public static void ProjectMerge(PeptidAce.Utilities.Interfaces.IConSol console)
{
string strProjectAll = @"C:\_IRIC\Data\NB\ProjectFile_EverythingReplicates_Oct.csv";
string project = @"C:\_IRIC\Data\NB\ProjectTest_AllAce_Spiked_19Oct.csv";
string fastaFile = @"C:\_IRIC\Data\NB\peptide.fasta";
DBOptions options = PositionnalIsomerSolver.CreateOptions(fastaFile, @"C:\_IRIC\Data\NB\Units\", 8, 0.05, console);
Samples samplesMixed = new Samples(strProjectAll, 0, options);
Samples samplesSynth = new Samples(project, 0, options);
PositionnalIsomerSolver newSolver = new PositionnalIsomerSolver();
newSolver.precTolPpm = 15;
newSolver.prodTolDa = 0.05;
newSolver.nbMinFragments = 5;
newSolver.nbMaxFragments = 5;
string[] synths = new string[samplesSynth.Count];
for (int i = 0; i < synths.Length; i++)
{
synths[i] = samplesSynth[i].sSDF;
}
string[] mixed = new string[samplesMixed.Count];
for (int i = 0; i < mixed.Length; i++)
{
mixed[i] = samplesMixed[i].sSDF;
}
newSolver.Solve(synths, mixed, fastaFile, Utilities.vsCSV.GetFolder(mixed[0]), options.ConSole);
//Precompute Spiked peptide identifications
Result SpikedResult = Ace.Start(options, samplesSynth, false, false);
Result mixedResult = Ace.Start(options, samplesMixed, false, false);
//Compute all usable spiked peptides
Dictionary <double, Dictionary <Sample, CharacterizedPrecursor> > characterizedPeptides = CharacterizedPrecursor.GetSpikedPrecursors(samplesSynth, SpikedResult, options, newSolver.nbMinFragments, newSolver.nbMaxFragments);
Dictionary <Sample, List <MixedPrecursor> > mixedPrecursors = new Dictionary <Sample, List <MixedPrecursor> >();
foreach (Sample mixedSample in samplesMixed)
{
mixedPrecursors.Add(mixedSample, MixedPrecursor.GetMixedPrecursors(mixedSample, mixedResult, options, characterizedPeptides));
}
Dictionary <Sample, List <Dictionary <CharacterizedPrecursor, MaxFlowElutionCurve> > > results = new Dictionary <Sample, List <Dictionary <CharacterizedPrecursor, MaxFlowElutionCurve> > >();
//Get the list of precursors to characterize
foreach (Sample mixedSample in samplesMixed)
{
foreach (double keyMz in characterizedPeptides.Keys)
{
//List<Dictionary<CharacterizedPrecursor, MaxFlowElutionCurve>> listOfRatios = new List<Dictionary<CharacterizedPrecursor, MaxFlowElutionCurve>>();
foreach (MixedPrecursor mPrec in mixedPrecursors[mixedSample])
{
if (mPrec.MZ == keyMz)
{
// Compute Max Flow for this precursor
Dictionary <CharacterizedPrecursor, MaxFlowElutionCurve> ratios = PositionnalIsomerSolver.GetRatios(characterizedPeptides, mPrec, options, newSolver.nbMinFragments, newSolver.nbMaxFragments);
if (!results.ContainsKey(mixedSample))
{
results.Add(mixedSample, new List <Dictionary <CharacterizedPrecursor, MaxFlowElutionCurve> >());
}
results[mixedSample].Add(ratios);
}
}
}
}
List <CharacterizedPrecursor> precursors = new List <CharacterizedPrecursor>();
foreach (Dictionary <Sample, CharacterizedPrecursor> dic in characterizedPeptides.Values)
{
foreach (CharacterizedPrecursor cP in dic.Values)
{
precursors.Add(cP);
}
}
//Create average of each characterized peptide plus standard deviance
vsCSVWriter writerArea = new vsCSVWriter(@"C:\_IRIC\Data\NB\Merge\stats_Area.csv");
string lineC = "Count,";
foreach (CharacterizedPrecursor cP in precursors)
{
lineC += cP.Peptide.Sequence + ",";
}
lineC += "Intensity per ms,";
foreach (CharacterizedPrecursor cP in precursors)
{
lineC += cP.Peptide.Sequence + ",";
}
lineC += "Standard Deviation Count,";
