/// <summary>
/// Evaluate joint log likelihood of all genotype combinations across samples.
/// Return joint likelihood object and the copy number states with the highest likelihood
/// </summary>
public static (SampleMap <Genotype> copyNumbersGenotypes, JointLikelihoods jointLikelihood) GetCopyNumbersNoPedigreeInfo(ISampleMap <CanvasSegment> segments,
ISampleMap <Dictionary <Genotype, double> > singleSampleLikelihoods)
{
// for non-pedigree samples JointLogLikelihoods object contains only maximum likelihood information
var jointLogLikelihoods = new JointLikelihoods();
var sampleCopyNumbersGenotypes = new SampleMap <Genotype>();
foreach (var sampleId in segments.SampleIds)
{
var(copyNumber, maxSampleLikelihood) = singleSampleLikelihoods[sampleId].MaxBy(x => x.Value);
jointLogLikelihoods.MaximalLogLikelihood += Math.Log(maxSampleLikelihood);
sampleCopyNumbersGenotypes.Add(sampleId, copyNumber);
}
return(copyNumbersGenotypes : sampleCopyNumbersGenotypes, jointLikelihood : jointLogLikelihoods);
}
/// <summary>
/// Perform de-novo CNV calling in two steps:
/// 1. Filter REF variants and common CNVs, this step relies only on total CN calls with associated shortcomings
/// 2. Assign de-novo quality based on joint likelihood across pedigree using marginalisation operations
/// </summary>
/// <param name="canvasSegments"></param>
/// <param name="samplesInfo"></param>
/// <param name="parentIDs"></param>
/// <param name="offspringIDs"></param>
/// <param name="copyNumbersLikelihoods"></param>
private void SetDenovoQualityScores(ISampleMap <CanvasSegment> canvasSegments, ISampleMap <SampleMetrics> samplesInfo, List <SampleId> parentIDs, List <SampleId> offspringIDs,
JointLikelihoods copyNumbersLikelihoods)
{
foreach (var probandId in offspringIDs)
{
// targeted proband is REF
if (IsReferenceVariant(canvasSegments, samplesInfo, probandId))
{
continue;
}
// common variant
if (CanvasPedigreeCaller.IsSharedCnv(canvasSegments, samplesInfo, parentIDs, probandId, _callerParameters.MaximumCopyNumber))
{
continue;
}
// other offsprings are ALT
if (!offspringIDs.Except(probandId.ToEnumerable()).All(id => IsReferenceVariant(canvasSegments, samplesInfo, id)))
{
continue;
}
// not all q-scores are above the threshold
if (parentIDs.Concat(probandId).Any(id => !IsPassVariant(canvasSegments, id)))
{
continue;
}
double deNovoQualityScore = CanvasPedigreeCaller.GetConditionalDeNovoQualityScore(canvasSegments, copyNumbersLikelihoods, samplesInfo, parentIDs, probandId);
// adjustment so that denovo quality score threshold is 20 (rather than 10) to match Manta
deNovoQualityScore *= 2;
if (Double.IsInfinity(deNovoQualityScore) | deNovoQualityScore > _callerParameters.MaxQscore)
{
deNovoQualityScore = _callerParameters.MaxQscore;
}
canvasSegments[probandId].DqScore = deNovoQualityScore;
}
}
/// <summary>
/// Assess likelihood of a de-novo variant for copyNumberGenotypes configuration with a Mendelian conflict
/// </summary>
/// <param name="canvasSegments"></param>
/// <param name="jointLikelihoods"></param>
/// <param name="parentIDs"></param>
/// <param name="probandId"></param>
/// <param name="samplesInfo"></param>
/// <returns></returns>
