public void test1()
{
string path = @"C:\Users\Rui Zhang\Downloads\ZC_20171218_C16_R1.raw";
ThermoRawSpectrumReader reader = new ThermoRawSpectrumReader();
reader.Init(path);
ISpectrum ms2 = reader.GetSpectrum(7638);
//IProcess processer = new LocalNeighborPicking();
IProcess processer = new WeightedAveraging(new LocalNeighborPicking());
//RidgeLineFinder coeffMatrix = new RidgeLineFinder(1.0, 2, 1, 2);
//IProcess processer = new PeakPickingCWT(coeffMatrix);
ms2 = processer.Process(ms2);
using (StreamWriter outputFile = new StreamWriter(@"C:\Users\Rui Zhang\Downloads\peak.csv"))
{
outputFile.WriteLine("mz,intensity");
foreach (IPeak pk in ms2.GetPeaks())
{
outputFile.WriteLine(pk.GetMZ().ToString() + "," + pk.GetIntensity().ToString());
}
}
}
public void ParallelRun(string path, string outputDir, AveragineType type, ChargerType chargerType)
{
string file = Path.GetFileNameWithoutExtension(path) + ".mgf";
string output = Path.Combine(outputDir, file);
ThermoRawSpectrumReader reader = new ThermoRawSpectrumReader();
LocalMaximaPicking picking = new LocalMaximaPicking(ms1PrcisionPPM);
reader.Init(path);
Dictionary <int, List <int> > scanGroup = new Dictionary <int, List <int> >();
int current = -1;
int start = reader.GetFirstScan();
int end = reader.GetLastScan();
for (int i = start; i < end; i++)
{
if (reader.GetMSnOrder(i) == 1)
{
current = i;
scanGroup[i] = new List <int>();
}
else if (reader.GetMSnOrder(i) == 2)
{
scanGroup[current].Add(i);
}
}
List <MS2Info> ms2Infos = new List <MS2Info>();
Parallel.ForEach(scanGroup, (scanPair) =>
{
if (scanPair.Value.Count > 0)
{
ISpectrum ms1 = reader.GetSpectrum(scanPair.Key);
foreach (int i in scanPair.Value)
{
double mz = reader.GetPrecursorMass(i, reader.GetMSnOrder(i));
List <IPeak> ms1Peaks = FilterPeaks(ms1.GetPeaks(), mz, searchRange);
if (ms1Peaks.Count() == 0)
{
continue;
}
// insert pseudo peaks for large gap
List <IPeak> peaks = new List <IPeak>();
double precision = 0.02;
double last = ms1Peaks.First().GetMZ();
foreach (IPeak peak in ms1Peaks)
{
if (peak.GetMZ() - last > precision)
{
peaks.Add(new GeneralPeak(last + precision / 2, 0));
peaks.Add(new GeneralPeak(peak.GetMZ() - precision / 2, 0));
}
peaks.Add(peak);
last = peak.GetMZ();
}
List <IPeak> majorPeaks = picking.Process(peaks);
ICharger charger = new Patterson();
if (chargerType == ChargerType.Fourier)
{
charger = new Fourier();
}
else if (chargerType == ChargerType.Combined)
{
charger = new PattersonFourierCombine();
}
int charge = charger.Charge(peaks, mz - searchRange, mz + searchRange);
// find evelope cluster
EnvelopeProcess envelope = new EnvelopeProcess();
var cluster = envelope.Cluster(majorPeaks, mz, charge);
if (cluster.Count == 0)
{
continue;
}
// find monopeak
Averagine averagine = new Averagine(type);
BrainCSharp braincs = new BrainCSharp();
MonoisotopicSearcher searcher = new MonoisotopicSearcher(averagine, braincs);
MonoisotopicScore result = searcher.Search(mz, charge, cluster);
double precursorMZ = result.GetMZ();
// write mgf
ISpectrum ms2 = reader.GetSpectrum(i);
IProcess processer = new WeightedAveraging(new LocalNeighborPicking());
ms2 = processer.Process(ms2);
MS2Info ms2Info = new MS2Info
{
PrecursorMZ = result.GetMZ(),
PrecursorCharge = charge,
Scan = ms2.GetScanNum(),
Retention = ms2.GetRetention(),
Peaks = ms2.GetPeaks()
};
lock (resultLock)
{
ms2Infos.Add(ms2Info);
}
}
}
readingProgress.Add(scanGroup.Count);
});
ms2Infos = ms2Infos.OrderBy(m => m.Scan).ToList();
using (FileStream ostrm = new FileStream(output, FileMode.OpenOrCreate, FileAccess.Write))
{
using (StreamWriter writer = new StreamWriter(ostrm))
{
foreach (MS2Info ms2 in ms2Infos)
{
WriteMGF(writer, path + ",SCANS=" + ms2.Scan.ToString() + ",PRECURSOR=" + ms2.PrecursorMZ, ms2.PrecursorMZ, ms2.PrecursorCharge,
ms2.Scan, ms2.Retention * 60, reader.GetActivation(ms2.Scan), ms2.Peaks);
writer.Flush();
}
}
}
// update progress
progress.Add();
}
public Run Read(string path, AveragineType type, ChargerType charger, string defaultDataProcessingRef,
ProgressUpdate updater)
{
Run data = new Run();
// init reader
ThermoRawSpectrumReader reader = new ThermoRawSpectrumReader();
LocalMaximaPicking picking = new LocalMaximaPicking(ms1PrcisionPPM);
IProcess process = new WeightedAveraging(new LocalNeighborPicking());
reader.Init(path);
data.spectrumList = new SpectrumList();
Dictionary <int, Spectrum> spectrumMap = new Dictionary <int, Spectrum>();