foreach (CharacterizedPrecursor cP in precursors)
{
lineC += cP.Peptide.Sequence + ",";
}
lineC += "Standard Deviation per ms,";
foreach (CharacterizedPrecursor cP in precursors)
{
lineC += cP.Peptide.Sequence + ",";
}
writerArea.AddLine(lineC);
foreach (int cond in samplesMixed.GetConditions())
{
Dictionary <CharacterizedPrecursor, Dictionary <int, MaxFlowElutionCurve> > deconvoluted = new Dictionary <CharacterizedPrecursor, Dictionary <int, MaxFlowElutionCurve> >();
string sampleName = "";
foreach (Sample mixedSample in results.Keys)
{
if (mixedSample.PROJECT.CONDITION == cond)
{
sampleName = vsCSV.GetFileName_NoExtension(mixedSample.sSDF);
foreach (Dictionary <CharacterizedPrecursor, MaxFlowElutionCurve> ratio in results[mixedSample])
{
foreach (CharacterizedPrecursor cP in ratio.Keys)
{
if (ratio[cP].eCurveCount.Area > 0)
{
if (!deconvoluted.ContainsKey(cP))
{
deconvoluted.Add(cP, new Dictionary <int, MaxFlowElutionCurve>());
}
if (deconvoluted[cP].ContainsKey(mixedSample.PROJECT.REPLICATE))
{
if (deconvoluted[cP][mixedSample.PROJECT.REPLICATE].eCurveCount.Area < ratio[cP].eCurveCount.Area)
{
deconvoluted[cP][mixedSample.PROJECT.REPLICATE] = ratio[cP];
}
}
else
{
deconvoluted[cP].Add(mixedSample.PROJECT.REPLICATE, ratio[cP]);
}
//deconvoluted[cP].Add(ratio[cP]);
}
}
}
}
}
Dictionary <int, double> totalIntensityCount = new Dictionary <int, double>();
Dictionary <int, double> totalIntensityPerMs = new Dictionary <int, double>();
foreach (CharacterizedPrecursor cP in precursors)
{
if (deconvoluted.ContainsKey(cP))
{
foreach (int keyRep in deconvoluted[cP].Keys)
//foreach (MaxFlowElutionCurve curve in deconvoluted[cP])
{
if (!totalIntensityCount.ContainsKey(keyRep))
{
totalIntensityCount.Add(keyRep, 0.0);
totalIntensityPerMs.Add(keyRep, 0.0);
}
MaxFlowElutionCurve curve = deconvoluted[cP][keyRep];
totalIntensityCount[keyRep] += curve.eCurveCount.Area;
totalIntensityPerMs[keyRep] += curve.eCurvePerMs.Area;
}
}
}
string lineArea = sampleName + ",";
string lineMS = ",";
string stdDevCount = "";
string stdDevMS = "";
//1) Compute an average out of the replicates
foreach (CharacterizedPrecursor cP in precursors)
{
if (deconvoluted.ContainsKey(cP))
{
double averageAreaMS = 0;
double averageAreaCount = 0;
foreach (MaxFlowElutionCurve curve in deconvoluted[cP].Values)
{
averageAreaCount += curve.eCurveCount.Area;
averageAreaMS += curve.eCurvePerMs.Area;
}
if (averageAreaCount > 0)
{
averageAreaCount = (averageAreaCount / ((double)deconvoluted[cP].Count));
averageAreaMS = (averageAreaMS / ((double)deconvoluted[cP].Count));
double deNormAverageCount = 0.0;
double deNormAveragePerMs = 0.0;
List <double> repAreaCount = new List <double>();
List <double> repAreaMS = new List <double>();
foreach (int keyRep in deconvoluted[cP].Keys)
{
MaxFlowElutionCurve curve = deconvoluted[cP][keyRep];
double tmpCount = (curve.eCurveCount.Area / totalIntensityCount[keyRep]) * averageAreaCount;
deNormAverageCount += tmpCount;
repAreaCount.Add(tmpCount);
double tmpPerMs = (curve.eCurvePerMs.Area / totalIntensityPerMs[keyRep]) * averageAreaMS;
deNormAveragePerMs += tmpPerMs;
repAreaMS.Add(tmpPerMs);
}
lineArea += (deNormAverageCount / ((double)repAreaCount.Count)) + ",";
lineMS += (deNormAveragePerMs / ((double)repAreaMS.Count)) + ",";
if (repAreaCount.Count > 1)
{
stdDevCount += MathNet.Numerics.Statistics.ArrayStatistics.StandardDeviation(repAreaCount.ToArray()) + ",";
stdDevMS += MathNet.Numerics.Statistics.ArrayStatistics.StandardDeviation(repAreaMS.ToArray()) + ",";
}
else
