void IDMapper::getIDDetails_(const PeptideIdentification & id, DoubleReal & rt_pep, DoubleList & mz_values, IntList & charges, bool use_avg_mass) const
{
mz_values.clear();
charges.clear();
rt_pep = id.getMetaValue("RT");
// collect m/z values of pepId
if (param_.getValue("mz_reference") == "precursor") // use precursor m/z of pepId
{
mz_values.push_back(id.getMetaValue("MZ"));
}
for (vector<PeptideHit>::const_iterator hit_it = id.getHits().begin();
hit_it != id.getHits().end(); ++hit_it)
{
Int charge = hit_it->getCharge();
charges.push_back(charge);
if (param_.getValue("mz_reference") == "peptide") // use mass of each pepHit (assuming H+ adducts)
{
DoubleReal mass = use_avg_mass ?
hit_it->getSequence().getAverageWeight(Residue::Full, charge) :
hit_it->getSequence().getMonoWeight(Residue::Full, charge);
mz_values.push_back( mass / (DoubleReal) charge);
}
}
}
//Visualizing PeptideIdentification object
void MetaDataBrowser::visualize_(PeptideIdentification & meta, QTreeWidgetItem * parent)
{
PeptideIdentificationVisualizer * visualizer = new PeptideIdentificationVisualizer(isEditable(), this, this);
QStringList labels;
int id = ws_->addWidget(visualizer);
labels << QString("PeptideIdentification %1").arg(meta.getScoreType().c_str()) << QString::number(id);
visualizer->load(meta, id);
QTreeWidgetItem * item;
if (parent == nullptr)
{
item = new QTreeWidgetItem(treeview_, labels);
}
else
{
item = new QTreeWidgetItem(parent, labels);
}
//check for proteins and peptides hits
meta.assignRanks();
//list all peptides hits in the tree
for (Size i = 0; i < meta.getHits().size(); ++i)
{
visualize_(const_cast<PeptideHit &>(meta.getHits()[i]), item);
}
visualize_(dynamic_cast<MetaInfoInterface &>(meta), item);
connectVisualizer_(visualizer);
}
bool IDFilter::filterIdentificationsByMetaValueRange(const PeptideIdentification& identification, const String& key, DoubleReal low, DoubleReal high, bool missing)
{
if (!identification.metaValueExists(key)) return missing;
DoubleReal value = identification.getMetaValue(key);
return (value >= low) && (value <= high);
}
void IDFilter::filterIdentificationsByCharge(const PeptideIdentification& identification,
Int min_charge,
PeptideIdentification& filtered_identification)
{
vector<Size> new_peptide_indices;
vector<PeptideHit> filtered_peptide_hits;
filtered_identification = identification;
filtered_identification.setHits(vector<PeptideHit>());
const vector<PeptideHit>& temp_peptide_hits = identification.getHits();
for (Size i = 0; i < temp_peptide_hits.size(); i++)
{
if (temp_peptide_hits[i].getCharge() >= min_charge)
{
new_peptide_indices.push_back(i);
}
}
for (Size i = 0; i < new_peptide_indices.size(); i++)
{
filtered_peptide_hits.push_back(identification.getHits()[new_peptide_indices[i]]);
}
if (!filtered_peptide_hits.empty())
{
filtered_identification.setHits(filtered_peptide_hits);
filtered_identification.assignRanks();
}
}
void IDFilter::filterIdentificationsByMzError(const PeptideIdentification& identification, DoubleReal mass_error, bool unit_ppm, PeptideIdentification& filtered_identification)
{
vector<PeptideHit> hits;
filtered_identification = identification;
vector<PeptideHit> temp_hits = identification.getHits();
for (vector<PeptideHit>::iterator it = temp_hits.begin(); it != temp_hits.end(); ++it)
{
Int charge = it->getCharge();
if (charge == 0)
{
charge = 1;
}
DoubleReal exp_mz = (DoubleReal)identification.getMetaValue("MZ");
DoubleReal theo_mz = (it->getSequence().getMonoWeight() + (DoubleReal)charge * Constants::PROTON_MASS_U) / (DoubleReal)charge;
DoubleReal error(exp_mz - theo_mz);
if (unit_ppm)
{
error = error / theo_mz * (DoubleReal)1e6;
}
if (fabs(error) <= mass_error)
{
hits.push_back(*it);
}
}
filtered_identification.setHits(hits);
}
void CompNovoIdentificationCID::getIdentifications(vector<PeptideIdentification> & pep_ids, const PeakMap & exp)
{
Size count(1);
for (PeakMap::ConstIterator it = exp.begin(); it != exp.end(); ++it, ++count)
{
//cerr << count << "/" << exp.size() << endl;
PeptideIdentification id;
// TODO check if both CID and ETD is present;
PeakSpectrum CID_spec(*it);
id.setRT(it->getRT());
id.setMZ(it->getPrecursors().begin()->getMZ());
subspec_to_sequences_.clear();
permute_cache_.clear();
decomp_cache_.clear();
getIdentification(id, CID_spec);
//cerr << "size_of id=" << id.getHits().size() << endl;
pep_ids.push_back(id);
//++it;
//
//if (count == 10)
//{
//return;
//}
}
return;
}
// Equality operator
bool PeptideIdentification::operator==(const PeptideIdentification & rhs) const
{
return MetaInfoInterface::operator==(rhs)
&& id_ == rhs.id_
&& hits_ == rhs.getHits()
&& significance_threshold_ == rhs.getSignificanceThreshold()
&& score_type_ == rhs.score_type_
&& higher_score_better_ == rhs.higher_score_better_;
}
// compare peptide IDs by score of best hit (hits must be sorted first!)