internal static double GetConditionalDeNovoQualityScore(ISampleMap <CanvasSegment> canvasSegments, JointLikelihoods jointLikelihoods, ISampleMap <SampleMetrics> samplesInfo, List <SampleId> parentIDs, SampleId probandId)
{
const double q60 = 0.000001;
var parent1Ploidy = Genotype.Create(samplesInfo[parentIDs.First()].GetPloidy(canvasSegments[parentIDs.First()]));
var parent2Ploidy = Genotype.Create(samplesInfo[parentIDs.Last()].GetPloidy(canvasSegments[parentIDs.Last()]));
int probandPloidy = samplesInfo[probandId].GetPloidy(canvasSegments[probandId]);
double deNovoGainMarginalLikelihood = jointLikelihoods.GetMarginalGainDeNovoLikelihood(new KeyValuePair <SampleId, Genotype>(probandId, Genotype.Create(probandPloidy)),
new KeyValuePair <SampleId, Genotype>(parentIDs.First(), parent1Ploidy), new KeyValuePair <SampleId, Genotype>(parentIDs.Last(), parent2Ploidy));
double deNovoLossMarginalLikelihood = jointLikelihoods.GetMarginalLossDeNovoLikelihood(new KeyValuePair <SampleId, Genotype>(probandId, Genotype.Create(probandPloidy)),
new KeyValuePair <SampleId, Genotype>(parentIDs.First(), parent1Ploidy), new KeyValuePair <SampleId, Genotype>(parentIDs.Last(), parent2Ploidy));
double denovoProbability = canvasSegments[probandId].CopyNumber > probandPloidy ?
1 - deNovoGainMarginalLikelihood / (jointLikelihoods.TotalMarginalLikelihood - deNovoLossMarginalLikelihood) :
1 - deNovoLossMarginalLikelihood / (jointLikelihoods.TotalMarginalLikelihood - deNovoGainMarginalLikelihood);
// likelihood of proband genotype != ALT given "copyNumberGenotypes" configuration in pedigree with Mendelian conflict
return(-10.0 * Math.Log10(Math.Max(denovoProbability, q60)));
}
private void EstimateQScores(ISampleMap <CanvasSegment> canvasSegments, ISampleMap <SampleMetrics> pedigreeMembersInfo,
PedigreeInfo pedigreeInfo, ISampleMap <Dictionary <Genotype, double> > singleSampleLikelihoods, JointLikelihoods copyNumberLikelihoods, ISampleMap <Genotype> copyNumbers)
{
foreach (var sampleId in canvasSegments.SampleIds)
{
canvasSegments[sampleId].QScore = GetSingleSampleQualityScore(singleSampleLikelihoods[sampleId], copyNumbers[sampleId]);
canvasSegments[sampleId].CopyNumber = copyNumbers[sampleId].TotalCopyNumber;
if (canvasSegments[sampleId].QScore < _qualityFilterThreshold)
{
canvasSegments[sampleId].Filter = CanvasFilter.Create(new[] { $"q{_qualityFilterThreshold}" });
}
}
if (pedigreeInfo.HasFullPedigree())
{
SetDenovoQualityScores(canvasSegments, pedigreeMembersInfo, pedigreeInfo.ParentsIds, pedigreeInfo.OffspringIds, copyNumberLikelihoods);
}
}
/// <summary>
/// Estimate joint likelihood and most likely CN assignment within a pedigree using total CN Genotype likelihoods and transition matrix
/// </summary>
/// <param name="pedigreeInfo"></param>
/// <param name="copyNumbersLikelihoods"></param>
/// <returns></returns>
private (ISampleMap <Genotype> copyNumbersGenotypes, JointLikelihoods jointLikelihood) GetPedigreeCopyNumbers(PedigreeInfo pedigreeInfo, ISampleMap <Dictionary <Genotype, double> > copyNumbersLikelihoods)
{
int nHighestLikelihoodGenotypes = pedigreeInfo != null && pedigreeInfo.OffspringIds.Count >= 2 ? 3 : _callerParameters.MaximumCopyNumber;
