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Example 1 with CopyRatioExpectationsCalculator

use of org.broadinstitute.hellbender.tools.coveragemodel.interfaces.CopyRatioExpectationsCalculator in project gatk by broadinstitute.

the class CoverageModelEMWorkspace method updateCopyRatioPosteriorExpectationsSpark.

/**
     * The Spark implementation of the E-step update of copy ratio posteriors
     *
     * @return a {@link SubroutineSignal} containing the update size
     */
@EvaluatesRDD
@UpdatesRDD
@CachesRDD
private SubroutineSignal updateCopyRatioPosteriorExpectationsSpark(final double admixingRatio) {
    /* local final member variables for lambda capture */
    final List<LinearlySpacedIndexBlock> targetBlocks = new ArrayList<>();
    targetBlocks.addAll(this.targetBlocks);
    final List<Target> targetList = new ArrayList<>();
    targetList.addAll(processedTargetList);
    final List<String> sampleNameList = new ArrayList<>();
    sampleNameList.addAll(processedSampleNameList);
    final List<SexGenotypeData> sampleSexGenotypeData = new ArrayList<>();
    sampleSexGenotypeData.addAll(processedSampleSexGenotypeData);
    final int numTargetBlocks = targetBlocks.size();
    final CopyRatioExpectationsCalculator<CoverageModelCopyRatioEmissionData, STATE> calculator = this.copyRatioExpectationsCalculator;
    final INDArray sampleReadDepths = Transforms.exp(sampleMeanLogReadDepths, true);
    /* make an RDD of copy ratio posterior expectations */
    final JavaPairRDD<Integer, CopyRatioExpectations> copyRatioPosteriorExpectationsPairRDD = /* fetch copy ratio emission data from workers */
    fetchCopyRatioEmissionDataSpark().mapPartitionsToPair(it -> {
        final List<Tuple2<Integer, CopyRatioExpectations>> newPartitionData = new ArrayList<>();
        while (it.hasNext()) {
            final Tuple2<Integer, List<CoverageModelCopyRatioEmissionData>> prevDatum = it.next();
            final int si = prevDatum._1;
            final CopyRatioCallingMetadata copyRatioCallingMetadata = CopyRatioCallingMetadata.builder().sampleName(sampleNameList.get(si)).sampleSexGenotypeData(sampleSexGenotypeData.get(si)).sampleCoverageDepth(sampleReadDepths.getDouble(si)).emissionCalculationStrategy(EmissionCalculationStrategy.HYBRID_POISSON_GAUSSIAN).build();
            newPartitionData.add(new Tuple2<>(prevDatum._1, calculator.getCopyRatioPosteriorExpectations(copyRatioCallingMetadata, targetList, prevDatum._2)));
        }
        return newPartitionData.iterator();
    }, true);
    /* we need to do two things to copyRatioPosteriorExpectationsPairRDD; so we cache it */
    /* step 1. update log chain posterior expectation on the driver node */
    final double[] newSampleLogChainPosteriors = copyRatioPosteriorExpectationsPairRDD.mapValues(CopyRatioExpectations::getLogChainPosteriorProbability).collect().stream().sorted(Comparator.comparingInt(t -> t._1)).mapToDouble(t -> t._2).toArray();
    sampleLogChainPosteriors.assign(Nd4j.create(newSampleLogChainPosteriors, new int[] { numSamples, 1 }));
    /* step 2. repartition in target space */
    final JavaPairRDD<LinearlySpacedIndexBlock, ImmutablePair<INDArray, INDArray>> blockifiedCopyRatioPosteriorResultsPairRDD = copyRatioPosteriorExpectationsPairRDD.flatMapToPair(dat -> targetBlocks.stream().map(tb -> new Tuple2<>(tb, new Tuple2<>(dat._1, ImmutablePair.of(dat._2.getLogCopyRatioMeans(tb), dat._2.getLogCopyRatioVariances(tb))))).iterator()).combineByKey(/* recipe to create an singleton list */
    Collections::singletonList, /* recipe to add an element to the list */
    (list, element) -> Stream.concat(list.stream(), Stream.of(element)).collect(Collectors.toList()), /* recipe to concatenate two lists */
    (list1, list2) -> Stream.concat(list1.stream(), list2.stream()).collect(Collectors.toList()), /* repartition with respect to target space blocks */
    new HashPartitioner(numTargetBlocks)).mapValues(list -> list.stream().sorted(Comparator.comparingInt(t -> t._1)).map(p -> p._2).map(t -> ImmutablePair.of(Nd4j.create(t.left), Nd4j.create(t.right))).collect(Collectors.toList())).mapValues(CoverageModelEMWorkspace::stackCopyRatioPosteriorDataForAllSamples);
    /* we do not need copy ratio expectations anymore */
    copyRatioPosteriorExpectationsPairRDD.unpersist();
    /* step 3. merge with computeRDD and update */
    computeRDD = computeRDD.join(blockifiedCopyRatioPosteriorResultsPairRDD).mapValues(t -> t._1.cloneWithUpdatedCopyRatioPosteriors(t._2.left, t._2.right, admixingRatio));
    cacheWorkers("after E-step for copy ratio update");
    /* collect subroutine signals */
    final List<SubroutineSignal> sigs = mapWorkersAndCollect(CoverageModelEMComputeBlock::getLatestMStepSignal);
    final double errorNormInfinity = Collections.max(sigs.stream().map(sig -> sig.<Double>get(StandardSubroutineSignals.RESIDUAL_ERROR_NORM)).collect(Collectors.toList()));
    return SubroutineSignal.builder().put(StandardSubroutineSignals.RESIDUAL_ERROR_NORM, errorNormInfinity).build();
}
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Example 2 with CopyRatioExpectationsCalculator