// (note to self: the "static" is necessary to avoid cryptic "no matching
// function" errors from gcc when the comparator is used below)
static bool compareIDs_(const PeptideIdentification & left,
const PeptideIdentification & right)
{
if (left.getHits()[0].getScore() < right.getHits()[0].getScore())
{
return true;
}
return false;
}
// Equality operator
bool PeptideIdentification::operator==(const PeptideIdentification& rhs) const
{
return MetaInfoInterface::operator==(rhs)
&& id_ == rhs.id_
&& (rt_ == rhs.rt_ || (!this->hasRT() && !rhs.hasRT())) // might be NaN, so comparing == will always be false
&& (mz_ == rhs.mz_ || (!this->hasMZ() && !rhs.hasMZ())) // might be NaN, so comparing == will always be false
&& hits_ == rhs.getHits()
&& significance_threshold_ == rhs.getSignificanceThreshold()
&& score_type_ == rhs.score_type_
&& higher_score_better_ == rhs.higher_score_better_
&& base_name_ == rhs.base_name_;
}
// list of peptide hits in "peptide" will be sorted
bool MapAlignmentAlgorithmIdentification::hasGoodHit_(PeptideIdentification &
peptide)
{
if (peptide.empty() || peptide.getHits().empty())
return false;
peptide.sort();
DoubleReal score = peptide.getHits().begin()->getScore();
if (peptide.isHigherScoreBetter())
return score >= score_threshold_;
return score <= score_threshold_;
}
void IDFilter::filterIdentificationsByBestHits(const PeptideIdentification& identification,
PeptideIdentification& filtered_identification,
bool strict)
{
vector<PeptideHit> filtered_peptide_hits;
PeptideHit temp_peptide_hit;
vector<Size> new_peptide_indices;
filtered_identification = identification;
filtered_identification.setHits(vector<PeptideHit>());
if (!identification.getHits().empty())
{
Real optimal_value = identification.getHits()[0].getScore();
new_peptide_indices.push_back(0);
// searching for peptide(s) with maximal score
for (Size i = 1; i < identification.getHits().size(); i++)
{
Real temp_score = identification.getHits()[i].getScore();
bool new_leader = false;
if ((identification.isHigherScoreBetter() && (temp_score > optimal_value))
|| (!identification.isHigherScoreBetter() && (temp_score < optimal_value)))
new_leader = true;
if (new_leader)
{
optimal_value = temp_score;
new_peptide_indices.clear();
new_peptide_indices.push_back(i);
}
else if (temp_score == optimal_value)
{
new_peptide_indices.push_back(i);
}
}
if (!strict || new_peptide_indices.size() == 1)
{
for (Size i = 0; i < new_peptide_indices.size(); i++)
{
filtered_peptide_hits.push_back(identification.getHits()[new_peptide_indices[i]]);
}
}
}
if (!filtered_peptide_hits.empty())
{
filtered_identification.setHits(filtered_peptide_hits);
filtered_identification.assignRanks();
}
}
void IDFilter::filterIdentificationsByProteins(const PeptideIdentification& identification,
const vector<FASTAFile::FASTAEntry>& proteins,
PeptideIdentification& filtered_identification,
bool no_protein_identifiers)
{
// TODO: this is highly inefficient! the Protein-Index should be build once for all peptide-identifications instead of
// doing this once for every ID. Furthermore the index itself is inefficient (use seqan instead)
String protein_sequences;
String accession_sequences;
vector<PeptideHit> filtered_peptide_hits;
PeptideHit temp_peptide_hit;
filtered_identification = identification;
filtered_identification.setHits(vector<PeptideHit>());
for (Size i = 0; i < proteins.size(); i++)
{
if (proteins[i].identifier != "")
{
accession_sequences.append("*" + proteins[i].identifier);
}
if (proteins[i].sequence != "")
{
protein_sequences.append("*" + proteins[i].sequence);
}
}
accession_sequences.append("*");
protein_sequences.append("*");
for (Size i = 0; i < identification.getHits().size(); i++)
{
if (no_protein_identifiers || accession_sequences == "*") // filter by sequence alone if no protein accesssions are available
{
if (protein_sequences.find(identification.getHits()[i].getSequence().toUnmodifiedString()) != String::npos)
{
filtered_peptide_hits.push_back(identification.getHits()[i]);
}
}
else // filter by protein accessions
{
for (vector<String>::const_iterator ac_it = identification.getHits()[i].getProteinAccessions().begin();
ac_it != identification.getHits()[i].getProteinAccessions().end();
++ac_it)
{
if (accession_sequences.find("*" + *ac_it) != String::npos)
{
filtered_peptide_hits.push_back(identification.getHits()[i]);
break; // we found a matching protein, the peptide is valid -> exit
}
}
}
}
filtered_identification.setHits(filtered_peptide_hits);
filtered_identification.assignRanks();
}
std::vector<PeptideIdentification> toPepVec(const QStringList& sl_pep)
{
std::vector<PeptideIdentification> pep_vec;
for (Size i = 0; i < sl_pep.size(); ++i)
{
PeptideHit hit;
hit.setSequence(AASequence::fromString(sl_pep[int(i)]));
std::vector<PeptideHit> hits;
hits.push_back(hit);
PeptideIdentification pi;
pi.setHits(hits);
pep_vec.push_back(pi);
}
return pep_vec;
}
void IDFilter::filterIdentificationsByRTPValues(const PeptideIdentification& identification,
PeptideIdentification& filtered_identification,
DoubleReal p_value)
{
DoubleReal border = 1 - p_value;
vector<PeptideHit> filtered_peptide_hits;
PeptideHit temp_peptide_hit;
filtered_identification = identification;
filtered_identification.setHits(vector<PeptideHit>());
Size missing_meta_value = 0;
for (Size i = 0; i < identification.getHits().size(); i++)
{
if (identification.getHits()[i].metaValueExists("predicted_RT_p_value"))
{
if ((DoubleReal)(identification.getHits()[i].getMetaValue("predicted_RT_p_value")) <= border)
{
filtered_peptide_hits.push_back(identification.getHits()[i]);
}
}
else
++missing_meta_value;
}
if (missing_meta_value > 0)
LOG_WARN << "Filtering identifications by p-value did not work on " << missing_meta_value << " of " << identification.getHits().size() << " hits. Your data is missing a meta-value ('predicted_RT_p_value') from RTPredict!\n";
if (!filtered_peptide_hits.empty())
{
filtered_identification.setHits(filtered_peptide_hits);
filtered_identification.assignRanks();
}
}
void IDFilter::filterIdentificationsByCharge(const PeptideIdentification& identification,
Int min_charge,
PeptideIdentification& filtered_identification)
{
filtered_identification = identification;
const vector<PeptideHit>& temp_peptide_hits = identification.getHits();
vector<PeptideHit> filtered_peptide_hits;
for (Size i = 0; i < temp_peptide_hits.size(); ++i)
{
if (temp_peptide_hits[i].getCharge() >= min_charge)
