public ScoreDistribution ReadFromXml(XElement root)
{
var conds =
(from c in root.Descendants("Condition")
select c).ToList();
ScoreDistribution result = new ScoreDistribution();
foreach (var c in conds)
{
var key = new OptimalResultCondition(
Convert.ToInt32(c.Element("PrecursorCharge").Value),
Convert.ToInt32(c.Element("MissCleavageSiteCount").Value),
2,
Convert.ToInt32(c.Element("ModificationCount").Value),
c.Element("Classification").Value);
var values =
(from d in c.Element("Distribution").Descendants("Item")
select new OptimalResult()
{
Score = MyConvert.ToDouble(d.Element("Score").Value),
PeptideCountFromTargetDB = Convert.ToInt32(d.Element("Target").Value),
PeptideCountFromDecoyDB = Convert.ToInt32(d.Element("Decoy").Value)
}
).ToList();
result[key] = values;
}
return(result);
}
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);
}
public List <OptimalItem> BuildSpectrumBin(IEnumerable <IIdentifiedSpectrum> peptides)
{
GetInteger chargeCalc = GetChargeCalculator();
GetInteger missCleavageCalc = GetMissCleavageCalculator();
IModificationCountCalculator modificationCalc = GetModificationCountCalculator();
GetInteger nptCalc = GetNumProteaseTerminiCalculator();
GetInteger proteinTagCalc = GetProteinTagCalculator();
Dictionary <OptimalResultCondition, OptimalItem> resultMap = new Dictionary <OptimalResultCondition, OptimalItem>();
foreach (IIdentifiedSpectrum mph in peptides)
{
int charge = chargeCalc(mph);
int missCleavage = missCleavageCalc(mph);
int modificationCount = modificationCalc.Calculate(mph.GetMatchSequence());
int nptCount = nptCalc(mph);
int proteinTag = proteinTagCalc(mph);
OptimalResultCondition cond = new OptimalResultCondition(charge, missCleavage, nptCount, modificationCount, mph.ClassificationTag);
if (!resultMap.ContainsKey(cond))
{
OptimalItem item = new OptimalItem();
item.Condition = cond;
item.Spectra.Add(mph);
resultMap[cond] = item;
}
else
{
resultMap[cond].Spectra.Add(mph);
}
}
var result = resultMap.Values.ToList();
if (this.MinimumSpectraPerGroup > 1)
{
result.Sort((m1, m2) => m2.Spectra.Count.CompareTo(m1.Spectra.Count));
for (int i = result.Count - 1; i > 0; i--)
{
if (result[i].Spectra.Count < this.MinimumSpectraPerGroup)
{
result[i - 1].Spectra.AddRange(result[i].Spectra);
result[i - 1].Condition.MergedConditions.Add(result[i].Condition);
result.RemoveAt(i);
}
}
}
result.Sort((m1, m2) => m1.Condition.CompareTo(m2.Condition));
return(result);
}
public int GetConditionSpectrumCount(OptimalResultCondition cond)
{
foreach (var oi in this.OptimalResults)
{
if (oi.Condition == cond)
{
return(oi.Spectra.Count);
}
}
return(0);
}
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);
}
public OptimalItem()
{
Condition = new OptimalResultCondition(-1, -1, -1, -1);
Spectra = new List <IIdentifiedSpectrum>();
Result = new OptimalResult();
}
public OptimalItem GetConditionItem(OptimalResultCondition cond)
{
return(this.OptimalResults.Find(m => m.Condition == cond));
}
