示例#1
0
        private static RegressionLine CalcConversion(IList <TimeScorePair> listPepCorr, int minCount)
        {
            var listTime  = listPepCorr.Select(p => p.Time).ToList();
            var listScore = listPepCorr.Select(p => p.Score).ToList();

            return(IrtRegression.TryGet <RegressionLine>(listScore, listTime, minCount, out var line)
                ? (RegressionLine)line
                : null);
        }
示例#2
0
        private bool TryGetCirtRegression(int count, out RegressionLine regression, out List <ScoredPeptide> peptides)
        {
            peptides = new List <ScoredPeptide>(_cirtPeptides);
            var rts           = _cirtPeptides.Select(pep => pep.Peptide.RetentionTime).ToList();
            var irts          = _cirtPeptides.Select(pep => _cirtAll[pep.Peptide.Target]).ToList();
            var removedValues = new List <Tuple <double, double> >();
            var success       = IrtRegression.TryGet <RegressionLine>(rts, irts, count, out var line, removedValues);

            regression = (RegressionLine)line;
            if (!success)
            {
                return(false);
            }

            for (var i = peptides.Count - 1; i >= 0; i--)
            {
                if (removedValues.Contains(Tuple.Create(rts[i], irts[i])))
                {
                    peptides.RemoveAt(i);
                }
            }
            return(peptides.Count >= count);
        }
示例#3
0
        public RetentionTimeProviderData(IrtRegressionType regressionType, IRetentionTimeProvider retentionTimes,
                                         IReadOnlyList <DbIrtPeptide> standardPeptides, IReadOnlyList <DbIrtPeptide> heavyStandardPeptides)
        {
            RetentionTimeProvider = retentionTimes;

            Peptides = new List <Peptide>(standardPeptides.Count);
            for (var i = 0; i < standardPeptides.Count; i++)
            {
                var heavy    = heavyStandardPeptides[i] != null;
                var standard = heavy ? heavyStandardPeptides[i] : standardPeptides[i];
                var rt       = retentionTimes.GetRetentionTime(standard.ModifiedTarget);
                if (!rt.HasValue && heavy)
                {
                    standard = standardPeptides[i];
                    rt       = retentionTimes.GetRetentionTime(standard.ModifiedTarget);
                }
                Peptides.Add(new Peptide(standard.ModifiedTarget, rt, standard.Irt));
            }
            Peptides.Sort((x, y) => x.Irt.CompareTo(y.Irt));

            if (!FilteredPeptides.Any())
            {
                Regression        = null;
                RegressionRefined = null;
                RegressionSuccess = false;
            }

            var filteredRt  = FilteredPeptides.Select(pep => pep.RetentionTime.Value).ToList();
            var filteredIrt = FilteredPeptides.Select(pep => pep.Irt).ToList();
            var removed     = new List <Tuple <double, double> >();

            if (ReferenceEquals(regressionType, IrtRegressionType.LINEAR))
            {
                Regression = new RegressionLine(filteredRt.ToArray(), filteredIrt.ToArray());
            }
            else if (ReferenceEquals(regressionType, IrtRegressionType.LOGARITHMIC))
            {
                Regression = new LogRegression(filteredRt, filteredIrt);
            }
            else if (ReferenceEquals(regressionType, IrtRegressionType.LOWESS))
            {
                Regression = new LoessRegression(filteredRt.ToArray(), filteredIrt.ToArray());
            }
            else
            {
                throw new ArgumentException();
            }

            IIrtRegression regressionRefined;

            if (IrtRegression.Accept(Regression, MinPoints))
            {
                regressionRefined = Regression;
                Regression        = null;
                RegressionSuccess = true;
            }
            else
            {
                RegressionSuccess = IrtRegression.TryGet(Regression, filteredRt, filteredIrt, MinPoints, out regressionRefined, removed);
            }

            RegressionRefined = regressionRefined;
            foreach (var remove in removed)
            {
                for (var i = 0; i < Peptides.Count; i++)
                {
                    var peptide = Peptides[i];
                    if (peptide.RetentionTime.Equals(remove.Item1) && peptide.Irt.Equals(remove.Item2))
                    {
                        Peptides[i] = new Peptide(peptide, true);
                    }
                }
            }
        }
示例#4
0
        public static ProcessedIrtAverages ProcessRetentionTimesCirt(IProgressMonitor monitor,
                                                                     IRetentionTimeProvider[] providers, DbIrtPeptide[] cirtPeptides, int numCirt, IrtRegressionType regressionType, out DbIrtPeptide[] chosenCirtPeptides)
        {
            chosenCirtPeptides = new DbIrtPeptide[0];

            var irts         = new TargetMap <DbIrtPeptide>(IrtStandard.CIRT.Peptides.Select(pep => new KeyValuePair <Target, DbIrtPeptide>(pep.ModifiedTarget, pep)));
            var targetRts    = new Dictionary <Target, List <double> >();
            var targetCounts = new Dictionary <Target, int>(); // count how many successful regressions each peptide participated in

            foreach (var provider in providers)
            {
                if (monitor.IsCanceled)
                {
                    return(null);
                }

                var times = (
                    from pep in cirtPeptides
                    let rt = provider.GetRetentionTime(pep.ModifiedTarget)
                             where rt.HasValue
                             select Tuple.Create(pep.ModifiedTarget, rt.Value, irts[pep.ModifiedTarget].Irt)).ToList();

