コード例 #1
0
 private double[] oneDprob(final EvidenceInterface evidence) {
   final Code code = mSubHypotheses.code();
   final double[] probs = new double[mSubHypotheses.size()];
   for (int i = 0; i < probs.length; i++) {
     final double a = Math.max(0, evidence.probability(code.a(i)));
     final double b = Math.max(0, evidence.probability(code.bc(i)));
     probs[i] = 0.5 * (a + b);
   }
   // System.err.println(probs.length + " :" + Arrays.toString(probs));
   return probs;
 }
コード例 #2
0
ファイル: Disease.java プロジェクト: ppflrs/rtg-core
 /**
  * @param diseaseHyp haploid disease hypothesis that starts with NONE and includes rest of
  *     nucleotides (see <code>HypothesesDisease</code>).
  * @param genome selects family member with father starting at 0.
  * @return true iff the disease hypothesis is consistent with the disease status of this family
  *     member (aka genome). Assumes disease is dominant.
  */
 private boolean q(final int diseaseHyp, final int genome) {
   final int hyp = mCurrentHypotheses[genome];
   final boolean contains;
   final Code code = mIndividualHypotheses.code();
   final int dis = diseaseHyp - 1;
   // TODO implement recessive version controlled by flag.
   if (code.homozygous(hyp)) {
     contains = code.a(hyp) == dis;
   } else {
     contains = code.a(hyp) == dis || code.b(hyp) == dis;
   }
   return contains == mFamily.isDiseased(genome);
 }
コード例 #3
0
 @Override
 public void increment(final EvidenceInterface evidence) {
   // System.err.println(evidence);
   incrementStatistics(evidence);
   if (ambiguityShortCircuit(evidence)) {
     return;
   }
   final double r = evidence.mapError();
   final double rc = 1.0 - r;
   // Avoid case where mapq is 0 which gives a NaN
   if (rc <= 0.0) {
     return;
   }
   final double[] probs = oneDprob(evidence);
   final double pE = evidence.pe();
   final double pEr = r * pE;
   final Code code = hypotheses().code();
   for (int i = 0; i < size(); i++) {
     final int a = code.a(i);
     final int b = code.bc(i);
     // The cross-product is normal x cancer
     final double prob = probs[a] * mContamination + probs[b] * mContaminationM;
     // Phred scores of 0 can result in 0 probability, just skip them
     if (prob <= 0.0) {
       return;
     }
     // Adjust for mapQ - see theory in scoring.tex
     final double pr = prob * rc + pEr;
     final double np = arithmetic().multiply(mPosteriors[i], arithmetic().prob2Poss(pr));
     assert arithmetic()
         .isValidPoss(
             np); // : System.err.println("np=" + np + " mPosteriors[i]=" + mPosteriors[i] + " i="
                  // + i + " pr=" + pr + " prob=" + prob + " rc=" + rc + " r=" + r + " pE=" + pE);
     mPosteriors[i] = np;
   }
 }