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/*
* Copyright (C) 2014-2021 Brian L. Browning
*
* This file is part of Beagle
*
* Beagle is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* Beagle is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
package phase;
import ints.IntArray;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import phase.SamplePhase.ClustType;
import vcf.Markers;
/**
* <p>Interface {@code PhaseBaum2} updates the estimated genotype phase
* of specified samples.
* </p>
* <p>Instances of class {@code PhaseBaum2} are not thread-safe.
* </p>
*
* @author Brian L. Browning {@code <browning@uw.edu>}
*/
public class PhaseBaum2 implements PhaseBaum {
private final PhaseData phaseData;
private final boolean burnin;
private final float lrThreshold;
private final boolean maskTrailingHets;
private final EstPhase estPhase;
private final Markers markers;
private final int nMarkers;
private final List<int[]> refAlleles; // ref panel alleles for each missing genotype
private final byte[][][] mismatches; // [3][nMarker][nStates]
private final float pMismatch;
private final float[] emProbs;
private final int maxStates;
private final BasicPhaseStates states;
private int nStates;
private final float[][] fwd;
private final float[][] bwd;
private final float[] fwdSums;
private final List<float[]> bwdMiss1;
private final List<float[]> bwdMiss2;
private final List<float[]> bwdHet1;
private final List<float[]> bwdHet2;
private boolean swapHaps = false;
private int nSwaps = 0;
/**
* Creates a {@code PhaseLSBaum} instance from the specified data.
*
* @param phaseIbs the IBS haplotype segments
* @throws NullPointerException if {@code phaseIBS == null}
*/
public PhaseBaum2(PbwtPhaseIbs phaseIbs) {
this.phaseData = phaseIbs.phaseData();
this.burnin = phaseData.it() < phaseData.fpd().par().burnin();
this.lrThreshold = phaseData.lrThreshold();
float lrMaskThreshold = 50f;
this.maskTrailingHets = lrThreshold<lrMaskThreshold;
this.estPhase = phaseData.estPhase();
this.markers = phaseData.fpd().stage1TargGT().markers();
this.nMarkers = markers.size();
this.maxStates = phaseData.fpd().par().phase_states();
this.states = new BasicPhaseStates(phaseIbs, maxStates);
this.refAlleles = new ArrayList<>();
this.mismatches = new byte[3][nMarkers][maxStates];
this.pMismatch = phaseData.pMismatch();
this.emProbs = new float[] {1.0f - pMismatch, pMismatch};
this.fwd = new float[3][maxStates];
this.bwd = new float[3][maxStates];
this.fwdSums = new float[3];
this.bwdMiss1 = new ArrayList<>();
this.bwdMiss2 = new ArrayList<>();
this.bwdHet1 = new ArrayList<>();
this.bwdHet2 = new ArrayList<>();
}
/**
* Returns the number of target samples.
* @return the number of target samples
*/
@Override
public int nTargSamples() {
return phaseData.fpd().targGT().nSamples();
}
/**
* Estimates and stores the phased haplotypes for the specified sample
* @param sample a sample index
* @throws IndexOutOfBoundsException if
* {@code sample < 0 || sample >= this.nTargSamples()}
*/
@Override
public void phase(int sample) {
SamplePhase samplePhase = estPhase.get(sample);
if (maskTrailingHets) {
samplePhase.maskTrailingUnphasedHets();
}
int nUnphHets = samplePhase.nUnphased();
int nMaskedHets = samplePhase.nMasked();
int nMissingOrMasked = samplePhase.nMissing() + nMaskedHets;
if (nMissingOrMasked>0 || nUnphHets>0) {
nSwaps = 0;
swapHaps = false;