int start = reader.GetFirstScan();
int end = reader.GetLastScan();
Dictionary <int, List <int> > scanGroup = new Dictionary <int, List <int> >();
int current = -1;
for (int i = start; i < end; i++)
{
if (reader.GetMSnOrder(i) == 1)
{
current = i;
scanGroup[i] = new List <int>();
}
else if (reader.GetMSnOrder(i) == 2)
{
scanGroup[current].Add(i);
}
}
Parallel.ForEach(scanGroup, (scanPair) => {
if (scanPair.Value.Count > 0)
{
int parentScan = scanPair.Key;
ISpectrum ms1 = null;
List <IPeak> majorPeaks = new List <IPeak>();
Spectrum ms1Spectrum =
ThermoRawRunFactoryHelper.GetMS1Spectrum(ref reader, parentScan, ref ms1);
if (ms1Spectrum != null)
{
lock (resultLock)
{
spectrumMap[parentScan] = ms1Spectrum;
}
}
foreach (int scan in scanPair.Value)
{
Spectrum ms2Spectrum =
ThermoRawRunFactoryHelper.GetMS2Spectrum(ref reader, scan, type, charger, picking, process, ms1);
if (ms2Spectrum != null)
{
lock (resultLock)
{
spectrumMap[scan] = ms2Spectrum;
}
}
}
}
updater(scanGroup.Count);
});
List <Spectrum> spectrumList =
spectrumMap.OrderBy(s => s.Key).Select(s => s.Value).ToList();
data.spectrumList.spectrum = new Spectrum[spectrumList.Count];
spectrumList = spectrumList.OrderBy(x => int.Parse(x.id.Substring(5))).ToList();
for (int i = 0; i < spectrumList.Count; i++)
{
int scan = int.Parse(spectrumList[i].id.Substring(5));
data.spectrumList.spectrum[i] = spectrumList[i];
data.spectrumList.spectrum[i].index = (scan - 1).ToString();
data.spectrumList.spectrum[i].defaultArrayLength = spectrumList[i].defaultArrayLength;
}
data.spectrumList.count = spectrumList.Count.ToString();
data.spectrumList.defaultDataProcessingRef = defaultDataProcessingRef;
return(data);
}
void GenerateTasks()
{
if (Path.GetExtension(msPath) == ".mgf")
{
MGFSpectrumReader reader = new MGFSpectrumReader();
reader.Init(msPath);
Dictionary <int, MS2Spectrum> spectraData = reader.GetSpectrum();
foreach (int scan in spectraData.Keys)
{
MS2Spectrum spectrum = spectraData[scan];
SearchTask searchTask = new SearchTask(spectrum,
spectrum.PrecursorMZ(), spectrum.PrecursorCharge());
tasks.Enqueue(searchTask);
readingCounter.Add(spectraData.Count);
}
}
else
{
ISpectrumReader reader = new ThermoRawSpectrumReader();
LocalMaximaPicking picking = new LocalMaximaPicking();
IProcess process = new WeightedAveraging(new LocalNeighborPicking());
reader.Init(msPath);
int start = reader.GetFirstScan();
int end = reader.GetLastScan();
Dictionary <int, List <int> > scanGroup = new Dictionary <int, List <int> >();
int current = -1;
for (int i = start; i < end; i++)
{
if (reader.GetMSnOrder(i) == 1)
{
current = i;
scanGroup[i] = new List <int>();
}
else if (reader.GetMSnOrder(i) == 2)
{
scanGroup[current].Add(i);
}
}
Parallel.ForEach(scanGroup,
new ParallelOptions {
MaxDegreeOfParallelism = SearchingParameters.Access.ThreadNums
},
(scanPair) =>
{
if (scanPair.Value.Count > 0)
{
ISpectrum ms1 = reader.GetSpectrum(scanPair.Key);
foreach (int i in scanPair.Value)
{
double mz = reader.GetPrecursorMass(i, reader.GetMSnOrder(i));
List <IPeak> ms1Peaks = FilterPeaks(ms1.GetPeaks(), mz, searchRange);
if (ms1Peaks.Count() == 0)
{
continue;
}
ICharger charger = new Patterson();
int charge = charger.Charge(ms1Peaks, mz - searchRange, mz + searchRange);
// insert pseudo peaks for large gap
List <IPeak> peaks = new List <IPeak>();
double precision = 0.02;
double last = ms1Peaks.First().GetMZ();
foreach (IPeak peak in ms1Peaks)
{
if (peak.GetMZ() - last > precision)
{
peaks.Add(new GeneralPeak(last + precision / 2, 0));
peaks.Add(new GeneralPeak(peak.GetMZ() - precision / 2, 0));
}
peaks.Add(peak);
last = peak.GetMZ();
}
List <IPeak> majorPeaks = picking.Process(peaks);
// find evelope cluster
EnvelopeProcess envelope = new EnvelopeProcess();
var cluster = envelope.Cluster(majorPeaks, mz, charge);
if (cluster.Count == 0)
{
continue;
}
// find monopeak
Averagine averagine = new Averagine(AveragineType.GlycoPeptide);
BrainCSharp braincs = new BrainCSharp();
MonoisotopicSearcher searcher = new MonoisotopicSearcher(averagine, braincs);
MonoisotopicScore result = searcher.Search(mz, charge, cluster);
double precursorMZ = result.GetMZ();
// search
ISpectrum ms2 = reader.GetSpectrum(i);
ms2 = process.Process(ms2);
SearchTask searchTask = new SearchTask(ms2, precursorMZ, charge);
tasks.Enqueue(searchTask);
}
}
readingCounter.Add(scanGroup.Count);
});
}
}
