override public IEnumerable <TrueCollection> Collection()
{
Set <Hla> assignmentAsSet = CreateAssignmentAsSet(QmmrModelOnePeptide.BestHlaAssignmentSoFar.Champ);
foreach (Hla originalTrueHla in QmmrModelOnePeptide.BestHlaAssignmentSoFar.Champ)
{
if (QmmrModelOnePeptide.QmrrModelMissingAssignment.KnownHlaSet.Contains(originalTrueHla))
{
continue;
}
assignmentAsSet.Remove(originalTrueHla);
foreach (Hla originalFalseHla in QmmrModelOnePeptide.QmrrModelMissingAssignment.SwitchableHlasOfRespondingPatients)
{
if (!assignmentAsSet.Contains(originalFalseHla))
{
assignmentAsSet.AddNew(originalFalseHla);
Debug.Assert(assignmentAsSet.Count == QmmrModelOnePeptide.BestHlaAssignmentSoFar.Champ.Count); // real assert
yield return(TrueCollection.GetInstance(assignmentAsSet));
assignmentAsSet.Remove(originalFalseHla);
}
}
assignmentAsSet.AddNew(originalTrueHla);
Debug.Assert(assignmentAsSet.Count == QmmrModelOnePeptide.BestHlaAssignmentSoFar.Champ.Count); // real assert
}
}
private void ReportPerHla(OptimizationParameterList qmrrParams, Dictionary <string, BestSoFar <double, TrueCollection> > peptideToBestHlaAssignmentSoFar,
string directory, string name)
{
string fileName = string.Format(@"{0}\NoisyOr.PeptideHlaProbability.{1}.new.txt", directory, name);
using (StreamWriter output = File.CreateText(fileName))
{
output.WriteLine(SpecialFunctions.CreateTabString("Peptide", "HLA", "LogOdds", "Probability"));
foreach (QmrrPartialModel qmrrPartialModel in QmrrPartialModelCollection)
{
QmrrModelMissingAssignment aQmrrModelMissingAssignment = QmrrModelMissingAssignment.GetInstance(ModelLikelihoodFactories, qmrrPartialModel, qmrrParams);
BestSoFar <double, TrueCollection> bestHlaAssignment = peptideToBestHlaAssignmentSoFar[qmrrPartialModel.Peptide];
Set <Hla> trueCollectionFullAsSet = new Set <Hla>(bestHlaAssignment.Champ);
double loglikelihoodFull = bestHlaAssignment.ChampsScore;
foreach (Hla hla in trueCollectionFullAsSet)
{
bool known = qmrrPartialModel.KnownHlaSet.Contains(hla);
if (!known)
{
Set <Hla> allLessOne = trueCollectionFullAsSet.SubtractElement(hla);
TrueCollection trueCollectionWithout = TrueCollection.GetInstance(allLessOne);
double loglikelihoodWithout = aQmrrModelMissingAssignment.LogLikelihoodOfCompleteModelConditionedOnKnownHlas(trueCollectionWithout);
double logOdds = loglikelihoodFull - loglikelihoodWithout;
double probabilityFull = Math.Exp(loglikelihoodFull);
double probabilityWithout = Math.Exp(loglikelihoodWithout);
double probability = probabilityFull / (probabilityFull + probabilityWithout);
Debug.Assert(logOdds >= 0); // real assert
output.WriteLine(SpecialFunctions.CreateTabString(qmrrPartialModel.Peptide, hla, logOdds, probability));
}
}
}
}
}
internal void CreateNoSwitchablesHlaAssignment()
{
BestHlaAssignmentSoFar = BestSoFar <double, TrueCollection> .GetInstance(SpecialFunctions.DoubleGreaterThan);
TrueCollection trueCollection = TrueCollection.GetInstance(QmrrModelMissingAssignment.KnownHlaSet);
double scoreOnNoSwitchables = QmrrModelMissingAssignment.LogLikelihoodOfCompleteModelConditionedOnKnownHlas(trueCollection);
BestHlaAssignmentSoFar.Compare(scoreOnNoSwitchables, trueCollection);
}
internal static Set <Hla> CreateAssignmentAsSet(TrueCollection startingAssignment)
{
Set <Hla> assignmentAsSet = Set <Hla> .GetInstance();
foreach (Hla hla in startingAssignment)
{
assignmentAsSet.AddNew(hla);
}