MarkerCluster mc = new MarkerCluster(phaseData, sample);
ensureCapacity(nUnphHets, nMissingOrMasked);
nStates = states.ibsStates(mc, refAlleles, mismatches);
bwdAlg(mc);
fwdAlg(mc);
estPhase.set(sample, samplePhase);
SwapRate.increment(nUnphHets, nSwaps);
}
}
private void ensureCapacity(int nUnph, int nMiss) {
if (refAlleles.size()<nMiss) {
for (int j=refAlleles.size(); j<nMiss; ++j) {
refAlleles.add(new int[maxStates]);
bwdMiss1.add(new float[maxStates]);
bwdMiss2.add(new float[maxStates]);
}
}
if (bwdHet1.size()<nUnph) {
for (int j=bwdHet1.size(); j<nUnph; ++j) {
bwdHet1.add(new float[maxStates]);
bwdHet2.add(new float[maxStates]);
}
}
}
private void bwdAlg(MarkerCluster mc) {
SamplePhase samplePhase = mc.samplePhase();
int missIndex = samplePhase.nMissing() + samplePhase.nMasked() - 1;
int unphIndex = samplePhase.nUnphased() - 1;
initializeBwdFields();
int lastCluster = mc.nClusters()-1;
if (mc.isMissingGtOrMaskedHet(lastCluster)) {
System.arraycopy(bwd[0], 0, bwdMiss1.get(missIndex), 0, nStates);
System.arraycopy(bwd[0], 0, bwdMiss2.get(missIndex), 0, nStates);
--missIndex;
}
for (int c=(lastCluster-1); c>=0; --c) {
bwdStep(mc, c);
if (mc.isMissingGtOrMaskedHet(c)) {
System.arraycopy(bwd[1], 0, bwdMiss1.get(missIndex), 0, nStates);
System.arraycopy(bwd[2], 0, bwdMiss2.get(missIndex), 0, nStates);
--missIndex;
}
if (mc.isUnphasedHet(c+1)) {
System.arraycopy(bwd[1], 0, bwdHet1.get(unphIndex), 0, nStates);
System.arraycopy(bwd[2], 0, bwdHet2.get(unphIndex), 0, nStates);
System.arraycopy(bwd[0], 0, bwd[1], 0, nStates);
System.arraycopy(bwd[0], 0, bwd[2], 0, nStates);
--unphIndex;
}
}
assert missIndex == -1;
assert unphIndex == -1;
}
private void initializeBwdFields() {
Arrays.fill(bwd[0], 0, nStates, 1.0f/nStates);
System.arraycopy(bwd[0], 0, bwd[1], 0, nStates);
System.arraycopy(bwd[0], 0, bwd[2], 0, nStates);
}
private void bwdStep(MarkerCluster mc, int cluster) {
int cP1 = cluster + 1;
float pRec = mc.pRecomb().get(cP1);
float clustEm = (mc.clusterEnd(cP1) - mc.clusterStart(cP1))*pMismatch;
if (clustEm>=0.5f) {
clustEm = 0.5f;
}
emProbs[1] = clustEm;
emProbs[0] = 1f - clustEm;
HmmUpdater.bwdUpdate(bwd[0], pRec, emProbs, mismatches[0][cP1], nStates);
HmmUpdater.bwdUpdate(bwd[1], pRec, emProbs, mismatches[1][cP1], nStates);
HmmUpdater.bwdUpdate(bwd[2], pRec, emProbs, mismatches[2][cP1], nStates);
}
private void fwdAlg(MarkerCluster mc) {
int missIndex = 0;
int unphHetIndex = 0;
initializeFwdFields();
IntArray unphClusters = mc.unphasedHetClusters();
for (int c=0, n=mc.nClusters(); c<n; ++c) {
if (mc.isUnphasedHet(c)) {
phaseHet(mc.samplePhase(), unphHetIndex, c);
++unphHetIndex;
if (swapHaps) {
int swapEnd = unphHetIndex < unphClusters.size()
? unphClusters.get(unphHetIndex)
: mc.nClusters();
swapHaps(mc, c, swapEnd);
}
System.arraycopy(fwd[0], 0, fwd[1], 0, nStates);
System.arraycopy(fwd[0], 0, fwd[2], 0, nStates);
fwdSums[1] = fwdSums[2] = fwdSums[0];
}
fwdStep(mc, c);
if (mc.isMissingGtOrMaskedHet(c)) {
imputeAlleles(mc, c, missIndex++);
}
}
}
private void initializeFwdFields() {
Arrays.fill(fwd[0], 0, nStates, 1.0f/nStates);
System.arraycopy(fwd[0], 0, fwd[1], 0, nStates);
System.arraycopy(fwd[0], 0, fwd[2], 0, nStates);
fwdSums[2] = fwdSums[1] = fwdSums[0] = 1.0f;
}
private void fwdStep(MarkerCluster mc, int cluster) {
float pRec = mc.pRecomb().get(cluster);
float clustEm = (mc.clusterEnd(cluster) - mc.clusterStart(cluster))*pMismatch;