use of org.broadinstitute.hellbender.tools.coveragemodel.interfaces.CopyRatioExpectationsCalculator in project gatk-protected by broadinstitute.

the class CoverageModelEMWorkspace method updateCopyRatioPosteriorExpectationsSpark.

/**
     * The Spark implementation of the E-step update of copy ratio posteriors
     *
     * @return a {@link SubroutineSignal} containing the update size
     */
@EvaluatesRDD
@UpdatesRDD
@CachesRDD
private SubroutineSignal updateCopyRatioPosteriorExpectationsSpark(final double admixingRatio) {
    /* local final member variables for lambda capture */
    final List<LinearlySpacedIndexBlock> targetBlocks = new ArrayList<>();
    targetBlocks.addAll(this.targetBlocks);
    final List<Target> targetList = new ArrayList<>();
    targetList.addAll(processedTargetList);
    final List<String> sampleNameList = new ArrayList<>();
    sampleNameList.addAll(processedSampleNameList);
    final List<SexGenotypeData> sampleSexGenotypeData = new ArrayList<>();
    sampleSexGenotypeData.addAll(processedSampleSexGenotypeData);
    final int numTargetBlocks = targetBlocks.size();
    final CopyRatioExpectationsCalculator<CoverageModelCopyRatioEmissionData, STATE> calculator = this.copyRatioExpectationsCalculator;
    final INDArray sampleReadDepths = Transforms.exp(sampleMeanLogReadDepths, true);
    /* make an RDD of copy ratio posterior expectations */
    final JavaPairRDD<Integer, CopyRatioExpectations> copyRatioPosteriorExpectationsPairRDD = /* fetch copy ratio emission data from workers */
    fetchCopyRatioEmissionDataSpark().mapPartitionsToPair(it -> {
        final List<Tuple2<Integer, CopyRatioExpectations>> newPartitionData = new ArrayList<>();
        while (it.hasNext()) {
            final Tuple2<Integer, List<CoverageModelCopyRatioEmissionData>> prevDatum = it.next();
            final int si = prevDatum._1;
            final CopyRatioCallingMetadata copyRatioCallingMetadata = CopyRatioCallingMetadata.builder().sampleName(sampleNameList.get(si)).sampleSexGenotypeData(sampleSexGenotypeData.get(si)).sampleCoverageDepth(sampleReadDepths.getDouble(si)).emissionCalculationStrategy(EmissionCalculationStrategy.HYBRID_POISSON_GAUSSIAN).build();
            newPartitionData.add(new Tuple2<>(prevDatum._1, calculator.getCopyRatioPosteriorExpectations(copyRatioCallingMetadata, targetList, prevDatum._2)));
        }
        return newPartitionData.iterator();
    }, true);
    /* we need to do two things to copyRatioPosteriorExpectationsPairRDD; so we cache it */
    /* step 1. update log chain posterior expectation on the driver node */