                foreach (var(target, rt, _) in times)
                {
                    if (targetRts.TryGetValue(target, out var list))
                    {
                        list.Add(rt);
                    }
                    else
                    {
                        targetRts[target] = new List <double> {
                            rt
                        }
                    };
                }

                var removed = new List <Tuple <double, double> >();
                if (!IrtRegression.TryGet <RegressionLine>(times.Select(t => t.Item2).ToList(), times.Select(t => t.Item3).ToList(),
                                                           MIN_PEPTIDES_COUNT, out _, removed))
                {
                    continue;
                }
                foreach (var(removeRt, removeIrt) in removed)
                {
                    times.Remove(times.First(time => time.Item2.Equals(removeRt) && time.Item3.Equals(removeIrt)));
                }
                foreach (var(target, _, _) in times)
                {
                    targetCounts[target] = targetCounts.TryGetValue(target, out var existing) ? existing + 1 : 1;
                }
            }

            // for each target, only keep median retention time
            var dupTargets = targetRts.Where(kvp => kvp.Value.Count > 1).Select(kvp => kvp.Key).ToArray();

            foreach (var target in dupTargets)
            {
                targetRts[target] = new List <double> {
                    new Statistics(targetRts[target]).Median()
                }
            }
            ;

            // separate targets into equal retention time bins
            var candidateBins = new List <Tuple <Target, double> > [numCirt];

            for (var i = 0; i < candidateBins.Length; i++)
            {
                candidateBins[i] = new List <Tuple <Target, double> >();
            }

            var minRt = double.MaxValue;
            var maxRt = -1d;

            foreach (var rt in targetRts.Values.Select(list => list.First()))
            {
                if (rt < minRt)
                {
                    minRt = rt;
                }
                if (rt > maxRt)
                {
                    maxRt = rt;
                }
            }

            var binSize    = (maxRt - minRt) / numCirt;
            var lastBinIdx = candidateBins.Length - 1;

            foreach (var target in targetRts)
            {
                foreach (var rt in target.Value)
                {
                    candidateBins[Math.Min((int)((rt - minRt) / binSize), lastBinIdx)].Add(Tuple.Create(target.Key, rt));
                }
            }

            Tuple <Target, double> GetBest(List <Tuple <Target, double> > bin, int binIdx, out int bestCount, out double bestRtDelta)
            {
                if (bin.Count == 0)
                {
                    bestCount   = 0;
                    bestRtDelta = 0;
                    return(null);
                }

                bestCount = 0;
                var filtered = new List <Tuple <Target, double> >();

                foreach (var t in bin)
                {
                    if (!targetCounts.TryGetValue(t.Item1, out var count))
                    {
                        continue;
                    }
                    if (count > bestCount)
                    {
                        bestCount = count;
                        filtered.Clear();
                        filtered.Add(t);
                    }
                    else if (count == bestCount)
                    {
                        filtered.Add(t);
                    }
                }
                if (filtered.Count == 0)
                {
                    filtered = bin;
                }
                var targetRt = ((minRt + binSize * binIdx) + (minRt + binSize * (binIdx + 1))) / 2;
                var closest  = filtered.Aggregate((x, y) => Math.Abs(x.Item2 - targetRt) < Math.Abs(y.Item2 - targetRt) ? x : y);

                bestRtDelta = Math.Abs(closest.Item2 - targetRt);
                return(closest);
            }

            var chosenList = new List <DbIrtPeptide>();
            var emptyBins  = new HashSet <int>();

            for (var i = 0; i < candidateBins.Length; i++)
            {
                var bin = candidateBins[i];
                if (bin.Count > 0)
                {
                    // choose the best from this bin
                    var best = GetBest(bin, i, out _, out _);
                    chosenList.Add(irts[best.Item1]);
                    bin.Remove(best);
                }
                else
                {
                    emptyBins.Add(i);
                }
            }
            foreach (var emptyIdx in emptyBins)
            {
                var bins  = new List <int>();
                var left  = emptyIdx - 1;
                var right = emptyIdx + 1;
                while (bins.Count == 0)
                {
                    if (left >= 0)
                    {
                        bins.Add(left);
                    }
                    if (right < candidateBins.Length)
                    {
                        bins.Add(right);
                    }
                    left--;
                    right++;
                }
                Tuple <Target, double> best = null;
                var bestBinIdx  = -1;
                var bestCount   = 0;
                var bestRtDelta = 0d;
                foreach (var i in bins)
                {
                    var current = GetBest(candidateBins[i], i, out var count, out var rtDelta);
                    if (count > bestCount || (count == bestCount && rtDelta < bestRtDelta))
                    {
                        best        = current;
                        bestBinIdx  = i;
                        bestCount   = count;
                        bestRtDelta = rtDelta;
                    }
                }
                if (best != null)
                {
                    chosenList.Add(irts[best.Item1]);
                    candidateBins[bestBinIdx].Remove(best);
                }
            }

            // Process retention times using the chosen peptides
            chosenCirtPeptides = chosenList.ToArray();
            return(ProcessRetentionTimes(monitor, providers, chosenCirtPeptides, new DbIrtPeptide[0], regressionType));
        }