/// <summary>
/// Return a list of peaks, where each peak has the maximum score in its transition group,
/// and its q-value is less than the cutoff value.
/// </summary>
/// <param name="qValueCutoff">Cutoff q-value.</param>
/// <param name="lambda">Optional p-value cutoff for calculating Pi-zero.</param>
/// <param name="decoyScoredGroupPeaks">Decoy transition groups.</param>
/// <returns>List of peaks the meet the criteria.</returns>
public List <ScoredPeak> SelectTruePeaks(double qValueCutoff, double?lambda, ScoredGroupPeaksSet decoyScoredGroupPeaks)
{
// Get max peak score for each transition group.
var targetScores = GetMaxScores();
var decoyScores = decoyScoredGroupPeaks.GetMaxScores();
// Calculate statistics for each set of scores.
var statDecoys = new Statistics(decoyScores);
var statTarget = new Statistics(targetScores);
// Calculate q values from decoy set.
var pvalues = statDecoys.PvaluesNorm(statTarget);
var qvalues = new Statistics(pvalues).Qvalues(lambda);
// Select max peak with q value less than the cutoff from each target group.
var truePeaks = new List <ScoredPeak>(_scoredGroupPeaksList.Count);
for (int i = 0; i < _scoredGroupPeaksList.Count; i++)
{
if (qvalues[i] <= qValueCutoff)
{
truePeaks.Add(_scoredGroupPeaksList[i].MaxPeak);
}
}
return(truePeaks);
}
private double[] CalcPValues(ScoredGroupPeaksSet decoyScoredGroupPeaks, bool nonParametric = false)
{
// Get max peak score for each transition group.
var targetScores = GetMaxScores();
var decoyScores = decoyScoredGroupPeaks.GetMaxScores();
// Calculate statistics for each set of scores.
var statDecoys = new Statistics(decoyScores);
var statTarget = new Statistics(targetScores);
return(nonParametric
? statDecoys.PvaluesNull(statTarget)
: statDecoys.PvaluesNorm(statTarget));
}
