private static float GetSSRCalcHydrophobicityZScore(PeptideSpectralMatch psm, PeptideWithSetModifications Peptide, Dictionary <string, Dictionary <int, Tuple <double, double> > > d)
{
//Using SSRCalc3 but probably any number of different calculators could be used instead. One could also use the CE mobility.
SSRCalc3 calc = new SSRCalc3("SSRCalc 3.0 (300A)", SSRCalc3.Column.A300);
double hydrophobicityZscore = double.NaN;
if (d.ContainsKey(psm.FullFilePath))
{
int time = (int)(2 * Math.Round(psm.ScanRetentionTime / 2d, 0));
if (d[psm.FullFilePath].Keys.Contains(time))
{
double predictedHydrophobicity = calc.ScoreSequence(Peptide);
hydrophobicityZscore = Math.Abs(d[psm.FullFilePath][time].Item1 - predictedHydrophobicity) / d[psm.FullFilePath][time].Item2;
}
}
double maxHydrophobicityZscore = 10; // each "Z" is one standard deviation. so, maxHydrophobicityZscore 10 is quite large
if (double.IsNaN(hydrophobicityZscore) || double.IsInfinity(hydrophobicityZscore) || hydrophobicityZscore > maxHydrophobicityZscore)
{
hydrophobicityZscore = maxHydrophobicityZscore;
}
return((float)hydrophobicityZscore);
}
/// <summary>
///A test for ScoreSequence with 100A column
///</summary>
// Problems with the results from the article
// [TestMethod]
public void ScoreSequence_100A_Test()
{
SSRCalc3 calc = new SSRCalc3(RetentionTimeRegression.SSRCALC_100_A, SSRCalc3.Column.A100);
for (int i = 0; i < _peptides100A.GetLength(0); i++)
{
string peptide = (string)_peptides100A[i, 0];
double expected = (double)_peptides100A[i, 1];
double actual = calc.ScoreSequence(peptide) ?? 0;
// Round the returned value to match the values presented
// in the supporting information of the SSRCalc 3 publication.
// First cast to float, since the added precision of the double
// caused the double representation of 12.805 to round to 12.80
// instead of 12.81. When diffed with 12.81 the result was
// 0.005000000000002558.
double actualRound = Math.Round((float)actual, 2);
// Extra conditional added to improve debugging of issues.
if (Math.Abs(expected - actual) > 0.005)
{
Assert.AreEqual(expected, actualRound, "Peptide {0}", peptide);
}
}
}
public static void SimpleReversePhaseRetentionTimeTest()
{
Dictionary <string, double> peptidesAndHyrophobicities = new Dictionary <string, double>
{
{ "QSHFANAEPEQK", 11.27 },
{ "SDLFENLQNYR", 30.44 },
{ "SLPSEFEPINLR", 33.12 }
};
SSRCalc3 calc = new SSRCalc3("SSRCalc 3.0 (300A)", SSRCalc3.Column.A300);
foreach (string peptideSequence in peptidesAndHyrophobicities.Keys)
{
var peptide = new PeptideWithSetModifications(peptideSequence, new Dictionary <string, Modification>());
double expected = peptidesAndHyrophobicities[peptideSequence];
double actual = calc.ScoreSequence(peptide);
Assert.That(expected, Is.EqualTo(actual).Within(0.01));
}
}
private static Dictionary <string, Dictionary <int, Tuple <double, double> > > ComputeHydrophobicityValues(List <PeptideSpectralMatch> psms, bool computeHydrophobicitiesforModifiedPeptides)
{
SSRCalc3 calc = new SSRCalc3("SSRCalc 3.0 (300A)", SSRCalc3.Column.A300);
//TODO change the tuple so the values have names
Dictionary <string, Dictionary <int, Tuple <double, double> > > rtHydrophobicityAvgDev = new Dictionary <string, Dictionary <int, Tuple <double, double> > >();
List <string> filenames = psms.Select(f => f.FullFilePath).ToList();
filenames = filenames.Distinct().ToList();
foreach (string filename in filenames)
{
Dictionary <int, List <double> > hydrophobicities = new Dictionary <int, List <double> >();
Dictionary <int, Tuple <double, double> > averagesCommaStandardDeviations = new Dictionary <int, Tuple <double, double> >();
foreach (PeptideSpectralMatch psm in psms.Where(f => (f.FullFilePath == filename || f.FullFilePath == null) && f.FdrInfo.QValue <= 0.01 && !f.IsDecoy))
{
List <string> fullSequences = new List <string>();
foreach ((int notch, PeptideWithSetModifications pwsm) in psm.BestMatchingPeptides)
{
if (fullSequences.Contains(pwsm.FullSequence))
{
continue;
}
fullSequences.Add(pwsm.FullSequence);
double predictedHydrophobicity = calc.ScoreSequence(pwsm);
//here i'm grouping this in 2 minute increments becuase there are cases where you get too few data points to get a good standard deviation an average. This is for stability.
