Exemple #1
0
 public int ComputeQScore(QScoreMethod qscoreMethod)
 {
     double score;
     int qscore;
     switch (qscoreMethod)
     {
         case QScoreMethod.LogisticGermline:
             // Logistic model using a new selection of features.  Gives ROC curve area 0.921
             score = -5.0123;
             score += GetQScorePredictor(QScorePredictor.LogBinCount) * 4.9801;
             score += GetQScorePredictor(QScorePredictor.ModelDistance) * -5.5472;
             score += GetQScorePredictor(QScorePredictor.DistanceRatio) * -1.7914;
             score = Math.Exp(score);
             score = score / (score + 1);
             // Transform probability into a q-score:
             qscore = (int)(Math.Round(-10 * Math.Log10(1 - score)));
             qscore = Math.Min(40, qscore);
             qscore = Math.Max(2, qscore);
             return qscore;
         case QScoreMethod.Logistic:
             // Logistic model using a new selection of features.  Gives ROC curve area 0.8289
             score = -0.5143;
             score += GetQScorePredictor(QScorePredictor.LogBinCount) * 0.8596;
             score += GetQScorePredictor(QScorePredictor.ModelDistance) * -50.4366;
             score += GetQScorePredictor(QScorePredictor.DistanceRatio) * -0.6511;
             score = Math.Exp(score);
             score = score / (score + 1);
             // Transform probability into a q-score:
             qscore = (int)(Math.Round(-10 * Math.Log10(1 - score)));
             qscore = Math.Min(60, qscore);
             qscore = Math.Max(2, qscore);
             return qscore;
         case QScoreMethod.BinCountLinearFit:
             if (this.BinCount >= 100)
                 return 61;
             else
                 return (int)Math.Round(-10 * Math.Log10(1 - 1 / (1 + Math.Exp(0.5532 - this.BinCount * 0.147))), 0, MidpointRounding.AwayFromZero);
         case QScoreMethod.GeneralizedLinearFit: // Generalized linear fit with linear transformation to QScore
             double linearFit = -3.65
                                - 1.12 * GetQScorePredictor(QScorePredictor.LogBinCount)
                                + 3.89 * GetQScorePredictor(QScorePredictor.ModelDistance)
                                + 0.47 * GetQScorePredictor(QScorePredictor.MajorChromosomeCount)
                                - 0.68 * GetQScorePredictor(QScorePredictor.MafMean)
                                - 0.25 * GetQScorePredictor(QScorePredictor.LogMafCv);
             score = -11.9 - 11.4 * linearFit; // Scaling to achieve 2 <= qscore <= 61
             score = Math.Max(2, score);
             score = Math.Min(61, score);
             return (int)Math.Round(score, 0, MidpointRounding.AwayFromZero);
         default:
             throw new Exception("Unhandled qscore method");
     }
 }
Exemple #2
0
 /// <summary>
 /// Apply quality scores.
 /// </summary>
 public static void AssignQualityScores(List<CanvasSegment> segments, QScoreMethod qscoreMethod)
 {
     foreach (CanvasSegment segment in segments)
     {
         segment.QScore = segment.ComputeQScore(qscoreMethod);
     }
 }