/*
* The MIT License
*
* Copyright (c) 2016 The Broad Institute
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in
* all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* THE SOFTWARE.
*/
package picard.fingerprint;
/**
* A wrapper class for any HaplotypeProbabilities instance that will assume that the given evidence is that of a tumor sample and
* provide an hp for the normal sample that tumor came from. This models possible loss of hetrozygosity where het genotypes
* turn into a homozygous genotype with probability pLoH.
*
* The shortcoming of this model is that we assume that the events are all independent, but this way they are allowed.
*
* @author farjoun
*/
public class HaplotypeProbabilityOfNormalGivenTumor extends HaplotypeProbabilities {
private final double[][] transitionMatrix;
private final HaplotypeProbabilities hpOfTumor;
public HaplotypeProbabilityOfNormalGivenTumor(final HaplotypeProbabilities hpOfTumor, final double pLoH) {
super(hpOfTumor.getHaplotype());
this.hpOfTumor = hpOfTumor;
transitionMatrix = new double[][]{
//This is P(g_t|g_n)
//tumor genotype are the columns.
{1, 0, 0}, //normal is hom_ref => tumor must be the same
{pLoH / 2, 1 - pLoH, pLoH / 2}, //normal is het => tumor may have transitioned
{0, 0, 1}}; //normal is hom_var => tumor must be the same
}
// This function needs to be overridden since we want likelihood to mean the probability of the
// data given a particular _normal_ genotype, however, the likelihood as given is that where the
// genotype is of the tumor (if that's what the data was measuring)
// P(D_t|g_n) = \sum_{g_t} P(D_t|g_t,g_n)
// = \sum P(D_t|g_t, g_n) P(g_t|g_n)
// = \sum P(D_t|g_t) P(g_t|g_n)
// = hpOfTumor.getLikelihoods() * transitionMatrix
// where the * operator is understood as linear algebra operation.
@Override
public double[] getLikelihoods() {
final double[] normalHaplotypeLikelihoods = new double[3];
final double[] tumorHaplotypeLikelihoods = hpOfTumor.getLikelihoods();
for (final Genotype g_n : Genotype.values()) {
normalHaplotypeLikelihoods[g_n.v] = 0D;
for (final Genotype g_t : Genotype.values()) {
normalHaplotypeLikelihoods[g_n.v] += tumorHaplotypeLikelihoods[g_t.v] * transitionMatrix[g_n.v][g_t.v];
}
}
return normalHaplotypeLikelihoods;
}
@Override
public Snp getRepresentativeSnp() {
return hpOfTumor.getRepresentativeSnp();
}
@Override
public void merge(final HaplotypeProbabilities ignored) {
throw new IllegalArgumentException("Cannot merge HaplotypeProbabilityOfNormalGivenTumor. Merge the underlying object and create a new wrapper.");
}
@Override
public int getObsAllele1() {
return hpOfTumor.getObsAllele1();
}
@Override
public int getObsAllele2() {
return hpOfTumor.getObsAllele2();
}
@Override
public int getTotalObs() {
return hpOfTumor.getTotalObs();
}
@Override
public boolean hasEvidence() {
return hpOfTumor.hasEvidence();
}
}