int possibleKey = (int)(2 * Math.Round(psm.ScanRetentionTime / 2d, 0));
//First block of if statement is for modified peptides.
if (pwsm.AllModsOneIsNterminus.Any() && computeHydrophobicitiesforModifiedPeptides)
{
if (hydrophobicities.ContainsKey(possibleKey))
{
hydrophobicities[possibleKey].Add(predictedHydrophobicity);
}
else
{
hydrophobicities.Add(possibleKey, new List <double>()
{
predictedHydrophobicity
});
}
}
//this second block of if statment is for unmodified peptides.
else if (!pwsm.AllModsOneIsNterminus.Any() && !computeHydrophobicitiesforModifiedPeptides)
{
if (hydrophobicities.ContainsKey(possibleKey))
{
hydrophobicities[possibleKey].Add(predictedHydrophobicity);
}
else
{
hydrophobicities.Add(possibleKey, new List <double>()
{
predictedHydrophobicity
});
}
}
}
}
List <double> allSquaredHyrophobicityDifferences = new List <double>();
foreach (int retentionTimeBin in hydrophobicities.Keys)
{
//TODO consider using inner-quartile range instead of standard deviation
double averageHydrophobicity = hydrophobicities[retentionTimeBin].Average();
averagesCommaStandardDeviations.Add(retentionTimeBin, new Tuple <double, double>(averageHydrophobicity, hydrophobicities[retentionTimeBin].StandardDeviation()));
foreach (double hydrophobicity in hydrophobicities[retentionTimeBin])
{
double difference = Math.Abs(hydrophobicity - averageHydrophobicity);
if (!double.IsNaN(difference) && difference > 0)
{
allSquaredHyrophobicityDifferences.Add(Math.Pow(difference, 2));
}
}
}
//some standard deviations are too small or too large because of random reasons, so we replace those small numbers of oddballs with reasonable numbers.
double globalStDev = 1;
if (allSquaredHyrophobicityDifferences.Count() > 1)
{
globalStDev = Math.Sqrt(allSquaredHyrophobicityDifferences.Sum() / (allSquaredHyrophobicityDifferences.Count() - 1));
}
Dictionary <int, Tuple <double, double> > stDevsToChange = new Dictionary <int, Tuple <double, double> >();
foreach (KeyValuePair <int, Tuple <double, double> > item in averagesCommaStandardDeviations)
{
//add stability. not allowing stdevs that are too small or too large at one position relative to the global stdev
//here we are finding which stdevs are out of whack.
if (Double.IsNaN(item.Value.Item2) || item.Value.Item2 < 0.5 || (item.Value.Item2 / globalStDev) > 3)
{
Tuple <double, double> pair = new Tuple <double, double>(averagesCommaStandardDeviations[item.Key].Item1, globalStDev);
stDevsToChange.Add(item.Key, pair);
}
}
//here we are replacing the stdevs that are out of whack.