{
filtered_peptide_hits.push_back(temp_peptide_hits[i]);
}
}
filtered_identification.setHits(filtered_peptide_hits);
filtered_identification.assignRanks();
}
void IDFilter::filterIdentificationsUnique(const PeptideIdentification& identification,
PeptideIdentification& filtered_identification)
{
vector<PeptideHit> hits;
filtered_identification = identification;
vector<PeptideHit> temp_hits = identification.getHits();
for (vector<PeptideHit>::iterator it = temp_hits.begin();
it != temp_hits.end();
++it)
{
if (find(hits.begin(), hits.end(), *it) == hits.end())
{
hits.push_back(*it);
}
}
filtered_identification.setHits(hits);
}
void IDFilter::filterIdentificationsUnique(const PeptideIdentification& identification,
PeptideIdentification& filtered_identification)
{
// there's no "PeptideHit::operator<" defined, so we can't use a set nor
// "sort" + "unique" from the standard library
vector<PeptideHit> hits;
filtered_identification = identification;
vector<PeptideHit> temp_hits = identification.getHits();
for (vector<PeptideHit>::iterator it = temp_hits.begin();
it != temp_hits.end();
++it)
{
if (find(hits.begin(), hits.end(), *it) == hits.end())
{
hits.push_back(*it);
}
}
filtered_identification.setHits(hits);
}
void IDFilter::filterIdentificationsByExclusionPeptides(const PeptideIdentification& identification,
const set<String>& peptides,
PeptideIdentification& filtered_identification)
{
String protein_sequences;
String accession_sequences;
vector<PeptideHit> filtered_peptide_hits;
PeptideHit temp_peptide_hit;
filtered_identification = identification;
filtered_identification.setHits(vector<PeptideHit>());
for (Size i = 0; i < identification.getHits().size(); i++)
{
if (find(peptides.begin(), peptides.end(), identification.getHits()[i].getSequence().toString()) == peptides.end())
{
filtered_peptide_hits.push_back(identification.getHits()[i]);
}
}
if (!filtered_peptide_hits.empty())
{
filtered_identification.setHits(filtered_peptide_hits);
filtered_identification.assignRanks();
}
}
void IDRipper::getProteinIdentification_(ProteinIdentification & result, PeptideIdentification pep_ident, std::vector<ProteinIdentification> & prot_idents)
{
const String & identifier = pep_ident.getIdentifier();
for (vector<ProteinIdentification>::iterator prot_it = prot_idents.begin(); prot_it != prot_idents.end(); ++prot_it)
{
if (identifier.compare(prot_it->getIdentifier()) == 0)
{
result = *prot_it;
break;
}
}
}
void IDFilter::filterIdentificationsByLength(const PeptideIdentification& identification,
PeptideIdentification& filtered_identification,
Size min_length,
Size max_length)
{
vector<Size> new_peptide_indices;
vector<PeptideHit> filtered_peptide_hits;
filtered_identification = identification;
filtered_identification.setHits(vector<PeptideHit>());
Size ml = max_length;
if (max_length < min_length)
{
ml = UINT_MAX;
}
const vector<PeptideHit>& temp_peptide_hits = identification.getHits();
for (Size i = 0; i < temp_peptide_hits.size(); i++)
{
if (temp_peptide_hits[i].getSequence().size() >= min_length && temp_peptide_hits[i].getSequence().size() <= ml)
{
new_peptide_indices.push_back(i);
}
}
for (Size i = 0; i < new_peptide_indices.size(); i++)
{
filtered_peptide_hits.push_back(identification.getHits()[new_peptide_indices[i]]);
}
if (!filtered_peptide_hits.empty())
{
filtered_identification.setHits(filtered_peptide_hits);
filtered_identification.assignRanks();
}
}
void IDFilter::filterIdentificationsByLength(const PeptideIdentification& identification,
PeptideIdentification& filtered_identification,
Size min_length,
Size max_length)
{
filtered_identification = identification;
if (max_length < min_length)
{
max_length = UINT_MAX;
}
const vector<PeptideHit>& temp_peptide_hits = identification.getHits();
vector<PeptideHit> filtered_peptide_hits;
for (Size i = 0; i < temp_peptide_hits.size(); ++i)
{
if (min_length <= temp_peptide_hits[i].getSequence().size() && temp_peptide_hits[i].getSequence().size() <= max_length)
{
filtered_peptide_hits.push_back(temp_peptide_hits[i]);
}
}
filtered_identification.setHits(filtered_peptide_hits);
filtered_identification.assignRanks();
}
// static
bool IDConflictResolverAlgorithm::compareIDsSmallerScores_(const PeptideIdentification & left, const PeptideIdentification & right)
{
// if any of them is empty, the other is considered "greater"
// independent of the score in the first hit
if (left.getHits().empty() || right.getHits().empty())
{ // also: for strict weak ordering, comp(x,x) needs to be false
return left.getHits().size() < right.getHits().size();
}
if (left.getHits()[0].getScore() < right.getHits()[0].getScore())
{
return true;
}
return false;
}
void IDFilter::filterIdentificationsByExclusionPeptides(const PeptideIdentification& identification,
const set<String>& peptides,
bool ignore_modifications,
PeptideIdentification& filtered_identification)
{
vector<PeptideHit> filtered_peptide_hits;
filtered_identification = identification;
filtered_identification.setHits(vector<PeptideHit>());
for (Size i = 0; i < identification.getHits().size(); i++)
{
String query = ignore_modifications ? identification.getHits()[i].getSequence().toUnmodifiedString() : identification.getHits()[i].getSequence().toString();
if (find(peptides.begin(), peptides.end(), query) == peptides.end())
{
filtered_peptide_hits.push_back(identification.getHits()[i]);
}
}
if (!filtered_peptide_hits.empty())
{
filtered_identification.setHits(filtered_peptide_hits);
filtered_identification.assignRanks();
}
}
void CompNovoIdentificationCID::getIdentification(PeptideIdentification & id, const PeakSpectrum & CID_spec)
{
//if (CID_spec.getPrecursors().begin()->getMZ() > 1000.0)
//{
//cerr << "Weight of precursor has been estimated to exceed 2000.0 Da which is the current limit" << endl;
//return;
//}
PeakSpectrum new_CID_spec(CID_spec);
windowMower_(new_CID_spec, 0.3, 1);
Param zhang_param;
zhang_param = zhang_.getParameters();
zhang_param.setValue("tolerance", fragment_mass_tolerance_);
zhang_param.setValue("use_gaussian_factor", "true");
zhang_param.setValue("use_linear_factor", "false");
zhang_.setParameters(zhang_param);
Normalizer normalizer;
Param n_param(normalizer.getParameters());
n_param.setValue("method", "to_one");
normalizer.setParameters(n_param);
normalizer.filterSpectrum(new_CID_spec);
Size charge(2);
double precursor_weight(0); // [M+H]+
if (!CID_spec.getPrecursors().empty())
{
// believe charge of spectrum?