    final double[] newSampleLogChainPosteriors = copyRatioPosteriorExpectationsPairRDD.mapValues(CopyRatioExpectations::getLogChainPosteriorProbability).collect().stream().sorted(Comparator.comparingInt(t -> t._1)).mapToDouble(t -> t._2).toArray();
    sampleLogChainPosteriors.assign(Nd4j.create(newSampleLogChainPosteriors, new int[] { numSamples, 1 }));
    /* step 2. repartition in target space */
    final JavaPairRDD<LinearlySpacedIndexBlock, ImmutablePair<INDArray, INDArray>> blockifiedCopyRatioPosteriorResultsPairRDD = copyRatioPosteriorExpectationsPairRDD.flatMapToPair(dat -> targetBlocks.stream().map(tb -> new Tuple2<>(tb, new Tuple2<>(dat._1, ImmutablePair.of(dat._2.getLogCopyRatioMeans(tb), dat._2.getLogCopyRatioVariances(tb))))).iterator()).combineByKey(/* recipe to create an singleton list */
    Collections::singletonList, /* recipe to add an element to the list */
    (list, element) -> Stream.concat(list.stream(), Stream.of(element)).collect(Collectors.toList()), /* recipe to concatenate two lists */
    (list1, list2) -> Stream.concat(list1.stream(), list2.stream()).collect(Collectors.toList()), /* repartition with respect to target space blocks */
    new HashPartitioner(numTargetBlocks)).mapValues(list -> list.stream().sorted(Comparator.comparingInt(t -> t._1)).map(p -> p._2).map(t -> ImmutablePair.of(Nd4j.create(t.left), Nd4j.create(t.right))).collect(Collectors.toList())).mapValues(CoverageModelEMWorkspace::stackCopyRatioPosteriorDataForAllSamples);
    /* we do not need copy ratio expectations anymore */
    copyRatioPosteriorExpectationsPairRDD.unpersist();
    /* step 3. merge with computeRDD and update */
    computeRDD = computeRDD.join(blockifiedCopyRatioPosteriorResultsPairRDD).mapValues(t -> t._1.cloneWithUpdatedCopyRatioPosteriors(t._2.left, t._2.right, admixingRatio));
    cacheWorkers("after E-step for copy ratio update");
    /* collect subroutine signals */
    final List<SubroutineSignal> sigs = mapWorkersAndCollect(CoverageModelEMComputeBlock::getLatestMStepSignal);
    final double errorNormInfinity = Collections.max(sigs.stream().map(sig -> sig.<Double>get(StandardSubroutineSignals.RESIDUAL_ERROR_NORM)).collect(Collectors.toList()));
    return SubroutineSignal.builder().put(StandardSubroutineSignals.RESIDUAL_ERROR_NORM, errorNormInfinity).build();
}
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Example 3 with CopyRatioExpectationsCalculator

use of org.broadinstitute.hellbender.tools.coveragemodel.interfaces.CopyRatioExpectationsCalculator in project gatk by broadinstitute.

the class CoverageModelEMWorkspace method getCopyRatioSegmentsSpark.

