peak_mz;
double max_peak_int = central_peak_int;
double threshold = 1e-6;
OpenMS::Math::spline_bisection(peak_spline, left_neighbor_mz, right_neighbor_mz, max_peak_mz, max_peak_int, threshold);
//
// compute FWHM
//
if (report_FWHM_)
{
double fwhm_int = max_peak_int / 2.0;
threshold = 0.01 * fwhm_int;
double mz_mid, int_mid;
// left:
double mz_left = peak_raw_data.begin()->first;
double mz_center = max_peak_mz;
if (peak_spline.eval(mz_left) > fwhm_int)
{ // the spline ends before half max is reached -- take the leftmost point (probably an underestimation)
mz_mid = mz_left;
}
else
{
do
{
mz_mid = mz_left / 2 + mz_center / 2;
int_mid = peak_spline.eval(mz_mid);
if (int_mid < fwhm_int)
{
mz_left = mz_mid;
}
else
{
mz_center = mz_mid;
}
} while (fabs(int_mid - fwhm_int) > threshold);
}
const double fwhm_left_mz = mz_mid;
// right ...
double mz_right = peak_raw_data.rbegin()->first;
mz_center = max_peak_mz;
if (peak_spline.eval(mz_right) > fwhm_int)
{ // the spline ends before half max is reached -- take the rightmost point (probably an underestimation)
mz_mid = mz_right;
}
else
{
do
{
mz_mid = mz_right / 2 + mz_center / 2;
int_mid = peak_spline.eval(mz_mid);
if (int_mid < fwhm_int)
{
mz_right = mz_mid;
}
else
{
mz_center = mz_mid;
}
} while (fabs(int_mid - fwhm_int) > threshold);
}
const double fwhm_right_mz = mz_mid;
const double fwhm_absolute = fwhm_right_mz - fwhm_left_mz;
output.getFloatDataArrays()[0].push_back( report_FWHM_as_ppm_ ? fwhm_absolute / max_peak_mz * 1e6 : fwhm_absolute);
} // FWHM
// save picked peak into output spectrum
Peak1D peak;
PeakBoundary peak_boundary;
peak.setMZ(max_peak_mz);
peak.setIntensity(max_peak_int);
peak_boundary.mz_min = input[left_boundary].getMZ();
peak_boundary.mz_max = input[right_boundary].getMZ();
output.push_back(peak);
boundaries.push_back(peak_boundary);
// jump over profile data points that have been considered already
i = i + k - 1;
}
}
return;
}