if (CID_spec.getPrecursors().begin()->getCharge() != 0)
{
charge = CID_spec.getPrecursors().begin()->getCharge();
}
else
{
// TODO estimate charge state
}
precursor_weight = CID_spec.getPrecursors().begin()->getMZ() * charge - ((charge - 1) * Constants::PROTON_MASS_U);
}
//cerr << "charge=" << charge << ", [M+H]=" << precursor_weight << endl;
// now delete all peaks that are right of the estimated precursor weight
Size peak_counter(0);
for (PeakSpectrum::ConstIterator it = new_CID_spec.begin(); it != new_CID_spec.end(); ++it, ++peak_counter)
{
if (it->getPosition()[0] > precursor_weight)
{
break;
}
}
if (peak_counter < new_CID_spec.size())
{
new_CID_spec.resize(peak_counter);
}
static double oxonium_mass = EmpiricalFormula("H2O+").getMonoWeight();
Peak1D p;
p.setIntensity(1);
p.setPosition(oxonium_mass);
new_CID_spec.push_back(p);
p.setPosition(precursor_weight);
new_CID_spec.push_back(p);
// add complement to spectrum
/*
for (PeakSpectrum::ConstIterator it1 = CID_spec.begin(); it1 != CID_spec.end(); ++it1)
{
// get m/z of complement
double mz_comp = precursor_weight - it1->getPosition()[0] + Constants::PROTON_MASS_U;
// search if peaks are available that have similar m/z values
Size count(0);
bool found(false);
for (PeakSpectrum::ConstIterator it2 = CID_spec.begin(); it2 != CID_spec.end(); ++it2, ++count)
{
if (fabs(mz_comp - it2->getPosition()[0]) < fragment_mass_tolerance)
{
// add peak intensity to corresponding peak in new_CID_spec
new_CID_spec[count].setIntensity(new_CID_spec[count].getIntensity());
}
}
if (!found)
{
// infer this peak
Peak1D p;
p.setIntensity(it1->getIntensity());
p.setPosition(mz_comp);
new_CID_spec.push_back(p);
}
}*/
CompNovoIonScoringCID ion_scoring;
Param ion_scoring_param(ion_scoring.getParameters());
ion_scoring_param.setValue("fragment_mass_tolerance", fragment_mass_tolerance_);
ion_scoring_param.setValue("precursor_mass_tolerance", precursor_mass_tolerance_);
ion_scoring_param.setValue("decomp_weights_precision", decomp_weights_precision_);
ion_scoring_param.setValue("double_charged_iso_threshold", (double)param_.getValue("double_charged_iso_threshold"));
ion_scoring_param.setValue("max_isotope_to_score", param_.getValue("max_isotope_to_score"));
ion_scoring_param.setValue("max_isotope", max_isotope_);
ion_scoring.setParameters(ion_scoring_param);
Map<double, IonScore> ion_scores;
ion_scoring.scoreSpectrum(ion_scores, new_CID_spec, precursor_weight, charge);
new_CID_spec.sortByPosition();
/*
cerr << "Size of ion_scores " << ion_scores.size() << endl;
for (Map<double, IonScore>::const_iterator it = ion_scores.begin(); it != ion_scores.end(); ++it)
{
cerr << it->first << " " << it->second.score << endl;
}*/
#ifdef WRITE_SCORED_SPEC
PeakSpectrum filtered_spec(new_CID_spec);
filtered_spec.clear();
for (Map<double, CompNovoIonScoringCID::IonScore>::const_iterator it = ion_scores.begin(); it != ion_scores.end(); ++it)
{
Peak1D p;
p.setIntensity(it->second.score);
p.setPosition(it->first);
filtered_spec.push_back(p);
}
DTAFile().store("spec_scored.dta", filtered_spec);
#endif
set<String> sequences;
getDecompositionsDAC_(sequences, 0, new_CID_spec.size() - 1, precursor_weight, new_CID_spec, ion_scores);
#ifdef SPIKE_IN
sequences.insert("AFCVDGEGR");
sequences.insert("APEFAAPWPDFVPR");
sequences.insert("AVKQFEESQGR");
sequences.insert("CCTESLVNR");
sequences.insert("DAFLGSFLYEYSR");
sequences.insert("DAIPENLPPLTADFAEDK");
sequences.insert("DDNKVEDIWSFLSK");
sequences.insert("DDPHACYSTVFDK");
sequences.insert("DEYELLCLDGSR");
sequences.insert("DGAESYKELSVLLPNR");
sequences.insert("DGASCWCVDADGR");
sequences.insert("DLFIPTCLETGEFAR");
sequences.insert("DTHKSEIAHR");
sequences.insert("DVCKNYQEAK");
sequences.insert("EACFAVEGPK");
sequences.insert("ECCHGDLLECADDR");
sequences.insert("EFLGDKFYTVISSLK");
sequences.insert("EFTPVLQADFQK");
sequences.insert("ELFLDSGIFQPMLQGR");
sequences.insert("ETYGDMADCCEK");
sequences.insert("EVGCPSSSVQEMVSCLR");
sequences.insert("EYEATLEECCAK");
sequences.insert("FADLIQSGTFQLHLDSK");
sequences.insert("FFSASCVPGATIEQK");
sequences.insert("FLANVSTVLTSK");
sequences.insert("FLSGSDYAIR");
sequences.insert("FTASCPPSIK");
sequences.insert("GAIEWEGIESGSVEQAVAK");
sequences.insert("GDVAFIQHSTVEENTGGK");
sequences.insert("GEPPSCAEDQSCPSER");
sequences.insert("GEYVPTSLTAR");
sequences.insert("GQEFTITGQKR");
sequences.insert("GTFAALSELHCDK");
sequences.insert("HLVDEPQNLIK");
sequences.insert("HQDCLVTTLQTQPGAVR");
sequences.insert("HTTVNENAPDQK");
sequences.insert("ILDCGSPDTEVR");
sequences.insert("KCPSPCQLQAER");
sequences.insert("KGTEFTVNDLQGK");
sequences.insert("KQTALVELLK");
sequences.insert("KVPQVSTPTLVEVSR");
sequences.insert("LALQFTTNAKR");
sequences.insert("LCVLHEKTPVSEK");
sequences.insert("LFTFHADICTLPDTEK");
sequences.insert("LGEYGFQNALIVR");
sequences.insert("LHVDPENFK");
sequences.insert("LKECCDKPLLEK");
sequences.insert("LKHLVDEPQNLIK");
sequences.insert("LKPDPNTLCDEFK");
sequences.insert("LLGNVLVVVLAR");
sequences.insert("LLVVYPWTQR");
sequences.insert("LRVDPVNFK");
sequences.insert("LTDEELAFPPLSPSR");
sequences.insert("LVNELTEFAK");
sequences.insert("MFLSFPTTK");
sequences.insert("MPCTEDYLSLILNR");
sequences.insert("NAPYSGYSGAFHCLK");
sequences.insert("NECFLSHKDDSPDLPK");
sequences.insert("NEPNKVPACPGSCEEVK");
sequences.insert("NLQMDDFELLCTDGR");
sequences.insert("QAGVQAEPSPK");
sequences.insert("RAPEFAAPWPDFVPR");
sequences.insert("RHPEYAVSVLLR");
sequences.insert("RPCFSALTPDETYVPK");
sequences.insert("RSLLLAPEEGPVSQR");
sequences.insert("SAFPPEPLLCSVQR");
sequences.insert("SAGWNIPIGTLLHR");
sequences.insert("SCWCVDEAGQK");
sequences.insert("SGNPNYPHEFSR");
sequences.insert("SHCIAEVEK");
sequences.insert("SISSGFFECER");
sequences.insert("SKYLASASTMDHAR");
sequences.insert("SLHTLFGDELCK");
sequences.insert("SLLLAPEEGPVSQR");
sequences.insert("SPPQCSPDGAFRPVQCK");
sequences.insert("SREGDPLAVYLK");
sequences.insert("SRQIPQCPTSCER");
sequences.insert("TAGTPVSIPVCDDSSVK");
sequences.insert("TCVADESHAGCEK");
sequences.insert("TQFGCLEGFGR");
sequences.insert("TVMENFVAFVDK");
sequences.insert("TYFPHFDLSHGSAQVK");
sequences.insert("TYMLAFDVNDEK");
sequences.insert("VDEVGGEALGR");
sequences.insert("VDLLIGSSQDDGLINR");
sequences.insert("VEDIWSFLSK");
sequences.insert("VGGHAAEYGAEALER");
sequences.insert("VGTRCCTKPESER");
sequences.insert("VKVDEVGGEALGR");
sequences.insert("VKVDLLIGSSQDDGLINR");
sequences.insert("VLDSFSNGMK");
sequences.insert("VLSAADKGNVK");
sequences.insert("VPQVSTPTLVEVSR");
sequences.insert("VTKCCTESLVNR");
sequences.insert("VVAASDASQDALGCVK");
sequences.insert("VVAGVANALAHR");
sequences.insert("YICDNQDTISSK");
sequences.insert("YLASASTMDHAR");
sequences.insert("YNGVFQECCQAEDK");
#endif
SpectrumAlignmentScore spectra_zhang;
spectra_zhang.setParameters(zhang_param);
vector<PeptideHit> hits;
Size missed_cleavages = param_.getValue("missed_cleavages");
for (set<String>::const_iterator it = sequences.begin(); it != sequences.end(); ++it)
{
Size num_missed = countMissedCleavagesTryptic_(*it);
if (missed_cleavages < num_missed)
{
//cerr << "Two many missed cleavages: " << *it << ", found " << num_missed << ", allowed " << missed_cleavages << endl;
continue;
}
PeakSpectrum CID_sim_spec;
getCIDSpectrum_(CID_sim_spec, *it, charge);
//normalizer.filterSpectrum(CID_sim_spec);
double cid_score = zhang_(CID_sim_spec, CID_spec);
PeptideHit hit;
hit.setScore(cid_score);
hit.setSequence(getModifiedAASequence_(*it));
hit.setCharge((Int)charge); //TODO unify charge interface: int or size?
