/// <summary>
/// Fit a Gaussian mixture model.
/// Fix the means to the model MAF and Coverage and run the EM algorithm until convergence.
/// Compute the empirical MAF and Coverage.
/// Fix the means to the empirical MAF and Coverage and run the EM algorithm again until convergence.
/// Always estimate the full covariance matrix?
/// </summary>
/// <param name="model"></param>
/// <param name="segments"></param>
/// <param name="debugPath"></param>
/// <returns></returns>
private double FitGaussians(CoverageModel model, List <SegmentInfo> segments, string debugPath = null)
{
List <ModelPoint> modelPoints = InitializeModelPoints(model);
GaussianMixtureModel gmm = new GaussianMixtureModel(modelPoints, segments, this.MeanCoverage, this.CoverageWeightingFactor, 0);
double likelihood = gmm.Fit();
if (debugPath != null)
{
// write Gaussian mixture model to debugPath
using (FileStream stream = new FileStream(debugPath, FileMode.Create, FileAccess.Write))
using (StreamWriter writer = new StreamWriter(stream))
{
writer.WriteLine("CN\tMajor Chr #\tMAF\tCoverage\tOmega\tMu0\tMu1\tSigma00\tSigma01\tSigma10\tSigma11");
foreach (ModelPoint modelPoint in modelPoints)
{
writer.WriteLine("{0}\t{1}\t{2}\t{3}\t{4}\t{5}\t{6}\t{7}\t{8}\t{9}\t{10}",
modelPoint.Ploidy.CopyNumber, modelPoint.Ploidy.MajorChromosomeCount,
modelPoint.Ploidy.MixedMinorAlleleFrequency, modelPoint.Ploidy.MixedCoverage,
modelPoint.Ploidy.Omega, modelPoint.Ploidy.Mu[0], modelPoint.Ploidy.Mu[1],
modelPoint.Ploidy.Sigma[0][0], modelPoint.Ploidy.Sigma[0][1],
modelPoint.Ploidy.Sigma[1][0], modelPoint.Ploidy.Sigma[1][1]);
}
writer.WriteLine("");
writer.WriteLine("MAF\tCoverage\tPosterior Probabilities");
StringBuilder sb = new StringBuilder();
foreach (SegmentInfo segment in segments)
{
sb.Clear();
sb.AppendFormat("{0}\t{1}", segment.MAF, segment.Coverage);
foreach (ModelPoint modelPoint in modelPoints)
{
sb.AppendFormat("\t{0}", segment.PosteriorProbs[modelPoint]);
}
writer.WriteLine(sb.ToString());
}
}
}
return(likelihood);
}