Refactoring of PairHMM to support reduced reads
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@ -28,6 +28,7 @@ package org.broadinstitute.sting.gatk.walkers.indels;
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import net.sf.samtools.Cigar;
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import net.sf.samtools.Cigar;
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import net.sf.samtools.CigarElement;
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import net.sf.samtools.CigarElement;
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import net.sf.samtools.CigarOperator;
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import net.sf.samtools.CigarOperator;
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import net.sf.samtools.SAMRecord;
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import org.broadinstitute.sting.gatk.contexts.ReferenceContext;
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import org.broadinstitute.sting.gatk.contexts.ReferenceContext;
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import org.broadinstitute.sting.utils.Haplotype;
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import org.broadinstitute.sting.utils.Haplotype;
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import org.broadinstitute.sting.utils.MathUtils;
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import org.broadinstitute.sting.utils.MathUtils;
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@ -268,7 +269,7 @@ public class PairHMMIndelErrorModel {
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dataManager.addToAllTables( key, datum, PRESERVE_QSCORES_LESS_THAN );
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dataManager.addToAllTables( key, datum, PRESERVE_QSCORES_LESS_THAN );
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}
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}
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*/
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*/
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public PairHMMIndelErrorModel(double indelGOP, double indelGCP, boolean deb, boolean doCDP, boolean dovit) {
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public PairHMMIndelErrorModel(double indelGOP, double indelGCP, boolean deb, boolean doCDP, boolean dovit) {
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this(indelGOP, indelGCP, deb, doCDP);
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this(indelGOP, indelGCP, deb, doCDP);
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this.doViterbi = dovit;
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this.doViterbi = dovit;
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@ -711,8 +712,8 @@ public class PairHMMIndelErrorModel {
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HashMap<PileupElement, LinkedHashMap<Allele,Double>> indelLikelihoodMap){
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HashMap<PileupElement, LinkedHashMap<Allele,Double>> indelLikelihoodMap){
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int numHaplotypes = haplotypeMap.size();
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int numHaplotypes = haplotypeMap.size();
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double[][] haplotypeLikehoodMatrix = new double[numHaplotypes][numHaplotypes];
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final double readLikelihoods[][] = new double[pileup.size()][numHaplotypes];
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double readLikelihoods[][] = new double[pileup.getReads().size()][numHaplotypes];
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final int readCounts[] = new int[pileup.size()];
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int readIdx=0;
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int readIdx=0;
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LinkedHashMap<Allele,double[]> gapOpenProbabilityMap = new LinkedHashMap<Allele,double[]>();
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LinkedHashMap<Allele,double[]> gapOpenProbabilityMap = new LinkedHashMap<Allele,double[]>();
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@ -751,6 +752,9 @@ public class PairHMMIndelErrorModel {
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}
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}
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}
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}
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for (PileupElement p: pileup) {
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for (PileupElement p: pileup) {
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// > 1 when the read is a consensus read representing multiple independent observations
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final boolean isReduced = ReadUtils.isReducedRead(p.getRead());
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readCounts[readIdx] = isReduced ? p.getReducedCount() : 1;
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// check if we've already computed likelihoods for this pileup element (i.e. for this read at this location)
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// check if we've already computed likelihoods for this pileup element (i.e. for this read at this location)
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if (indelLikelihoodMap.containsKey(p)) {
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if (indelLikelihoodMap.containsKey(p)) {
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@ -762,10 +766,14 @@ public class PairHMMIndelErrorModel {
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}
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}
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else {
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else {
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//System.out.format("%d %s\n",p.getRead().getAlignmentStart(), p.getRead().getClass().getName());
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//System.out.format("%d %s\n",p.getRead().getAlignmentStart(), p.getRead().getClass().getName());
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GATKSAMRecord read = ReadUtils.hardClipAdaptorSequence(p.getRead());
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SAMRecord read = ReadUtils.hardClipAdaptorSequence(p.getRead());
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if (read == null)
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if (read == null)
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continue;
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continue;
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if ( isReduced ) {
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read = ReadUtils.reducedReadWithReducedQuals(read);
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}
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if(ReadUtils.is454Read(read) && !getGapPenaltiesFromFile) {
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if(ReadUtils.is454Read(read) && !getGapPenaltiesFromFile) {
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continue;
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continue;
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}
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}
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@ -971,7 +979,7 @@ public class PairHMMIndelErrorModel {
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System.out.println(new String(haplotypeBases));
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System.out.println(new String(haplotypeBases));
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}
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}
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Double readLikelihood = 0.0;
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double readLikelihood = 0.0;