{
stdDevCount += ",";
stdDevMS += ",";
}
}
else
{
lineArea += ",";
lineMS += ",";
stdDevCount += ",";
stdDevMS += ",";
}
}
else
{
lineArea += ",";
lineMS += ",";
stdDevCount += ",";
stdDevMS += ",";
}
}
writerArea.AddLine(lineArea + lineMS + "," + stdDevCount + "," + stdDevMS);
//2) Add replicates results (to use for standard deviation)
}
writerArea.WriteToFile();
}
/// <summary>
/// Provides deconvoluted elution curves of mixed spectra from the provided raw files using the provided synthetic raw file
/// Exports in CSV files and stores everything in class objects
/// </summary>
/// <param name="spikedRaws"></param>
/// <param name="mixedRaws"></param>
/// <param name="fastaFile"></param>
/// <param name="folderToOutputTo"></param>
/// <param name="conSol"></param>
public void Solve(string[] spikedRaws, string[] mixedRaws, string fastaFile, string folderToOutputTo, IConSol conSol)
{
dbOptions = CreateOptions(fastaFile, folderToOutputTo, precTolPpm, prodTolDa, conSol);
SpikedSamples = new Samples(dbOptions);
for (int i = 0; i < spikedRaws.Length; i++)
{
SpikedSamples.Add(new Sample(i + 1, 1, 1, spikedRaws[i], spikedRaws[i], 0, ""));
}
//Precompute Spiked peptide identifications
SpikedResult = Ace.Start(dbOptions, SpikedSamples, false, false);
SpikedResult.ExportPSMs(1, dbOptions.OutputFolder + "Identifications" + System.IO.Path.DirectorySeparatorChar + "SpikedSamplesPSMs.csv");
MixedSamples = new Samples(dbOptions);
for (int i = 0; i < mixedRaws.Length; i++)
{
MixedSamples.Add(new Sample(i + 1, 1, 1, mixedRaws[i], mixedRaws[i], 0, ""));
}
//Precompute Mixed peptide identifications
mixedResult = Ace.Start(dbOptions, MixedSamples, false, false);
if (mixedResult == null)
{
conSol.WriteLine("OOPS! No queries could be extracted from the list of mixed spectrum files...");
}
else
{
mixedResult.ExportPSMs(1, dbOptions.OutputFolder + "Identifications" + System.IO.Path.DirectorySeparatorChar + "MixedSamplesPSMs.csv");
conSol.WriteLine("Computing gradient descents...");
//Compute all usable spiked peptides
characterizedPeptides = CharacterizedPrecursor.GetSpikedPrecursors(SpikedSamples, SpikedResult, dbOptions, nbMinFragments, nbMaxFragments);
ExportSpikedSampleResult(characterizedPeptides, dbOptions);
vsCSVWriter writerCumul = new vsCSVWriter(OutputFolder + "Results.csv");
string titleCombined = "Mixed Sample,Precursor";
string curveStr = "Polynomial Curve,";
string spikedIntensityStr = "Area under the curve,";
foreach (double precursor in characterizedPeptides.Keys)
{
foreach (CharacterizedPrecursor charPrec in characterizedPeptides[precursor].Values)
{
titleCombined += "," + charPrec.Peptide.Sequence + " Charge " + charPrec.Charge;
if (charPrec.eCurveIntensityCount.Coefficients != null && charPrec.eCurveIntensityCount.Coefficients.Length == 3)
{
curveStr += "," + charPrec.eCurveIntensityCount.Coefficients[0] + "x^2 + " + charPrec.eCurveIntensityCount.Coefficients[1] + "x" + charPrec.eCurveIntensityCount.Coefficients[2];
}
else
{
curveStr += ",NA";
}
spikedIntensityStr += "," + charPrec.eCurveIntensityCount.Area;
}
}
writerCumul.AddLine(titleCombined);
writerCumul.AddLine(curveStr);
writerCumul.AddLine(spikedIntensityStr);
mixedPrecursors = new Dictionary <Sample, List <MixedPrecursor> >();
foreach (Sample mixedSample in MixedSamples)
{
mixedPrecursors.Add(mixedSample, MixedPrecursor.GetMixedPrecursors(mixedSample, mixedResult, dbOptions, characterizedPeptides));
}
//Get the list of precursors to characterize