return(assignmentAsSet);
}
//!!!similar code is used in NumberOfPositiveHlas
private int FitTrueCount(Set <Hla> fitUniverse, TrueCollection trueCollection)
{
int fitTrueCount = 0;
foreach (Hla hla in trueCollection)
{
if (fitUniverse.Contains(hla))
{
++fitTrueCount;
}
}
return(fitTrueCount);
}
internal static TrueCollection GetInstance(params IEnumerable <Hla>[] hlaCollectionCollection)
{
TrueCollection aTrueCollection = new TrueCollection();
foreach (IEnumerable <Hla> hlaCollection in hlaCollectionCollection)
{
foreach (Hla hla in hlaCollection)
{
aTrueCollection.Add(hla);
}
}
return(aTrueCollection);
}
override public IEnumerable <TrueCollection> Collection()
{
Set <Hla> assignmentAsSet = CreateAssignmentAsSet(QmmrModelOnePeptide.BestHlaAssignmentSoFar.Champ);
SubtractKnownHlas(ref assignmentAsSet);
EverySubsetBySize aEverySubsetBySize = EverySubsetBySize.GetInstance(QmmrModelOnePeptide.QmrrModelMissingAssignment.SwitchableHlasOfRespondingPatients.Count, Depth, 1);
foreach (List <int> indexList in aEverySubsetBySize.Collection())
{
FlipListedBits(assignmentAsSet, indexList);
yield return(TrueCollection.GetInstance(QmmrModelOnePeptide.QmrrModelMissingAssignment.KnownHlaSet, assignmentAsSet));
FlipListedBits(assignmentAsSet, indexList);
}
}
private void ReportPerHlaAssignment(Dictionary <string, BestSoFar <double, TrueCollection> > peptideToBestHlaAssignmentSoFar,
string directory, string name)
{
string fileName = string.Format(@"{0}\NoisyOr.HlasPerPeptide.{1}.new.txt", directory, name);
using (StreamWriter output = File.CreateText(fileName))
{
output.WriteLine(SpecialFunctions.CreateTabString("Peptide", "HLAAssignment", "LogLikelihood"));
foreach (QmrrPartialModel qmrrPartialModel in QmrrPartialModelCollection)
{
BestSoFar <double, TrueCollection> bestHlaAssignment = peptideToBestHlaAssignmentSoFar[qmrrPartialModel.Peptide];
TrueCollection trueCollectionFull = bestHlaAssignment.Champ;
double loglikelihoodFull = bestHlaAssignment.ChampsScore;
output.WriteLine(SpecialFunctions.CreateTabString(qmrrPartialModel.Peptide, trueCollectionFull, loglikelihoodFull));
}
}
}
internal static HlaAssignmentWithResponses GetInstance(IEnumerable <Hla> trueCollection, Quickscore <Hla, int> quickscore, List <Hla> hlaListFromRepondingPatients, Dictionary <Hla, List <int> > hlaToRespondingPatients)
{
HlaAssignmentWithResponses aHlaAssignment = new HlaAssignmentWithResponses();
aHlaAssignment.TrueCollection = TrueCollection.GetInstance(trueCollection);
aHlaAssignment.AsDictionary = new Dictionary <Hla, bool>();
aHlaAssignment.UnexplainedPatients = new List <int>();
Dictionary <int, bool> patientToIsExplained = new Dictionary <int, bool>();
aHlaAssignment.HlaToRespondingPatients = hlaToRespondingPatients;
foreach (Hla hla in trueCollection)
{
aHlaAssignment.AsDictionary.Add(hla, true);
foreach (int patient in hlaToRespondingPatients[hla])
{
patientToIsExplained[patient] = true;
}
}
foreach (Hla hla in quickscore.CauseList())
{
if (!aHlaAssignment.AsDictionary.ContainsKey(hla))
{
aHlaAssignment.AsDictionary.Add(hla, false);
if (hlaToRespondingPatients.ContainsKey(hla))
{
foreach (int patient in hlaToRespondingPatients[hla])
{
if (!patientToIsExplained.ContainsKey(patient))
{
patientToIsExplained.Add(patient, false);
aHlaAssignment.UnexplainedPatients.Add(patient);
}
}
}
}
}
return(aHlaAssignment);
}
override public IEnumerable <TrueCollection> Collection()
