public double CalculateSubsetFdr(ScoreDistribution subset, IFalseDiscoveryRateCalculator calc)
{
double targetCount = 0;
double decoyCount = 0;
foreach (OptimalResultCondition cond in subset.Keys)
{
var subsetOrs = subset[cond];
var totalOrs = this[cond];
var counts =
from s in subsetOrs
join t in totalOrs on s.Score equals t.Score
select new { TargetCount = (int)s.PeptideCountFromTargetDB, DecoyCount = (double)s.PeptideCountFromTargetDB * t.PeptideCountFromDecoyDB / t.PeptideCountFromTargetDB };
targetCount +=
(from c in counts
select c.TargetCount).Sum();
decoyCount +=
(from c in counts
select c.DecoyCount).Sum();
}
return(calc.Calculate((int)decoyCount, (int)targetCount));
}
public void Test()
{
ScoreDistribution s = new ScoreDistribution();
OptimalResultCondition or = new OptimalResultCondition(1, 1, 1, 1);
s[or] = new List <OptimalResult>()
{
new OptimalResult(1.0, 1.0, 100, 10, 0.1),
new OptimalResult(2.0, 1.0, 200, 10, 0.05),
new OptimalResult(3.0, 1.0, 1000, 10, 0.01)
};
ScoreDistribution subset = new ScoreDistribution();
subset[or] = new List <OptimalResult>()
{
new OptimalResult(2.0, 1.0, 100, 0, 0),
new OptimalResult(3.0, 1.0, 900, 0, 0)
};
IFalseDiscoveryRateCalculator calc = new TargetFalseDiscoveryRateCalculator();
double fdr = s.CalculateSubsetFdr(subset, calc);
Assert.AreEqual(0.014, fdr);
}