foreach (int key in stDevsToChange.Keys)
{
averagesCommaStandardDeviations[key] = stDevsToChange[key];
}
rtHydrophobicityAvgDev.Add(filename, averagesCommaStandardDeviations);
}
return(rtHydrophobicityAvgDev);
}
//determine if a peptide is unqiue or shared. Also generates in silico peptide objects
Dictionary <Protein, List <InSilicoPep> > DeterminePeptideStatus(string databaseName, Dictionary <Protein, List <PeptideWithSetModifications> > databasePeptides, Parameters userParams)
{
SSRCalc3 RTPrediction = new SSRCalc3("SSRCalc 3.0 (300A)", SSRCalc3.Column.A300);
Dictionary <Protein, List <InSilicoPep> > inSilicoPeptides = new Dictionary <Protein, List <InSilicoPep> >();
if (userParams.TreatModifiedPeptidesAsDifferent == true)
{
foreach (var peptideSequence in databasePeptides.Select(p => p.Value).SelectMany(pep => pep).GroupBy(p => p.FullSequence).ToDictionary(group => group.Key, group => group.ToList()))
{
if (peptideSequence.Value.Select(p => p.Protein).Distinct().Count() == 1)
{
foreach (var peptide in peptideSequence.Value)
{
if (inSilicoPeptides.ContainsKey(peptide.Protein))
{
inSilicoPeptides[peptide.Protein].Add(new InSilicoPep(peptide.BaseSequence, peptide.FullSequence, peptide.PreviousAminoAcid, peptide.NextAminoAcid, true, RTPrediction.ScoreSequence(peptide), GetCifuentesMobility(peptide), peptide.Length, peptide.MonoisotopicMass, databaseName,
peptide.Protein.Accession, peptide.OneBasedStartResidueInProtein, peptide.OneBasedEndResidueInProtein, peptide.DigestionParams.Protease.Name));
}
else
{
inSilicoPeptides.Add(peptide.Protein, new List <InSilicoPep>()
{
new InSilicoPep(peptide.BaseSequence, peptide.FullSequence, peptide.PreviousAminoAcid, peptide.NextAminoAcid, true, RTPrediction.ScoreSequence(peptide), GetCifuentesMobility(peptide), peptide.Length, peptide.MonoisotopicMass, databaseName,
peptide.Protein.Accession, peptide.OneBasedStartResidueInProtein, peptide.OneBasedEndResidueInProtein, peptide.DigestionParams.Protease.Name)
});
}
}
}
else
{
foreach (var peptide in peptideSequence.Value)
{
if (inSilicoPeptides.ContainsKey(peptide.Protein))
{
inSilicoPeptides[peptide.Protein].Add(new InSilicoPep(peptide.BaseSequence, peptide.FullSequence, peptide.PreviousAminoAcid, peptide.NextAminoAcid, false, RTPrediction.ScoreSequence(peptide), GetCifuentesMobility(peptide), peptide.Length, peptide.MonoisotopicMass, databaseName,
peptide.Protein.Accession, peptide.OneBasedStartResidueInProtein, peptide.OneBasedEndResidueInProtein, peptide.DigestionParams.Protease.Name));
}
else
{
inSilicoPeptides.Add(peptide.Protein, new List <InSilicoPep>()
{
new InSilicoPep(peptide.BaseSequence, peptide.FullSequence, peptide.PreviousAminoAcid, peptide.NextAminoAcid, false, RTPrediction.ScoreSequence(peptide), GetCifuentesMobility(peptide), peptide.Length, peptide.MonoisotopicMass, databaseName,
peptide.Protein.Accession, peptide.OneBasedStartResidueInProtein, peptide.OneBasedEndResidueInProtein, peptide.DigestionParams.Protease.Name)
});
}
}
}
}
}
else
{
foreach (var peptideSequence in databasePeptides.Select(p => p.Value).SelectMany(pep => pep).GroupBy(p => p.BaseSequence).ToDictionary(group => group.Key, group => group.ToList()))
{
if (peptideSequence.Value.Select(p => p.Protein).Distinct().Count() == 1)
{
foreach (var peptide in peptideSequence.Value)
{
var hydrophob = RTPrediction.ScoreSequence(peptide);
var em = GetCifuentesMobility(peptide);
if (inSilicoPeptides.ContainsKey(peptide.Protein))
{
inSilicoPeptides[peptide.Protein].Add(new InSilicoPep(peptide.BaseSequence, peptide.FullSequence, peptide.PreviousAminoAcid, peptide.NextAminoAcid, true, hydrophob, em, peptide.Length, peptide.MonoisotopicMass, databaseName,
peptide.Protein.Accession, peptide.OneBasedStartResidueInProtein, peptide.OneBasedEndResidueInProtein, peptide.DigestionParams.Protease.Name));