if (clustEm>=0.5f) {
clustEm = 0.5f;
}
emProbs[1] = clustEm;
emProbs[0] = 1.0f - clustEm;
fwdSums[0] = HmmUpdater.fwdUpdate(fwd[0], fwdSums[0], pRec, emProbs, mismatches[0][cluster], nStates);
fwdSums[1] = HmmUpdater.fwdUpdate(fwd[1], fwdSums[1], pRec, emProbs, mismatches[1][cluster], nStates);
fwdSums[2] = HmmUpdater.fwdUpdate(fwd[2], fwdSums[2], pRec, emProbs, mismatches[2][cluster], nStates);
}
private void swapHaps(MarkerCluster mc, int startClust, int endClust) {
for (int c=startClust; c<endClust; ++c) {
byte[] tmpMatch = mismatches[1][c];
mismatches[1][c] = mismatches[2][c];
mismatches[2][c] = tmpMatch;
}
mc.samplePhase().swapHaps(mc.clusterStart(startClust), mc.clusterEnd(endClust-1));
}
private void imputeAlleles(MarkerCluster mc, int cluster, int missIndex) {
assert (mc.clusterEnd(cluster) - mc.clusterStart(cluster))==1;
assert mc.isMissingGtOrMaskedHet(cluster);
float[] stateProbs1 = bwdMiss1.get(missIndex);
float[] stateProbs2 = bwdMiss2.get(missIndex);
if (swapHaps) {
float[] tmp = stateProbs1;
stateProbs1 = stateProbs2;
stateProbs2 = tmp;
}
int[] refAl = refAlleles.get(missIndex);
for (int k=0; k<nStates; ++k) {
stateProbs1[k] *= fwd[1][k];
stateProbs2[k] *= fwd[2][k];
}
int marker = mc.clusterStart(cluster);
int nAlleles = markers.marker(marker).nAlleles();
float[] alFreq1 = new float[nAlleles];
float[] alFreq2 = new float[nAlleles];
for (int k=0; k<nStates; ++k) {
alFreq1[refAl[k]] += stateProbs1[k];
alFreq2[refAl[k]] += stateProbs2[k];
}
SamplePhase samplePhase = mc.samplePhase();
ClustType clustType = samplePhase.clustType(cluster);
if (clustType==ClustType.MISSING_GT) {
imputeMissingGT(samplePhase, marker, alFreq1, alFreq2);
}
else if (clustType==ClustType.MASKED_HET) {
imputeMaskedHet(samplePhase, cluster, marker, alFreq1, alFreq2);
}
}
private void imputeMissingGT(SamplePhase samplePhase, int marker,
float[] alFreq1, float[] alFreq2) {
int a1 = 0;
int a2 = 0;
for (int j=1; j<alFreq1.length; ++j) {
if (alFreq1[j]>alFreq1[a1]) {
a1 = j;
}
if (alFreq2[j]>alFreq2[a2]) {
a2 = j;
}
}
samplePhase.setAllele1(marker, a1);
samplePhase.setAllele2(marker, a2);
}
private void imputeMaskedHet(SamplePhase samplePhase, int cluster,
int marker, float[] alFreq1, float[] alFreq2) {
int a1 = samplePhase.allele1(marker);
int a2 = samplePhase.allele2(marker);
assert a1!=a2;
float pNoSwitch = alFreq1[a1]*alFreq2[a2];
float pSwitch = alFreq1[a2]*alFreq2[a1];
if (pSwitch > pNoSwitch) {
samplePhase.setAllele1(marker, a2);
samplePhase.setAllele2(marker, a1);
if (pSwitch>=(lrThreshold*pNoSwitch)) {
samplePhase.markMaskedHetClusterAsPhased(cluster);
}
}
else if (pNoSwitch>=(lrThreshold*pSwitch)) {
samplePhase.markMaskedHetClusterAsPhased(cluster);
}
}
private void phaseHet(SamplePhase samplePhase, int unphHetIndex, int cluster) {
float[] b1 = bwdHet1.get(unphHetIndex);
float[] b2 = bwdHet2.get(unphHetIndex);
float p11 = 0.0f;
float p12 = 0.0f;
float p21 = 0.0f;
float p22 = 0.0f;
for (int k=0; k<nStates; ++k) {
p11 += fwd[1][k]*b1[k];
p12 += fwd[1][k]*b2[k];
p21 += fwd[2][k]*b1[k];
p22 += fwd[2][k]*b2[k];
}
float num = (p11*p22);
float den = (p12*p21);
boolean lastSwapHaps = swapHaps;
swapHaps = num < den;
if (swapHaps!=lastSwapHaps) {
++nSwaps;
}
if (burnin==false) {
if (num>=den*lrThreshold || (swapHaps && den>=num*lrThreshold) ) {
samplePhase.markUnphasedHetClusterAsPhased(cluster);
}
}
}
}
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