copyNumbersLikelihoods = copyNumbersLikelihoods.SelectValues(l => l.OrderByDescending(kvp => kvp.Value).Take(nHighestLikelihoodGenotypes).ToDictionary());
var sampleCopyNumbersGenotypes = new SampleMap <Genotype>();
var jointLikelihood = new JointLikelihoods();
if (!pedigreeInfo.HasFullPedigree())
{
return(sampleCopyNumbersGenotypes, jointLikelihood);
}
// parent 1 total CNs and likelihoods
foreach (var copyNumberParent1 in copyNumbersLikelihoods[pedigreeInfo.ParentsIds.First()])
{
// parent 2 total CNs and likelihoods
foreach (var copyNumberParent2 in copyNumbersLikelihoods[pedigreeInfo.ParentsIds.Last()])
{
// for offspring in addition to querying likelihoods using total CNs, iterate over all possible genotype combination (CopyNumberA/B) for a given
// CN and estimate likely transition probabilities using TransitionMatrix
foreach (var offspringGtStates in pedigreeInfo.OffspringPhasedGenotypes)
{
if (!pedigreeInfo.OffspringIds.All(id => copyNumbersLikelihoods[id].ContainsKey(
Genotype.Create(Math.Min(offspringGtStates[pedigreeInfo.OffspringIds.IndexOf(id)].PhasedGenotype.CopyNumberA + offspringGtStates[pedigreeInfo.OffspringIds.IndexOf(id)].PhasedGenotype.CopyNumberB,
_callerParameters.MaximumCopyNumber - 1)))))
{
// unavailable total CN
continue;
}
// For a given combination of offspring copy numbers, only the genotypes that result in the maximum likelihood contribute to the final result."
double currentLikelihood = copyNumberParent1.Value * copyNumberParent2.Value;
var totalCopyNumberGenotypes = new List <Genotype>();
for (var counter = 0; counter < pedigreeInfo.OffspringIds.Count; counter++)
{
var child = pedigreeInfo.OffspringIds[counter];
var copyNumberGenotypeChild = Genotype.Create(Math.Min(offspringGtStates[counter].PhasedGenotype.CopyNumberA + offspringGtStates[counter].PhasedGenotype.CopyNumberB,
_callerParameters.MaximumCopyNumber - 1));
totalCopyNumberGenotypes.Add(copyNumberGenotypeChild);
currentLikelihood *= pedigreeInfo.TransitionMatrix[copyNumberParent1.Key.TotalCopyNumber][offspringGtStates[counter].PhasedGenotype.CopyNumberA] *
pedigreeInfo.TransitionMatrix[copyNumberParent2.Key.TotalCopyNumber][offspringGtStates[counter].PhasedGenotype.CopyNumberB] *
copyNumbersLikelihoods[child][copyNumberGenotypeChild];
}
currentLikelihood = Double.IsNaN(currentLikelihood) || Double.IsInfinity(currentLikelihood) ? 0 : currentLikelihood;
var genotypesInPedigree = new SampleMap <Genotype>
{
{ pedigreeInfo.ParentsIds.First(), copyNumberParent1.Key },
{ pedigreeInfo.ParentsIds.Last(), copyNumberParent2.Key }
};
pedigreeInfo.OffspringIds.Zip(totalCopyNumberGenotypes).ForEach(sampleIdGenotypeKvp => genotypesInPedigree.Add(sampleIdGenotypeKvp.Item1, sampleIdGenotypeKvp.Item2));
genotypesInPedigree = genotypesInPedigree.OrderBy(pedigreeInfo.AllSampleIds);
jointLikelihood.AddJointLikelihood(genotypesInPedigree, currentLikelihood);
double currentLogLikelihood = Math.Log(currentLikelihood);
if (currentLogLikelihood > jointLikelihood.MaximalLogLikelihood)
{
jointLikelihood.MaximalLogLikelihood = currentLogLikelihood;
sampleCopyNumbersGenotypes = genotypesInPedigree;
}
}
}
}
if (sampleCopyNumbersGenotypes.Empty())
{
throw new IlluminaException("Maximal likelihood was not found");
}
return(sampleCopyNumbersGenotypes, jointLikelihood);
}