}
else
{
inSilicoPeptides.Add(peptide.Protein, new List <InSilicoPep>()
{
new InSilicoPep(peptide.BaseSequence, peptide.FullSequence, peptide.PreviousAminoAcid, peptide.NextAminoAcid, true, hydrophob, em, peptide.Length, peptide.MonoisotopicMass, databaseName,
peptide.Protein.Accession, peptide.OneBasedStartResidueInProtein, peptide.OneBasedEndResidueInProtein, peptide.DigestionParams.Protease.Name)
});
}
}
}
else
{
foreach (var peptide in peptideSequence.Value)
{
var hydrophob = RTPrediction.ScoreSequence(peptide);
var em = GetCifuentesMobility(peptide);
if (inSilicoPeptides.ContainsKey(peptide.Protein))
{
inSilicoPeptides[peptide.Protein].Add(new InSilicoPep(peptide.BaseSequence, peptide.FullSequence, peptide.PreviousAminoAcid, peptide.NextAminoAcid, false, hydrophob, em, peptide.Length, peptide.MonoisotopicMass, databaseName,
peptide.Protein.Accession, peptide.OneBasedStartResidueInProtein, peptide.OneBasedEndResidueInProtein, peptide.DigestionParams.Protease.Name));
}
else
{
inSilicoPeptides.Add(peptide.Protein, new List <InSilicoPep>()
{
new InSilicoPep(peptide.BaseSequence, peptide.FullSequence, peptide.PreviousAminoAcid, peptide.NextAminoAcid, false, hydrophob, em, peptide.Length, peptide.MonoisotopicMass, databaseName,
peptide.Protein.Accession, peptide.OneBasedStartResidueInProtein, peptide.OneBasedEndResidueInProtein, peptide.DigestionParams.Protease.Name)
});
}
}
}
}
}
databasePeptides = null;
return(inSilicoPeptides);
}
public void ScoreSequence_300A_Test()
{
SSRCalc3 calc = new SSRCalc3(RetentionTimeRegression.SSRCALC_300_A, SSRCalc3.Column.A300);
for (int i = 0; i < _peptides300A.GetLength(0); i++ )
{
string peptide = (string) _peptides300A[i, 0];
double expected = (double) _peptides300A[i, 1];
double actual = calc.ScoreSequence(peptide) ?? 0;
// Round the returned value to match the values presented
// in the supporting information of the SSRCalc 3 publication.
// First cast to float, since the added precision of the double
// caused the double representation of 12.805 to round to 12.80
// instead of 12.81. When diffed with 12.81 the result was
// 0.005000000000002558.
double actualRound = Math.Round((float) actual, 2);
// Extra conditional added to improve debugging of issues.
if (Math.Abs(expected - actual) > 0.005)
Assert.AreEqual(expected, actualRound, "Peptide {0}", peptide);
}
}
private void linePlot(int plotType)
{
string yAxisTitle = "";
string xAxisTitle = "";
ScatterSeries series = new ScatterSeries
{
MarkerFill = OxyColors.Blue,
MarkerSize = 0.5,
TrackerFormatString = "{1}: {2:0.###}\n{3}: {4:0.###}\nFull sequence: {Tag}"
};
ScatterSeries variantSeries = new ScatterSeries
{
MarkerFill = OxyColors.DarkRed,
MarkerSize = 1.5,
MarkerType = MarkerType.Circle,
TrackerFormatString = "{1}: {2:0.###}\n{3}: {4:0.###}\nFull sequence: {Tag}"
};
List <Tuple <double, double, string> > xy = new List <Tuple <double, double, string> >();
List <Tuple <double, double, string> > variantxy = new List <Tuple <double, double, string> >();
var filteredList = allPsms.Where(p => !p.MassDiffDa.Contains("|") && Math.Round(double.Parse(p.MassDiffDa), 0) == 0).ToList();
var test = allPsms.SelectMany(p => p.MatchedIons.Select(v => v.MassErrorPpm));
switch (plotType)
{
case 1: // Precursor PPM Error vs. RT
yAxisTitle = "Precursor error (ppm)";
xAxisTitle = "Retention time";
foreach (var psm in filteredList)
{
if (psm.IdentifiedSequenceVariations == null || psm.IdentifiedSequenceVariations.Equals(""))
{
xy.Add(new Tuple <double, double, string>(double.Parse(psm.MassDiffPpm), (double)psm.RetentionTime, psm.FullSequence));
}
else
{
variantxy.Add(new Tuple <double, double, string>(double.Parse(psm.MassDiffPpm), (double)psm.RetentionTime, psm.FullSequence));
}
}