foreach (Sample mixedSample in MixedSamples)
{
foreach (double keyMz in characterizedPeptides.Keys)
{
List <Dictionary <CharacterizedPrecursor, MaxFlowElutionCurve> > listOfRatios = new List <Dictionary <CharacterizedPrecursor, MaxFlowElutionCurve> >();
foreach (MixedPrecursor mPrec in mixedPrecursors[mixedSample])
{
if (mPrec.MZ == keyMz)
{
// Compute Max Flow for this precursor
Dictionary <CharacterizedPrecursor, MaxFlowElutionCurve> ratios = GetRatios(characterizedPeptides, mPrec, dbOptions, nbMinFragments, nbMaxFragments);
listOfRatios.Add(ratios);
ExportMixedSampleResult(ratios, mixedSample, mPrec, keyMz, dbOptions);
}
}
bool isEmpty = true;
string resultStr = vsCSV.GetFileName(mixedSample.sSDF) + "," + keyMz;
foreach (double precursor in characterizedPeptides.Keys)
{
foreach (CharacterizedPrecursor charPrec in characterizedPeptides[precursor].Values)
{
double cumulArea = 0.0;
foreach (Dictionary <CharacterizedPrecursor, MaxFlowElutionCurve> ratios in listOfRatios)
{
if (ratios.ContainsKey(charPrec))
{
cumulArea += ratios[charPrec].eCurvePerMs.Area;
}
}
resultStr += "," + cumulArea;
if (cumulArea > 0)
{
isEmpty = false;
}
}
}
if (!isEmpty)
{
writerCumul.AddLine(resultStr);
}
}
}
writerCumul.WriteToFile();
//List Modifications
Dictionary <Modification, double> dicOfIntensityPerMod = new Dictionary <Modification, double>();
foreach (Sample sample in mixedPrecursors.Keys)
{
foreach (MixedPrecursor mP in mixedPrecursors[sample])
{
foreach (CharacterizedPrecursor cP in mP.PeptideRatios.Keys)
{
if (cP.Peptide.VariableModifications != null)
{
foreach (Modification mod in cP.Peptide.VariableModifications.Values)
{
if (!dicOfIntensityPerMod.ContainsKey(mod))
{
dicOfIntensityPerMod.Add(mod, 0.0);
}
}
}
}
}
}
//Compute site occupancy for identical sequences (real positionnal isomers)
vsCSVWriter writerSitesOccupancy = new vsCSVWriter(OutputFolder + "Results_SiteOccupancy.csv");
List <Protein> AllProteins = Ace.ReadProteomeFromFasta(fastaFile, false, dbOptions);
foreach (Protein protein in AllProteins)
{
string newTitleProtein = protein.Description.Replace(',', ' ') + "," + protein.Sequence;
for (int i = 0; i < protein.Sequence.Length; i++)
{
newTitleProtein += "," + protein[i].ToString();
}
writerSitesOccupancy.AddLine(newTitleProtein);
foreach (Sample mixedSample in mixedPrecursors.Keys)
{
string coverage = "Coverage," + mixedSample.Name;
for (int i = 0; i < protein.Sequence.Length; i++)
{
double cumulSite = 0.0;
newTitleProtein += "," + protein[i].ToString();
foreach (MixedPrecursor mP in mixedPrecursors[mixedSample])
{
foreach (CharacterizedPrecursor cP in mP.PeptideRatios.Keys)
{
if (i + 1 >= cP.Peptide.StartResidueNumber && i + 1 <= cP.Peptide.EndResidueNumber)
{
cumulSite += mP.PeptideRatios[cP].eCurvePerMs.Area;
}
}
}
coverage += "," + cumulSite;
}
writerSitesOccupancy.AddLine(coverage);
}
foreach (Modification mod in dicOfIntensityPerMod.Keys)
{
Dictionary <Sample, string> dicOfLines = new Dictionary <Sample, string>();
for (int i = 0; i < protein.Sequence.Length; i++)
{
foreach (Sample mixedSample in mixedPrecursors.Keys)
{
double cumulModArea = 0.0;
foreach (MixedPrecursor mP in mixedPrecursors[mixedSample])
{
foreach (CharacterizedPrecursor cP in mP.PeptideRatios.Keys)
{
if (i + 1 >= cP.Peptide.StartResidueNumber && i + 1 <= cP.Peptide.EndResidueNumber &&
cP.Peptide.VariableModifications != null)
{
foreach (int pos in cP.Peptide.VariableModifications.Keys)
{
if (cP.Peptide.StartResidueNumber + pos - 2 == i + 1 && cP.Peptide.VariableModifications[pos] == mod)