{
Set <Hla> assignmentAsSet = CreateAssignmentAsSet(QmmrModelOnePeptide.BestHlaAssignmentSoFar.Champ);
foreach (Hla hla in QmmrModelOnePeptide.QmrrModelMissingAssignment.SwitchableHlasOfRespondingPatients)
{
if (assignmentAsSet.Contains(hla))
{
assignmentAsSet.Remove(hla);
yield return(TrueCollection.GetInstance(assignmentAsSet));
assignmentAsSet.AddNew(hla);
}
else
{
assignmentAsSet.AddNew(hla);
yield return(TrueCollection.GetInstance(assignmentAsSet));
assignmentAsSet.Remove(hla);
}
}
}
internal static TrueCollection GetInstance()
{
TrueCollection aTrueCollection = new TrueCollection();
return(aTrueCollection);
}
virtual public MissingParametersDelegate MissingParametersDelegateFactory(QmrrPartialModel qmrrPartialModel, TrueCollection trueCollection)
{
PartialModelDelegate LogLikelihoodOfCompleteModelConditionedOnKnownHlas = PartialModelDelegateFactory(qmrrPartialModel);
return(delegate(OptimizationParameterList parameterList)
{
return LogLikelihoodOfCompleteModelConditionedOnKnownHlas(trueCollection, parameterList);
});
}
private double LogLikelihoodOfCompleteModelConditionedOnKnownHlas(QmrrPartialModel qmrrPartialModel, TrueCollection trueCollection, OptimizationParameterList qmrrParams)
{
Set <Hla> trueHlaSet = trueCollection.CreateHlaAssignmentAsSet();
int reactionsCoveredCount = CountReactionsCovered(qmrrPartialModel, trueHlaSet);
SpecialFunctions.CheckCondition(reactionsCoveredCount < 1000);
int trueCount = trueCollection.Count;
SpecialFunctions.CheckCondition(trueCount < 1000);
int falseCount = qmrrPartialModel.HlaList.Count - trueCollection.Count;
SpecialFunctions.CheckCondition(falseCount < 1000);
string llAsString = string.Format("{0:000}.{1:000}{2:000}", reactionsCoveredCount, falseCount, trueCount);
double logLikelihood = double.Parse(llAsString);
return(logLikelihood);
}
protected override double LogLikelihoodOfCausesConditionedOnKnownHlas(QmrrPartialModel qmrrPartialModel, TrueCollection trueCollection, OptimizationParameterList qmrrParams)
{
//!!!This could be calculated during the construction of qmrrPartialModel
Set <Hla> fitUniverse = SpecialFunctions.GetValueOrDefault(PeptideToFitUniverse, qmrrPartialModel.Peptide);
//Compute with priors
double unfitCausePrior = qmrrParams["causePrior"].Value;
double fitFactor = qmrrParams["fitFactor"].Value;
double fitCausePrior = unfitCausePrior * fitFactor;
double logUnfitCausePrior = Math.Log(unfitCausePrior);
double logOneLessUnfitCausePrior = Math.Log(1.0 - unfitCausePrior);
double logFitCausePrior = Math.Log(fitCausePrior);
double logOneLessFitCausePrior = Math.Log(1.0 - fitCausePrior);
//Tabulate counts
int unfitTotalCount = qmrrPartialModel.HlaList.Count - fitUniverse.Count;
int trueCountLessKnown = trueCollection.Count - qmrrPartialModel.KnownHlaSet.Count;
int falseCount = qmrrPartialModel.HlaList.Count - trueCollection.Count;
int knownFitCount = KnownFitCount(fitUniverse, qmrrPartialModel.KnownHlaSet); //!!!could be pretabulated
int knownUnfitCount = qmrrPartialModel.KnownHlaSet.Count - knownFitCount;
int fitTrueCountLessKnown = FitTrueCount(fitUniverse, trueCollection) - knownFitCount;
int unfitTrueCountLessKnown = trueCountLessKnown - fitTrueCountLessKnown;
int fitFalseCount = fitUniverse.Count - fitTrueCountLessKnown - knownFitCount;
int unfitFalseCount = unfitTotalCount - unfitTrueCountLessKnown - knownUnfitCount;