break;
case 2: // Fragment PPM Error vs. RT
yAxisTitle = "Retention time";
xAxisTitle = "Fragment error (ppm)";
foreach (var psm in allPsms)
{
foreach (var ion in psm.MatchedIons)
{
xy.Add(new Tuple <double, double, string>((double)psm.RetentionTime, ion.MassErrorPpm, psm.FullSequence));
}
}
break;
case 3: // Predicted RT vs. Observed RT
yAxisTitle = "Predicted retention time";
xAxisTitle = "Observed retention time";
SSRCalc3 sSRCalc3 = new SSRCalc3("A100", SSRCalc3.Column.A100);
foreach (var psm in allPsms)
{
if (psm.IdentifiedSequenceVariations == null || psm.IdentifiedSequenceVariations.Equals(""))
{
xy.Add(new Tuple <double, double, string>(sSRCalc3.ScoreSequence(new PeptideWithSetModifications(psm.BaseSeq.Split('|')[0], null)),
(double)psm.RetentionTime, psm.FullSequence));
}
else
{
variantxy.Add(new Tuple <double, double, string>(sSRCalc3.ScoreSequence(new PeptideWithSetModifications(psm.BaseSeq.Split('|')[0], null)),
(double)psm.RetentionTime, psm.FullSequence));
}
}
break;
}
if (xy.Count != 0)
{
// plot each peptide
IOrderedEnumerable <Tuple <double, double, string> > sorted = xy.OrderBy(x => x.Item1);
foreach (var val in sorted)
{
series.Points.Add(new ScatterPoint(val.Item2, val.Item1, tag: val.Item3));
}
privateModel.Series.Add(series);
// add series displayed in legend, the real series will show up with a tiny dot for the symbol
privateModel.Series.Add(new ScatterSeries {
Title = "non-variant PSMs", MarkerFill = OxyColors.Blue
});
}
if (variantxy.Count != 0)
{
// plot each variant peptide
IOrderedEnumerable <Tuple <double, double, string> > variantSorted = variantxy.OrderBy(x => x.Item1);
foreach (var val in variantSorted)
{
variantSeries.Points.Add(new ScatterPoint(val.Item2, val.Item1, tag: val.Item3));
}
privateModel.Series.Add(variantSeries);
// add series displayed in legend, the real series will show up with a tiny dot for the symbol
privateModel.Series.Add(new ScatterSeries {
Title = "variant PSMs", MarkerFill = OxyColors.DarkRed
});
}
privateModel.Axes.Add(new LinearAxis {
Title = xAxisTitle, Position = AxisPosition.Bottom
});
privateModel.Axes.Add(new LinearAxis {
Title = yAxisTitle, Position = AxisPosition.Left
});
}
private static Dictionary <string, Dictionary <int, Tuple <double, double> > > ComputeHydrophobicityValues(List <PeptideSpectralMatch> psms, bool computeHydrophobicitiesforModifiedPeptides)
{
SSRCalc3 calc = new SSRCalc3("SSRCalc 3.0 (300A)", SSRCalc3.Column.A300);
Dictionary <string, Dictionary <int, Tuple <double, double> > > rtHydrophobicityAvgDev = new Dictionary <string, Dictionary <int, Tuple <double, double> > >();
List <string> filenames = psms.Select(f => f.FullFilePath).ToList();
filenames = filenames.Distinct().ToList();
foreach (string filename in filenames)
{
Dictionary <int, List <double> > hydrobophobicites = new Dictionary <int, List <double> >();
Dictionary <int, Tuple <double, double> > averagesCommaStandardDeviations = new Dictionary <int, Tuple <double, double> >();
foreach (PeptideSpectralMatch psm in psms.Where(f => (f.FullFilePath == filename || f.FullFilePath == null) && f.FdrInfo.QValue <= 0.01))
{
foreach ((int notch, PeptideWithSetModifications pwsm) in psm.BestMatchingPeptides)
{
if (pwsm.AllModsOneIsNterminus.Any() && !computeHydrophobicitiesforModifiedPeptides)
{
double predictedHydrophobicity = calc.ScoreSequence(pwsm);
int possibleKey = (int)Math.Round(psm.ScanRetentionTime, 0);
if (hydrobophobicites.ContainsKey(possibleKey))
{
hydrobophobicites[possibleKey].Add(predictedHydrophobicity);
}
else
{
hydrobophobicites.Add(possibleKey, new List <double>()
{
predictedHydrophobicity
});
}
}
else if (!pwsm.AllModsOneIsNterminus.Any() && computeHydrophobicitiesforModifiedPeptides)
{
double predictedHydrophobicity = calc.ScoreSequence(pwsm);
