void DigestSimulation::digest(SimTypes::FeatureMapSim& feature_map)
{
LOG_INFO << "Digest Simulation ... started" << std::endl;
if ((String)param_.getValue("enzyme") == String("none"))
{
//peptides = proteins;
// convert all proteins into peptides
// for each protein_hit in the FeatureMap
for (std::vector<ProteinHit>::iterator protein_hit = feature_map.getProteinIdentifications()[0].getHits().begin();
protein_hit != feature_map.getProteinIdentifications()[0].getHits().end();
++protein_hit)
{
// generate a PeptideHit hit with the correct link to the protein
PeptideHit pep_hit(1.0, 1, 0, AASequence::fromString(protein_hit->getSequence()));
PeptideEvidence pe;
pe.setProteinAccession(protein_hit->getAccession());
pep_hit.addPeptideEvidence(pe);
// add the PeptideHit to the PeptideIdentification
PeptideIdentification pep_id;
pep_id.insertHit(pep_hit);
// generate Feature with correct Intensity and corresponding PeptideIdentification
Feature f;
f.getPeptideIdentifications().push_back(pep_id);
f.setIntensity(protein_hit->getMetaValue("intensity"));
// copy intensity meta-values and additional annotations from Protein to Feature
StringList keys;
protein_hit->getKeys(keys);
for (StringList::const_iterator it_key = keys.begin(); it_key != keys.end(); ++it_key)
{
f.setMetaValue(*it_key, protein_hit->getMetaValue(*it_key));
}
// add Feature to SimTypes::FeatureMapSim
feature_map.push_back(f);
}
return;
}
UInt min_peptide_length = param_.getValue("min_peptide_length");
bool use_log_model = param_.getValue("model") == "trained" ? true : false;
UInt missed_cleavages = param_.getValue("model_naive:missed_cleavages");
double cleave_threshold = param_.getValue("model_trained:threshold");
EnzymaticDigestion digestion;
digestion.setEnzyme(digestion.getEnzymeByName((String)param_.getValue("enzyme")));
digestion.setLogModelEnabled(use_log_model);
digestion.setLogThreshold(cleave_threshold);
std::vector<AASequence> digestion_products;
// keep track of generated features
std::map<AASequence, Feature> generated_features;
// Iterate through ProteinHits in the FeatureMap and digest them
for (std::vector<ProteinHit>::iterator protein_hit = feature_map.getProteinIdentifications()[0].getHits().begin();
protein_hit != feature_map.getProteinIdentifications()[0].getHits().end();
++protein_hit)
{
// determine abundance of each digestion product (this is quite long now...)
// we assume that each digestion product will have the same abundance
// note: missed cleavages reduce overall abundance as they combine two (or more) single peptides
// how many "atomic"(i.e. non-cleavable) peptides are created?
digestion.setMissedCleavages(0);
Size complete_digest_count = digestion.peptideCount(AASequence::fromString(protein_hit->getSequence()));
// compute average number of "atomic" peptides summed from all digestion products
Size number_atomic_whole = 0;
Size number_of_digestion_products = 0;
for (Size i = 0; (i <= missed_cleavages) && (i < complete_digest_count); ++i)
{
number_atomic_whole += (complete_digest_count - i) * (i + 1);
number_of_digestion_products += (complete_digest_count - i);
}
// mean number of "atomic" peptides per digestion product is now: number_atomic_whole / number_of_digestion_products
// -> thus abundance of a digestion product is: #proteins / avg#of"atomic"peptides
// i.e.: protein->second / (number_atomic_whole / number_of_digestion_products)
Map<String, SimTypes::SimIntensityType> intensities;
StringList keys;
protein_hit->getKeys(keys);
for (StringList::const_iterator it_key = keys.begin(); it_key != keys.end(); ++it_key)
{
if (!it_key->hasPrefix("intensity"))
continue;
intensities[*it_key] = std::max(SimTypes::SimIntensityType(1), SimTypes::SimIntensityType(protein_hit->getMetaValue(*it_key))
* SimTypes::SimIntensityType(number_of_digestion_products)
/ SimTypes::SimIntensityType(number_atomic_whole)); // order changed for numeric stability
}
// do real digest
digestion.setMissedCleavages(missed_cleavages);
digestion.digest(AASequence::fromString(protein_hit->getSequence()), digestion_products);
for (std::vector<AASequence>::const_iterator dp_it = digestion_products.begin();
dp_it != digestion_products.end();
++dp_it)
{
if (dp_it->size() < min_peptide_length)
continue;
// sum equal peptide's intensities
// *dp_it -> peptide
// If we see this Peptide the first time -> generate corresponding feature
if (generated_features.count(*dp_it) == 0)
{
PeptideHit pep_hit(1.0, 1, 0, *dp_it);
PeptideIdentification pep_id;
pep_id.insertHit(pep_hit);
// create feature
Feature f;
f.getPeptideIdentifications().push_back(pep_id);
// set intensity to 0 to avoid problems when summing up
f.setIntensity(0.0);
// copy all non-intensity meta values
StringList lkeys;
protein_hit->getKeys(lkeys);
for (StringList::iterator key = lkeys.begin(); key != lkeys.end(); ++key)
{
if (!key->hasPrefix("intensity"))
{
f.setMetaValue(*key, protein_hit->getMetaValue(*key));
}
}
// insert into map
generated_features.insert(std::make_pair(*dp_it, f));
}
// sum up intensity values
generated_features[*dp_it].setIntensity(generated_features[*dp_it].getIntensity() + intensities["intensity"]);
// ... same for other intensities (iTRAQ...)