hits.push_back(hit);
//cerr << getModifiedAASequence_(*it) << " " << cid_score << " " << endl;
}
// rescore the top hits
id.setHits(hits);
id.assignRanks();
hits = id.getHits();
SpectrumAlignmentScore alignment_score;
Param align_param(alignment_score.getParameters());
align_param.setValue("tolerance", fragment_mass_tolerance_);
align_param.setValue("use_linear_factor", "true");
alignment_score.setParameters(align_param);
for (vector<PeptideHit>::iterator it = hits.begin(); it != hits.end(); ++it)
{
//cerr << "Pre: " << it->getRank() << " " << it->getSequence() << " " << it->getScore() << " " << endl;
}
Size number_of_prescoring_hits = param_.getValue("number_of_prescoring_hits");
if (hits.size() > number_of_prescoring_hits)
{
hits.resize(number_of_prescoring_hits);
}
for (vector<PeptideHit>::iterator it = hits.begin(); it != hits.end(); ++it)
{
PeakSpectrum CID_sim_spec;
getCIDSpectrum_(CID_sim_spec, getModifiedStringFromAASequence_(it->getSequence()), charge);
normalizer.filterSpectrum(CID_sim_spec);
//DTAFile().store("sim_specs/" + it->getSequence().toUnmodifiedString() + "_sim_CID.dta", CID_sim_spec);
//double cid_score = spectra_zhang(CID_sim_spec, CID_spec);
double cid_score = alignment_score(CID_sim_spec, CID_spec);
//cerr << "Final: " << it->getSequence() << " " << cid_score << endl;
it->setScore(cid_score);
}
id.setHits(hits);
id.assignRanks();
hits = id.getHits();
for (vector<PeptideHit>::iterator it = hits.begin(); it != hits.end(); ++it)
{
//cerr << "Fin: " << it->getRank() << " " << it->getSequence() << " " << it->getScore() << " " << endl;
}
Size number_of_hits = param_.getValue("number_of_hits");
if (id.getHits().size() > number_of_hits)
{
hits.resize(number_of_hits);
}
id.setHits(hits);
id.assignRanks();
return;
}
///////////////////////////
START_TEST(IDFilter, "$Id$")
/////////////////////////////////////////////////////////////
/////////////////////////////////////////////////////////////
using namespace OpenMS;
using namespace std;
///load input data
std::vector<ProteinIdentification> protein_identifications;
std::vector<PeptideIdentification> identifications;
String document_id;
IdXMLFile().load(OPENMS_GET_TEST_DATA_PATH("IDFilter_test.idXML"), protein_identifications, identifications, document_id);
PeptideIdentification identification = identifications[0];
ProteinIdentification protein_identification = protein_identifications[0];
/// Proteins for search
vector<FASTAFile::FASTAEntry> proteins;
proteins.push_back(FASTAFile::FASTAEntry("Q824A5", "test description 1", "LHASGITVTEIPVTATNFK"));
proteins.push_back(FASTAFile::FASTAEntry("Q872T5", "test description 2", "THPYGHAIVAGIERYPSK"));
IDFilter* ptr = 0;
IDFilter* nullPointer = 0;
START_SECTION((IDFilter()))
ptr = new IDFilter();
TEST_NOT_EQUAL(ptr, nullPointer);
END_SECTION
ExitCodes main_(int, const char **)
{
//-------------------------------------------------------------
// parameter handling
//-------------------------------------------------------------
//input/output files
String in(getStringOption_("in"));
String out(getStringOption_("out"));
//-------------------------------------------------------------
// loading input
//-------------------------------------------------------------
RichPeakMap exp;
MzMLFile f;
f.setLogType(log_type_);
f.load(in, exp);
writeDebug_("Data set contains " + String(exp.size()) + " spectra", 1);
//-------------------------------------------------------------
// calculations
//-------------------------------------------------------------
writeDebug_("Reading model file", 2);
// create model an set the given options
PILISModel * model = new PILISModel();
model->readFromFile(getStringOption_("model_file"));
Param model_param(model->getParameters());
model_param.setValue("upper_mz", getDoubleOption_("model:upper_mz"));
model_param.setValue("lower_mz", getDoubleOption_("model:lower_mz"));
model_param.setValue("charge_directed_threshold", getDoubleOption_("model:charge_directed_threshold"));
model_param.setValue("charge_remote_threshold", getDoubleOption_("model:charge_remote_threshold"));
//model_param.setValue("min_main_ion_intensity", getDoubleOption_("model:min_main_ion_intensity"));
//model_param.setValue("min_loss_ion_intensity", getDoubleOption_("model:min_loss_ion_intensity"));
model_param.setValue("min_y_ion_intensity", getDoubleOption_("model:min_y_ion_intensity"));
model_param.setValue("min_b_ion_intensity", getDoubleOption_("model:min_b_ion_intensity"));
model_param.setValue("min_a_ion_intensity", getDoubleOption_("model:min_a_ion_intensity"));
model_param.setValue("min_y_loss_intensity", getDoubleOption_("model:min_y_loss_intensity"));
model_param.setValue("min_b_loss_intensity", getDoubleOption_("model:min_b_loss_intensity"));
model_param.setValue("charge_loss_factor", getDoubleOption_("model:charge_loss_factor"));
model_param.setValue("visible_model_depth", getIntOption_("model:visible_model_depth"));
model_param.setValue("model_depth", getIntOption_("model:model_depth"));
model_param.setValue("fixed_modifications", getStringOption_("fixed_modifications"));
model->setParameters(model_param);
writeDebug_("Reading sequence db", 2);
// create sequence db
SuffixArrayPeptideFinder * sapf = new SuffixArrayPeptideFinder(getStringOption_("peptide_db_file"), "trypticCompressed");
sapf->setTolerance(getDoubleOption_("precursor_mass_tolerance"));
sapf->setNumberOfModifications(0);
sapf->setUseTags(false);
//exp.resize(50); // TODO
UInt max_charge(3), min_charge(1); // TODO
vector<double> pre_weights;
for (RichPeakMap::Iterator it = exp.begin(); it != exp.end(); ++it)
{
double pre_weight(it->getPrecursors()[0].getMZ());
for (Size z = min_charge; z <= max_charge; ++z)
{
pre_weights.push_back((pre_weight * (double)z) - (double)z);
}
}
sort(pre_weights.begin(), pre_weights.end());