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if (useAffineGapModel) {
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if (useAffineGapModel) {
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double[] currentContextGOP = null;
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double[] currentContextGOP = null;
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@ -1004,7 +1012,7 @@ public class PairHMMIndelErrorModel {
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if (DEBUG) {
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if (DEBUG) {
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System.out.println("\nLikelihood summary");
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System.out.println("\nLikelihood summary");
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for (readIdx=0; readIdx < pileup.getReads().size(); readIdx++) {
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for (readIdx=0; readIdx < pileup.size(); readIdx++) {
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System.out.format("Read Index: %d ",readIdx);
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System.out.format("Read Index: %d ",readIdx);
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for (int i=0; i < readLikelihoods[readIdx].length; i++)
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for (int i=0; i < readLikelihoods[readIdx].length; i++)
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System.out.format("L%d: %f ",i,readLikelihoods[readIdx][i]);
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System.out.format("L%d: %f ",i,readLikelihoods[readIdx][i]);
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@ -1012,36 +1020,35 @@ public class PairHMMIndelErrorModel {
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}
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}
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}
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}
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return getHaplotypeLikelihoods(numHaplotypes, readCounts, readLikelihoods);
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}
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private final static double[] getHaplotypeLikelihoods(final int numHaplotypes, final int readCounts[], final double readLikelihoods[][]) {
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final double[][] haplotypeLikehoodMatrix = new double[numHaplotypes][numHaplotypes];
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// todo: MAD 09/26/11 -- I'm almost certain this calculation can be simplied to just a single loop without the intermediate NxN matrix
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for (int i=0; i < numHaplotypes; i++) {
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for (int i=0; i < numHaplotypes; i++) {
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for (int j=i; j < numHaplotypes; j++){
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for (int j=i; j < numHaplotypes; j++){
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// combine likelihoods of haplotypeLikelihoods[i], haplotypeLikelihoods[j]
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// combine likelihoods of haplotypeLikelihoods[i], haplotypeLikelihoods[j]
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// L(Hi, Hj) = sum_reads ( Pr(R|Hi)/2 + Pr(R|Hj)/2)
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// L(Hi, Hj) = sum_reads ( Pr(R|Hi)/2 + Pr(R|Hj)/2)
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//readLikelihoods[k][j] has log10(Pr(R_k) | H[j] )
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//readLikelihoods[k][j] has log10(Pr(R_k) | H[j] )
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for (readIdx=0; readIdx < pileup.getReads().size(); readIdx++) {
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for (int readIdx = 0; readIdx < readLikelihoods.length; readIdx++) {
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// Compute log10(10^x1/2 + 10^x2/2) = log10(10^x1+10^x2)-log10(2)
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// Compute log10(10^x1/2 + 10^x2/2) = log10(10^x1+10^x2)-log10(2)
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// First term is approximated by Jacobian log with table lookup.
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// First term is approximated by Jacobian log with table lookup.
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if (Double.isInfinite(readLikelihoods[readIdx][i]) && Double.isInfinite(readLikelihoods[readIdx][j]))
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if (Double.isInfinite(readLikelihoods[readIdx][i]) && Double.isInfinite(readLikelihoods[readIdx][j]))
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continue;
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continue;
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haplotypeLikehoodMatrix[i][j] += ( MathUtils.softMax(readLikelihoods[readIdx][i],
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final double li = readLikelihoods[readIdx][i];
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readLikelihoods[readIdx][j]) + LOG_ONE_HALF);
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final double lj = readLikelihoods[readIdx][j];
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final int readCount = readCounts[readIdx];
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haplotypeLikehoodMatrix[i][j] += readCount * (MathUtils.softMax(li, lj) + LOG_ONE_HALF);
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}
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}
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}
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}
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}
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}
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return getHaplotypeLikelihoods(haplotypeLikehoodMatrix);
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final double[] genotypeLikelihoods = new double[numHaplotypes*(numHaplotypes+1)/2];
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}
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public static double[] getHaplotypeLikelihoods(double[][] haplotypeLikehoodMatrix) {
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int hSize = haplotypeLikehoodMatrix.length;
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double[] genotypeLikelihoods = new double[hSize*(hSize+1)/2];
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int k=0;
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int k=0;
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for (int j=0; j < hSize; j++) {
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for (int j=0; j < numHaplotypes; j++) {
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for (int i=0; i <= j; i++){
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for (int i=0; i <= j; i++){
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genotypeLikelihoods[k++] = haplotypeLikehoodMatrix[i][j];
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genotypeLikelihoods[k++] = haplotypeLikehoodMatrix[i][j];
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}
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}
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@ -1124,5 +1131,5 @@ public class PairHMMIndelErrorModel {
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//return newQualityByte;
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//return newQualityByte;
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}
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}
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*/
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*/
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}
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}
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