//Compute logLikelihood
double logLikelihood =
(double)unfitTrueCountLessKnown * logUnfitCausePrior
+ (double)unfitFalseCount * logOneLessUnfitCausePrior
+ (double)fitTrueCountLessKnown * logFitCausePrior
+ (double)fitFalseCount * logOneLessFitCausePrior;
return(logLikelihood);
}
virtual protected double LogLikelihoodOfCompleteModelConditionedOnKnownHlas(QmrrPartialModel qmrrPartialModel, TrueCollection trueCollection, OptimizationParameterList qmrrParams)
{
double logLikelihood =
LogLikelihoodOfCausesConditionedOnKnownHlas(qmrrPartialModel, trueCollection, qmrrParams)
+ LogLikelihoodOfEffects(qmrrPartialModel, trueCollection, qmrrParams);
return(logLikelihood);
}
virtual protected double LogLikelihoodOfCausesConditionedOnKnownHlas(QmrrPartialModel qmrrPartialModel, TrueCollection trueCollection, OptimizationParameterList qmrrParams)
{
double logCausePrior = Math.Log(qmrrParams["causePrior"].Value);
double logOneLessCausePrior = Math.Log(1.0 - qmrrParams["causePrior"].Value);
int trueCountLessKnown = trueCollection.Count - qmrrPartialModel.KnownHlaSet.Count;
Debug.Assert(trueCountLessKnown >= 0); // real assert
int falseCount = qmrrPartialModel.HlaList.Count - trueCollection.Count;
double logLikelihood =
(double)trueCountLessKnown * logCausePrior
+ (double)falseCount * logOneLessCausePrior;
return(logLikelihood);
}
virtual protected double LogLikelihoodOfEffects(QmrrPartialModel qmrrPartialModel, TrueCollection trueCollection, OptimizationParameterList qmrrParams)
{
double logOneLessLink = Math.Log(1.0 - qmrrParams["link"].Value);
double logOneLessLeakProbability = Math.Log(1.0 - qmrrParams["leakProbability"].Value);
double logLikelihood = 0.0;
Set <Hla> trueCollectionAsSet = trueCollection.CreateHlaAssignmentAsSet();
foreach (KeyValuePair <string, Set <Hla> > patientAndHlaList in qmrrPartialModel.PatientList)
{
double logLikelihoodNoReactionInThisPatient =
logOneLessLeakProbability
+ NumberOfPositiveHlas(patientAndHlaList.Value, trueCollectionAsSet) * logOneLessLink;
bool didReact = qmrrPartialModel.PatientToAnyReaction.ContainsKey(patientAndHlaList.Key);
logLikelihood += LogLikelihoodOfThisPatient(logLikelihoodNoReactionInThisPatient, didReact);
}
return(logLikelihood);
}
override protected double LogLikelihoodOfEffects(QmrrPartialModel qmrrPartialModel, TrueCollection trueCollection, OptimizationParameterList qmrrParams)
{
Set <Hla> trueCollectionAsSet = trueCollection.CreateHlaAssignmentAsSet();
double logOneLessLeakProbability = Math.Log(1.0 - qmrrParams["leakProbability"].Value);
Dictionary <Hla, double> hlaToLogOneLessLink = new Dictionary <Hla, double>();
foreach (Hla hla in trueCollectionAsSet)
{
double logOneLessLink = Math.Log(1.0 - qmrrParams["link" + hla].Value);
hlaToLogOneLessLink.Add(hla, logOneLessLink);
}
double logLikelihood = 0.0;
foreach (KeyValuePair <string, Set <Hla> > patientAndHlaList in qmrrPartialModel.PatientList)
{
double logLikelihoodNoReactionInThisPatient = logOneLessLeakProbability;
foreach (Hla hla in patientAndHlaList.Value)
{
if (trueCollectionAsSet.Contains(hla))
{
double logOneLessLink = hlaToLogOneLessLink[hla];
logLikelihoodNoReactionInThisPatient += logOneLessLink;
}
}
bool didReact = qmrrPartialModel.PatientToAnyReaction.ContainsKey(patientAndHlaList.Key);
logLikelihood += LogLikelihoodOfThisPatient(logLikelihoodNoReactionInThisPatient, didReact);
}
return(logLikelihood);
}