int possibleKey = (int)Math.Round(psm.ScanRetentionTime, 0);
if (hydrobophobicites.ContainsKey(possibleKey))
{
hydrobophobicites[possibleKey].Add(predictedHydrophobicity);
}
else
{
hydrobophobicites.Add(possibleKey, new List <double>()
{
predictedHydrophobicity
});
}
}
}
}
foreach (int key in hydrobophobicites.Keys)
{
//TODO consider using inner-quartile range instead of standard deviation
averagesCommaStandardDeviations.Add(key, new Tuple <double, double>(hydrobophobicites[key].Average(), hydrobophobicites[key].StandardDeviation()));
}
rtHydrophobicityAvgDev.Add(filename, averagesCommaStandardDeviations);
}
return(rtHydrophobicityAvgDev);
}
//determine if peptides are unique and shared for the speicifc database that they came from (Will do pooled analysis later)
Dictionary <Protein, List <InSilicoPeptide> > DeterminePeptideStatus(Dictionary <Protein, List <PeptideWithSetModifications> > databasePeptides, Parameters userParams)
{
SSRCalc3 RTPrediction = new SSRCalc3("SSRCalc 3.0 (300A)", SSRCalc3.Column.A300);
bool treatModPeptidesAsDifferent = userParams.TreatModifiedPeptidesAsDifferent;
Dictionary <string, (List <PeptideWithSetModifications>, HashSet <Protein>)> peptidesToProteins = new Dictionary <string, (List <PeptideWithSetModifications>, HashSet <Protein>)>();
foreach (var protein in databasePeptides)
{
if (treatModPeptidesAsDifferent)
{
//use full sequences
foreach (var peptide in protein.Value)
{
if (peptidesToProteins.ContainsKey(peptide.FullSequence))
{
peptidesToProteins[peptide.FullSequence].Item1.Add(peptide);
peptidesToProteins[peptide.FullSequence].Item2.Add(protein.Key);
}
else
{
peptidesToProteins.Add(peptide.FullSequence, (new List <PeptideWithSetModifications>()
{
peptide
}, new HashSet <Protein>()
{
protein.Key
}));
}
}
}
else
{
//use base sequences
foreach (var peptide in protein.Value)
{
if (peptidesToProteins.ContainsKey(peptide.BaseSequence))
{
peptidesToProteins[peptide.BaseSequence].Item1.Add(peptide);
peptidesToProteins[peptide.BaseSequence].Item2.Add(protein.Key);
}
else
{
peptidesToProteins.Add(peptide.BaseSequence, (new List <PeptideWithSetModifications>()
{
peptide
}, new HashSet <Protein>()
{
protein.Key
}));
}
}
}
}
var sharedPeptides = peptidesToProteins.Select(p => p.Value).Where(p => p.Item2.Count >= 2).Select(p => p.Item1).SelectMany(p => p).ToList();
var uniquePeptides = peptidesToProteins.Select(p => p.Value).Where(p => p.Item2.Count == 1).Select(p => p.Item1).SelectMany(p => p).ToList();
List <InSilicoPeptide> inSilicoPeptides = new List <InSilicoPeptide>();
foreach (var peptide in sharedPeptides)
{
var pep = new InSilicoPeptide(peptide.Protein, peptide.DigestionParams, peptide.OneBasedStartResidueInProtein, peptide.OneBasedEndResidueInProtein,
CleavageSpecificity.Full, peptide.PeptideDescription, peptide.MissedCleavages, peptide.AllModsOneIsNterminus, peptide.NumFixedMods,
peptide.BaseSequence, false);
var hydrophob = RTPrediction.ScoreSequence(pep);
var em = GetCifuentesMobility(peptide);
pep.SetHydrophobicity(hydrophob);
pep.SetElectrophoreticMobility(em);
inSilicoPeptides.Add(pep);
}
foreach (var peptide in uniquePeptides)
{
var pep = new InSilicoPeptide(peptide.Protein, peptide.DigestionParams, peptide.OneBasedStartResidueInProtein, peptide.OneBasedEndResidueInProtein,
CleavageSpecificity.Full, peptide.PeptideDescription, peptide.MissedCleavages, peptide.AllModsOneIsNterminus, peptide.NumFixedMods,
peptide.BaseSequence, true);
var hydrophob = RTPrediction.ScoreSequence(pep);
var em = GetCifuentesMobility(peptide);
pep.SetHydrophobicity(hydrophob);
pep.SetElectrophoreticMobility(em);
inSilicoPeptides.Add(pep);
}
var labeledPeptides = inSilicoPeptides.GroupBy(p => p.Protein).ToDictionary(group => group.Key, group => group.ToList());
return(labeledPeptides);
}