cerr << "Getting candidates from SA...";
vector<vector<pair<pair<String, String>, String> > > candidates;
sapf->getCandidates(candidates, pre_weights);
cerr << "done" << endl;
delete sapf;
map<double, vector<pair<pair<String, String>, String> > > sorted_candidates;
UInt count(0);
for (Size count = 0; count != candidates.size(); ++count)
{
sorted_candidates[pre_weights[count]] = candidates[count];
}
candidates.clear();
// create ProteinIdentification and set the options
PILISIdentification PILIS_id;
PILIS_id.setModel(model);
Param id_param(PILIS_id.getParameters());
id_param.setValue("precursor_mass_tolerance", getDoubleOption_("precursor_mass_tolerance"));
id_param.setValue("max_candidates", getIntOption_("max_pre_candidates"));
// disable evalue scoring, this is done separately to allow for a single id per spectrum
id_param.setValue("use_evalue_scoring", 0);
id_param.setValue("fixed_modifications", getStringOption_("fixed_modifications"));
PILIS_id.setParameters(id_param);
vector<PeptideIdentification> ids;
// perform the ProteinIdentification of the given spectra
UInt no(0);
for (RichPeakMap::Iterator it = exp.begin(); it != exp.end(); ++it, ++no)
{
if (it->getMSLevel() == 0)
{
writeLog_("Warning: MSLevel is 0, assuming MSLevel 2");
it->setMSLevel(2);
}
if (it->getMSLevel() == 2)
{
writeDebug_(String(no) + "/" + String(exp.size()), 1);
PeptideIdentification id;
map<String, UInt> cand;
for (UInt z = min_charge; z <= max_charge; ++z)
{
double pre_weight = (it->getPrecursors()[0].getMZ() * (double)z) - (double)z;
for (vector<pair<pair<String, String>, String> >::const_iterator cit = sorted_candidates[pre_weight].begin(); cit != sorted_candidates[pre_weight].end(); ++cit)
{
String seq = cit->first.second;
if (seq.size() > 39)
{
continue;
}
UInt num_cleavages_sites(0);
for (Size k = 0; k != seq.size(); ++k)
{
if (k != seq.size() - 1)
{
if ((seq[k] == 'K' || seq[k] == 'R') && seq[k + 1] != 'P')
{
++num_cleavages_sites;
}
}
}
if (num_cleavages_sites > 1)
{
continue;
}
cand[seq] = z;
}
}
cerr << "#cand=" << cand.size() << endl;
PILIS_id.getIdentification(cand, id, *it);
id.setMetaValue("RT", it->getRT());
id.setMetaValue("MZ", it->getPrecursors()[0].getMZ());
ids.push_back(id);
if (!id.getHits().empty())
{
cerr << it->getPrecursors()[0].getMZ() << " " << AASequence(id.getHits().begin()->getSequence()).getAverageWeight() << endl;
writeDebug_(id.getHits().begin()->getSequence().toString() + " (z=" + id.getHits().begin()->getCharge() + "), score=" + String(id.getHits().begin()->getScore()), 10);
}
}
}
// perform the PILIS scoring to the spectra
if (!getFlag_("scoring:do_not_use_evalue_scoring"))
{
PILISScoring scoring;
Param scoring_param(scoring.getParameters());
scoring_param.setValue("use_local_scoring", (int)getFlag_("scoring:use_local_scoring"));
scoring_param.setValue("survival_function_bin_size", getIntOption_("scoring:survival_function_bin_size"));
scoring_param.setValue("global_linear_fitting_threshold", getDoubleOption_("scoring:global_linear_fitting_threshold"));
scoring_param.setValue("local_linear_fitting_threshold", getDoubleOption_("scoring:local_linear_fitting_threshold"));
scoring.setParameters(scoring_param);
scoring.getScores(ids);
}
// write the result to the IdentificationData structure for the storing
UInt max_candidates = getIntOption_("max_candidates");
for (Size i = 0; i != ids.size(); ++i)
{
if (ids[i].getHits().size() > max_candidates)
{
vector<PeptideHit> hits = ids[i].getHits();
hits.resize(max_candidates);
ids[i].setHits(hits);
}
}
delete model;
//-------------------------------------------------------------
// writing output
//-------------------------------------------------------------
DateTime now;
now.now();
String date_string;
//now.get(date_string); // @todo Fix it (Andreas)
String identifier("PILIS_" + date_string);
//UInt count(0);
count = 0;
for (RichPeakMap::ConstIterator it = exp.begin(); it != exp.end(); ++it)
{
if (it->getMSLevel() == 2)
{
ids[count].setMetaValue("RT", it->getRT());
ids[count].setMetaValue("MZ", it->getPrecursors()[0].getMZ());
ids[count].setIdentifier(identifier);
ids[count++].setHigherScoreBetter(false);
}
}
// search parameters
ProteinIdentification::SearchParameters search_parameters;
search_parameters.db = getStringOption_("peptide_db_file");
search_parameters.db_version = "";
search_parameters.taxonomy = "";
//search_parameters.charges = getStringOption_("charges");
search_parameters.mass_type = ProteinIdentification::MONOISOTOPIC;
vector<String> fixed_mods;
getStringOption_("fixed_modifications").split(',', fixed_mods);
search_parameters.fixed_modifications = fixed_mods;
search_parameters.enzyme = ProteinIdentification::TRYPSIN;
search_parameters.missed_cleavages = 1;
search_parameters.peak_mass_tolerance = getDoubleOption_("peak_mass_tolerance");
search_parameters.precursor_tolerance = getDoubleOption_("precursor_mass_tolerance");
ProteinIdentification protein_identification;
protein_identification.setDateTime(now);
protein_identification.setSearchEngine("PILIS");
protein_identification.setSearchEngineVersion("beta");
protein_identification.setSearchParameters(search_parameters);
protein_identification.setIdentifier(identifier);
vector<ProteinIdentification> protein_identifications;
protein_identifications.push_back(protein_identification);
IdXMLFile().store(out, protein_identifications, ids);
return EXECUTION_OK;
}
END_SECTION
START_SECTION(void load(const String &filename, ProteinIdentification &protein_ids, PeptideIdentification &peptide_ids))
{
ProtXMLFile f;
ProteinIdentification proteins;
PeptideIdentification peptides;
String prot_file;
StringList ids = ListUtils::create<String>("16627578304933075941,13229490167902618598");
// we do this twice, just to check that members are correctly reset etc..