for (Map<String, SimTypes::SimIntensityType>::const_iterator it_other = intensities.begin(); it_other != intensities.end(); ++it_other)
{
if (!generated_features[*dp_it].metaValueExists(it_other->first))
{
generated_features[*dp_it].setMetaValue(it_other->first, it_other->second);
}
else
{
generated_features[*dp_it].setMetaValue(it_other->first, SimTypes::SimIntensityType(generated_features[*dp_it].getMetaValue(it_other->first)) + it_other->second);
}
}
// add current protein accession
// existing proteins accessions ...
std::set<String> protein_accessions = generated_features[*dp_it].getPeptideIdentifications()[0].getHits()[0].extractProteinAccessions();
// ... add accession of current protein
protein_accessions.insert(protein_hit->getAccession());
std::vector<PeptideIdentification> pep_idents = generated_features[*dp_it].getPeptideIdentifications();
std::vector<PeptideHit> pep_hits = pep_idents[0].getHits();
for (std::set<String>::const_iterator s_it = protein_accessions.begin(); s_it != protein_accessions.end(); ++s_it)
{
PeptideEvidence pe;
pe.setProteinAccession(*s_it);
pep_hits[0].addPeptideEvidence(pe);
}
pep_idents[0].setHits(pep_hits);
generated_features[*dp_it].setPeptideIdentifications(pep_idents);
}
}
// add generated_features to FeatureMap
for (std::map<AASequence, Feature>::iterator it_gf = generated_features.begin();
it_gf != generated_features.end();
++it_gf)
{
// round up intensity
(it_gf->second).setIntensity(ceil((it_gf->second).getIntensity()));
feature_map.push_back(it_gf->second);
}
}
START_SECTION((DoubleReal getLogThreshold() const))
EnzymaticDigestion ed;
ed.setLogThreshold(1.234);
TEST_EQUAL(ed.getLogThreshold(), 1.234);
END_SECTION
START_SECTION((void setLogThreshold(DoubleReal threshold)))
// TESTED ABOVE
NOT_TESTABLE
END_SECTION
START_SECTION((Size peptideCount(const AASequence &protein)))
EnzymaticDigestion ed;
Size tmp = ed.peptideCount(AASequence("ACDE"));
TEST_EQUAL(tmp,1)
tmp = ed.peptideCount(AASequence("ACKDE"));
TEST_EQUAL(tmp,2)
tmp = ed.peptideCount(AASequence("ACRDE"));
TEST_EQUAL(tmp,2)
tmp = ed.peptideCount(AASequence("ACKPDE"));
TEST_EQUAL(tmp,1)
tmp = ed.peptideCount(AASequence("ACRPDE"));
TEST_EQUAL(tmp,1)
tmp = ed.peptideCount(AASequence("ARCRDRE"));
TEST_EQUAL(tmp,4)
tmp = ed.peptideCount(AASequence("RKR"));
TEST_EQUAL(tmp,3)
ed.setMissedCleavages(1);
TEST_EQUAL(ed.peptideCount(AASequence("ACDE")),1)