{
cumulModArea += mP.PeptideRatios[cP].eCurvePerMs.Area;
}
}
}
}
}
if (!dicOfLines.ContainsKey(mixedSample))
{
dicOfLines.Add(mixedSample, mod.Description + "," + mixedSample.Name + "," + cumulModArea);
}
else
{
dicOfLines[mixedSample] += "," + cumulModArea;
}
}
}
foreach (string line in dicOfLines.Values)
{
writerSitesOccupancy.AddLine(line);
}
}
}
writerSitesOccupancy.WriteToFile();
}
}
public void Solve(string[] mixedRaws, string fastaFile, string folderToOutputTo, IConSol conSol)
{
dbOptions = CreateOptions(fastaFile, folderToOutputTo, conSol);
MixedSamples = new Samples(dbOptions);
for (int i = 0; i < mixedRaws.Length; i++)
{
MixedSamples.Add(new Sample(i + 1, 1, 1, mixedRaws[i], mixedRaws[i], 0, ""));
}
//Precompute Mixed peptide identifications
mixedResult = Ace.Start(dbOptions, MixedSamples, false, false);
conSol.WriteLine("Computing gradient descents...");
//Compute all usable spiked peptides
characterizedPeptides = CharacterizedPrecursor.GetSpikedPrecursors(MixedSamples, mixedResult, dbOptions, nbMinFragments, nbMaxFragments);
ExportSpikedSampleResult(characterizedPeptides, dbOptions);
vsCSVWriter writerCumul = new vsCSVWriter(OutputFolder + "Results.csv");
string titleCombined = "Mixed Sample,Precursor";
string curveStr = "Polynomial Curve,";
string spikedIntensityStr = "Area under the curve,";
foreach (double precursor in characterizedPeptides.Keys)
{
foreach (CharacterizedPrecursor charPrec in characterizedPeptides[precursor].Values)
{
titleCombined += "," + charPrec.Peptide.Sequence + " Charge " + charPrec.Charge;
if (charPrec.eCurveIntensityCount.Coefficients != null && charPrec.eCurveIntensityCount.Coefficients.Length == 3)
{
curveStr += "," + charPrec.eCurveIntensityCount.Coefficients[0] + "x^2 + " + charPrec.eCurveIntensityCount.Coefficients[1] + "x" + charPrec.eCurveIntensityCount.Coefficients[2];
}
else
{
curveStr += ",NA";
}
spikedIntensityStr += "," + charPrec.eCurveIntensityCount.Area;
}
}
writerCumul.AddLine(titleCombined);
writerCumul.AddLine(curveStr);
writerCumul.AddLine(spikedIntensityStr);
//mixedPrecursors = new Dictionary<Sample, Dictionary<double, MixedPrecursor>>();
mixedPrecursors = new Dictionary <Sample, List <MixedPrecursor> >();
foreach (Sample mixedSample in MixedSamples)
{
mixedPrecursors.Add(mixedSample, MixedPrecursor.GetMixedPrecursors(mixedSample, mixedResult, dbOptions, characterizedPeptides));
}
//Get the list of precursors to characterize
foreach (Sample mixedSample in MixedSamples)
{
foreach (double keyMz in characterizedPeptides.Keys)
{
List <Dictionary <Peptide, MaxFlowElutionCurve> > listOfRatios = new List <Dictionary <Peptide, MaxFlowElutionCurve> >();
foreach (MixedPrecursor mPrec in mixedPrecursors[mixedSample])
{
if (mPrec.MZ == keyMz)
{
// Compute Max Flow for this precursor
Dictionary <Peptide, MaxFlowElutionCurve> ratios = GetRatiosNoSpikes(mPrec, precision);
listOfRatios.Add(ratios);
ExportMixedSampleResult(ratios, mixedSample, mPrec, keyMz, dbOptions);
}
}
/*
* string resultStr = vsCSV.GetFileName(mixedSample.sSDF) + "," + keyMz;
* foreach (double precursor in characterizedPeptides.Keys)
* {
* foreach (Peptide charPrec in characterizedPeptides[precursor].Values)
* {
* double cumulArea = 0.0;
* foreach (Dictionary<Peptide, ElutionCurve> ratios in listOfRatios)
* if (ratios.ContainsKey(charPrec))
* cumulArea += ratios[charPrec].Area;
* resultStr += "," + cumulArea;
* }
* }
* writerCumul.AddLine(resultStr);//*/
}
}
writerCumul.WriteToFile();
}