for (Int i=0;i<2;++i)
{
prot_file = OPENMS_GET_TEST_DATA_PATH("ProtXMLFile_input_1.protXML");
f.load(prot_file, proteins, peptides);
TEST_EQUAL(proteins.getIdentifier(), ids[i]);
TEST_EQUAL(peptides.getIdentifier(), ids[i]);
// groups
TEST_EQUAL(proteins.getProteinGroups().size(), 7);
TEST_EQUAL(proteins.getProteinGroups()[0].probability, 0.9990);
TEST_EQUAL(proteins.getProteinGroups()[0].accessions.size(), 1);
TEST_EQUAL(proteins.getProteinGroups()[3].accessions.size(), 2);
TEST_EQUAL(proteins.getProteinGroups()[3].accessions[0],
"P01876|IGHA1_HUMAN");
TEST_EQUAL(proteins.getProteinGroups()[3].accessions[1],
"P01877|IGHA2_HUMAN");
TEST_EQUAL(proteins.getProteinGroups()[6].probability, 0.2026);
TEST_EQUAL(proteins.getProteinGroups()[6].accessions.size(), 1);
TEST_EQUAL(proteins.getIndistinguishableProteins().size(), 7);
TEST_EQUAL(proteins.getIndistinguishableProteins()[0].accessions.size(), 1);
TEST_EQUAL(proteins.getIndistinguishableProteins()[3].accessions.size(), 2);
TEST_EQUAL(proteins.getIndistinguishableProteins()[3].accessions[0],
"P01876|IGHA1_HUMAN");
TEST_EQUAL(proteins.getIndistinguishableProteins()[3].accessions[1],
"P01877|IGHA2_HUMAN");
TEST_EQUAL(proteins.getIndistinguishableProteins()[6].accessions.size(), 1);
// proteins
TEST_EQUAL(proteins.getHits().size(), 9);
TEST_EQUAL(proteins.getHits()[0].getAccession(), "P02787|TRFE_HUMAN");
TEST_EQUAL(proteins.getHits()[0].getCoverage(), 8.6);
TEST_EQUAL(proteins.getHits()[0].getScore(), 0.9990);
// this one is indistinguishable... therefore it should have minimal infos
TEST_EQUAL(proteins.getHits()[6].getAccession(), "P00739|HPTR_HUMAN");
TEST_EQUAL(proteins.getHits()[6].getCoverage(), -1);
TEST_EQUAL(proteins.getHits()[6].getScore(), -1);
TEST_EQUAL(proteins.getHits()[8].getAccession(), "P04217|A1BG_HUMAN");
TEST_EQUAL(proteins.getHits()[8].getCoverage(), 2.0);
TEST_EQUAL(proteins.getHits()[8].getScore(), 0.2026);
// peptides
TEST_EQUAL(peptides.getHits().size(), 16);
AASequence aa_seq("MYLGYEYVTAIR");
TEST_EQUAL(peptides.getHits()[0].getSequence(), aa_seq);
TEST_EQUAL(peptides.getHits()[0].getCharge(), 2);
TEST_EQUAL(peptides.getHits()[0].getScore(), 0.8633);
TEST_EQUAL(peptides.getHits()[0].getProteinAccessions().size(), 1);
TEST_EQUAL(peptides.getHits()[0].getProteinAccessions()[0], "P02787|TRFE_HUMAN");
TEST_EQUAL(peptides.getHits()[0].getMetaValue("is_unique"), true);
TEST_EQUAL(peptides.getHits()[0].getMetaValue("is_contributing"), true);
// load 2 nd file and
prot_file = OPENMS_GET_TEST_DATA_PATH("ProtXMLFile_input_2.protXML");
}
}
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 IDFilter::filterIdentificationsByVariableModifications(const PeptideIdentification& identification,
const vector<String>& fixed_modifications,
PeptideIdentification& filtered_identification)
{
vector<Size> new_peptide_indices;
vector<PeptideHit> filtered_peptide_hits;
filtered_identification = identification;
filtered_identification.setHits(vector<PeptideHit>());
const vector<PeptideHit>& temp_peptide_hits = identification.getHits();
for (Size i = 0; i < temp_peptide_hits.size(); i++)
{
const AASequence& aa_seq = temp_peptide_hits[i].getSequence();
/*
TODO: check these cases
// check terminal modifications
if (aa_seq.hasNTerminalModification())
{
String unimod_name = aa_seq.getNTerminalModification();
if (find(fixed_modifications.begin(), fixed_modifications.end(), unimod_name) == fixed_modifications.end())
{
new_peptide_indices.push_back(i);
continue;
}
}
if (aa_seq.hasCTerminalModification())
{
String unimod_name = aa_seq.getCTerminalModification();
if (find(fixed_modifications.begin(), fixed_modifications.end(), unimod_name) == fixed_modifications.end())
{
new_peptide_indices.push_back(i);
continue;
}
}
*/
// check internal modifications
for (Size j = 0; j != aa_seq.size(); ++j)
{
if (aa_seq[j].isModified())
{
String unimod_name = aa_seq[j].getModification() + " (" + aa_seq[j].getOneLetterCode() + ")";
if (find(fixed_modifications.begin(), fixed_modifications.end(), unimod_name) == fixed_modifications.end())
{
new_peptide_indices.push_back(i);
continue;
}
}
}
}
for (Size i = 0; i < new_peptide_indices.size(); i++)
{
const PeptideHit& ph = temp_peptide_hits[new_peptide_indices[i]];
filtered_peptide_hits.push_back(ph);
}
if (!filtered_peptide_hits.empty())
{
filtered_identification.setHits(filtered_peptide_hits);
filtered_identification.assignRanks();
}
}
void IDDecoyProbability::apply_(vector<PeptideIdentification> & ids, const vector<double> & rev_scores, const vector<double> & fwd_scores, const vector<double> & all_scores)
{
Size number_of_bins(param_.getValue("number_of_bins"));
// normalize distribution to [0, 1]
vector<double> fwd_scores_normalized(number_of_bins, 0.0), rev_scores_normalized(number_of_bins, 0.0), diff_scores(number_of_bins, 0.0), all_scores_normalized(number_of_bins, 0.0);
Transformation_ rev_trafo, fwd_trafo, all_trafo;
normalizeBins_(rev_scores, rev_scores_normalized, rev_trafo);
normalizeBins_(fwd_scores, fwd_scores_normalized, fwd_trafo);
normalizeBins_(all_scores, all_scores_normalized, all_trafo);
// rev scores fitting
vector<DPosition<2> > rev_data;
for (Size i = 0; i < number_of_bins; ++i)
{
DPosition<2> pos;
pos.setX(((double)i) / (double)number_of_bins + 0.0001); // necessary????
pos.setY(rev_scores_normalized[i]);
rev_data.push_back(pos);
#ifdef IDDECOYPROBABILITY_DEBUG
cerr << pos.getX() << " " << pos.getY() << endl;
#endif
}
Math::GammaDistributionFitter gdf;
Math::GammaDistributionFitter::GammaDistributionFitResult result_gamma_1st (1.0, 3.0);
gdf.setInitialParameters(result_gamma_1st);
// TODO heuristic for good start parameters
Math::GammaDistributionFitter::GammaDistributionFitResult result_gamma = gdf.fit(rev_data);
#ifdef IDDECOYPROBABILITY_DEBUG
cerr << gdf.getGnuplotFormula() << endl;
String rev_filename = param_.getValue("rev_filename");
generateDistributionImage_(rev_scores_normalized, gdf.getGnuplotFormula(), rev_filename);
#endif
// generate diffs of distributions
// get the fwd and rev distribution, apply all_trafo and calculate the diff
vector<Size> fwd_bins(number_of_bins, 0), rev_bins(number_of_bins, 0);
double min(all_trafo.min_score), diff(all_trafo.diff_score);
Size max_bin(0);
for (vector<double>::const_iterator it = fwd_scores.begin(); it != fwd_scores.end(); ++it)
{
Size bin = (Size)((*it - min) / diff * (double)(number_of_bins - 1));
++fwd_bins[bin];
if (fwd_bins[bin] > max_bin)
{
max_bin = fwd_bins[bin];
}
}
Size max_reverse_bin(0), max_reverse_bin_value(0);
//min = rev_trafo.min_score;
//diff = rev_trafo.diff_score;
for (vector<double>::const_iterator it = rev_scores.begin(); it != rev_scores.end(); ++it)
{
Size bin = (Size)((*it - min) / diff * (double)number_of_bins);
++rev_bins[bin];
if (rev_bins[bin] > max_bin)
{
max_bin = rev_bins[bin];
}
if (rev_bins[bin] > max_reverse_bin_value)
{
max_reverse_bin = bin;
max_reverse_bin_value = rev_bins[bin];
}
}
#ifdef IDDECOYPROBABILITY_DEBUG
cerr << "Trying to get diff scores" << endl;
#endif
// get diff of fwd and rev
for (Size i = 0; i < number_of_bins; ++i)
{
Size fwd(0), rev(0);
fwd = fwd_bins[i];
rev = rev_bins[i];
if ((double)fwd > (double)(1.3 * rev) && max_reverse_bin < i)
{
diff_scores[i] = (double)(fwd - rev) / (double)max_bin;
}
else
{
diff_scores[i] = 0.0;
}
}
#ifdef IDDECOYPROBABILITY_DEBUG
cerr << "Gauss Fitting values size of diff scores=" << diff_scores.size() << endl;
#endif
// diff scores fitting
vector<DPosition<2> > diff_data;
double gauss_A(0), gauss_x0(0), norm_factor(0);
for (Size i = 0; i < number_of_bins; ++i)
{
DPosition<2> pos;
pos.setX((double)i / (double)number_of_bins);
pos.setY(diff_scores[i]);
if (pos.getY() > gauss_A)
{
gauss_A = pos.getY();
}
gauss_x0 += pos.getX() * pos.getY();
norm_factor += pos.getY();
diff_data.push_back(pos);
}
double gauss_sigma(0);
gauss_x0 /= (double)diff_data.size();
gauss_x0 /= norm_factor;
for (Size i = 0; i <= number_of_bins; ++i)
{
gauss_sigma += fabs(gauss_x0 - (double)i / (double)number_of_bins);
}
gauss_sigma /= (double)diff_data.size();
#ifdef IDDECOYPROBABILITY_DEBUG
cerr << "setting initial parameters: " << endl;
#endif
Math::GaussFitter gf;
Math::GaussFitter::GaussFitResult result_1st(gauss_A, gauss_x0, gauss_sigma);
gf.setInitialParameters(result_1st);
#ifdef IDDECOYPROBABILITY_DEBUG
cerr << "Initial Gauss guess: A=" << gauss_A << ", x0=" << gauss_x0 << ", sigma=" << gauss_sigma << endl;
#endif
//TODO: fail-to-fit correction was done using the GNUPlotFormula. Seemed to be a hack.
//Changed it to try-catch-block but I am not sure if this correction should be made
//at all. Can someone please verify?
Math::GaussFitter::GaussFitResult result_gauss (gauss_A, gauss_x0, gauss_sigma);
try{
result_gauss = gf.fit(diff_data);
}
catch(Exception::UnableToFit& /* e */)
{
result_gauss.A = gauss_A;
result_gauss.x0 = gauss_x0;
result_gauss.sigma = gauss_sigma;
}
// // fit failed?
// if (gf.getGnuplotFormula() == "")
// {
// result_gauss.A = gauss_A;
// result_gauss.x0 = gauss_x0;
// result_gauss.sigma = gauss_sigma;
// }
#ifdef IDDECOYPROBABILITY_DEBUG
cerr << gf.getGnuplotFormula() << endl;
String fwd_filename = param_.getValue("fwd_filename");
if (gf.getGnuplotFormula() == "")
{
String formula("f(x)=" + String(gauss_A) + " * exp(-(x - " + String(gauss_x0) + ") ** 2 / 2 / (" + String(gauss_sigma) + ") ** 2)");
generateDistributionImage_(diff_scores, formula, fwd_filename);
}
else
{
generateDistributionImage_(diff_scores, gf.getGnuplotFormula(), fwd_filename);
}
#endif
#ifdef IDDECOYPROBABILITY_DEBUG
//all_trafo.diff_score + all_trafo.min_score
String gauss_formula("f(x)=" + String(result_gauss.A / all_trafo.max_intensity) + " * exp(-(x - " + String(result_gauss.x0 * all_trafo.diff_score + all_trafo.min_score) + ") ** 2 / 2 / (" + String(result_gauss.sigma * all_trafo.diff_score) + ") ** 2)");
String b_str(result_gamma.b), p_str(result_gamma.p);
String gamma_formula = "g(x)=(" + b_str + " ** " + p_str + ") / gamma(" + p_str + ") * x ** (" + p_str + " - 1) * exp(- " + b_str + " * x)";
generateDistributionImage_(all_scores_normalized, all_trafo, gauss_formula, gamma_formula, (String)param_.getValue("fwd_filename"));
#endif
vector<PeptideIdentification> new_prob_ids;
// calculate the probabilities and write them to the IDs
for (vector<PeptideIdentification>::const_iterator it = ids.begin(); it != ids.end(); ++it)
{
if (it->getHits().size() > 0)
{
vector<PeptideHit> hits;
String score_type = it->getScoreType() + "_score";
for (vector<PeptideHit>::const_iterator pit = it->getHits().begin(); pit != it->getHits().end(); ++pit)
{
PeptideHit hit = *pit;
double score = hit.getScore();
if (!it->isHigherScoreBetter())
{
score = -log10(score);
}
hit.setMetaValue(score_type, hit.getScore());
hit.setScore(getProbability_(result_gamma, rev_trafo, result_gauss, fwd_trafo, score));
hits.push_back(hit);
}
PeptideIdentification id = *it;
id.setHigherScoreBetter(true);
id.setScoreType(id.getScoreType() + "_DecoyProbability");
id.setHits(hits);
new_prob_ids.push_back(id);
}
}
ids = new_prob_ids;
}