/**
     * Fetch copy ratio segments from compute blocks (Spark implementation)
     *
     * @return a list of {@link CopyRatioHMMResults}
     */
private List<List<HiddenStateSegmentRecord<STATE, Target>>> getCopyRatioSegmentsSpark() {
    /* local final member variables for lambda capture */
    final List<Target> processedTargetList = new ArrayList<>();
    processedTargetList.addAll(this.processedTargetList);
    final List<SexGenotypeData> processedSampleSexGenotypeData = new ArrayList<>();
    processedSampleSexGenotypeData.addAll(this.processedSampleSexGenotypeData);
    final List<String> processedSampleNameList = new ArrayList<>();
    processedSampleNameList.addAll(this.processedSampleNameList);
    final INDArray sampleReadDepths = Transforms.exp(sampleMeanLogReadDepths, true);
    final CopyRatioExpectationsCalculator<CoverageModelCopyRatioEmissionData, STATE> copyRatioExpectationsCalculator = this.copyRatioExpectationsCalculator;
    final BiFunction<SexGenotypeData, Target, STATE> referenceStateFactory = this.referenceStateFactory;
    return fetchCopyRatioEmissionDataSpark().mapPartitionsToPair(it -> {
        final List<Tuple2<Integer, CopyRatioHMMResults<CoverageModelCopyRatioEmissionData, STATE>>> newPartitionData = new ArrayList<>();
        while (it.hasNext()) {
            final Tuple2<Integer, List<CoverageModelCopyRatioEmissionData>> prevDatum = it.next();
            final int sampleIndex = prevDatum._1;
            final CopyRatioCallingMetadata copyRatioCallingMetadata = CopyRatioCallingMetadata.builder().sampleName(processedSampleNameList.get(sampleIndex)).sampleSexGenotypeData(processedSampleSexGenotypeData.get(sampleIndex)).sampleCoverageDepth(sampleReadDepths.getDouble(sampleIndex)).emissionCalculationStrategy(EmissionCalculationStrategy.HYBRID_POISSON_GAUSSIAN).build();
            newPartitionData.add(new Tuple2<>(sampleIndex, copyRatioExpectationsCalculator.getCopyRatioHMMResults(copyRatioCallingMetadata, processedTargetList, prevDatum._2)));
        }
        return newPartitionData.iterator();
    }, true).mapPartitionsToPair(it -> {
        final List<Tuple2<Integer, List<HiddenStateSegmentRecord<STATE, Target>>>> newPartitionData = new ArrayList<>();
        while (it.hasNext()) {
            final Tuple2<Integer, CopyRatioHMMResults<CoverageModelCopyRatioEmissionData, STATE>> prevDatum = it.next();
            final int sampleIndex = prevDatum._1;
            final CopyRatioHMMResults<CoverageModelCopyRatioEmissionData, STATE> result = prevDatum._2;
            final HMMSegmentProcessor<CoverageModelCopyRatioEmissionData, STATE, Target> processor = new HMMSegmentProcessor<>(Collections.singletonList(result.getMetaData().getSampleName()), Collections.singletonList(result.getMetaData().getSampleSexGenotypeData()), referenceStateFactory, Collections.singletonList(new HashedListTargetCollection<>(processedTargetList)), Collections.singletonList(result.getForwardBackwardResult()), Collections.singletonList(result.getViterbiResult()));
            newPartitionData.add(new Tuple2<>(sampleIndex, processor.getSegmentsAsList()));
        }
        return newPartitionData.iterator();
    }).collect().stream().sorted(Comparator.comparingInt(t -> t._1)).map(t -> t._2).collect(Collectors.toList());
}
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Example 4 with CopyRatioExpectationsCalculator

use of org.broadinstitute.hellbender.tools.coveragemodel.interfaces.CopyRatioExpectationsCalculator in project gatk-protected by broadinstitute.

the class CoverageModelEMWorkspace method getCopyRatioSegmentsSpark.

/**
     * Fetch copy ratio segments from compute blocks (Spark implementation)
     *
     * @return a list of {@link CopyRatioHMMResults}
     */
private List<List<HiddenStateSegmentRecord<STATE, Target>>> getCopyRatioSegmentsSpark() {
    /* local final member variables for lambda capture */
    final List<Target> processedTargetList = new ArrayList<>();
    processedTargetList.addAll(this.processedTargetList);
    final List<SexGenotypeData> processedSampleSexGenotypeData = new ArrayList<>();
    processedSampleSexGenotypeData.addAll(this.processedSampleSexGenotypeData);
    final List<String> processedSampleNameList = new ArrayList<>();
    processedSampleNameList.addAll(this.processedSampleNameList);
    final INDArray sampleReadDepths = Transforms.exp(sampleMeanLogReadDepths, true);
    final CopyRatioExpectationsCalculator<CoverageModelCopyRatioEmissionData, STATE> copyRatioExpectationsCalculator = this.copyRatioExpectationsCalculator;
    final BiFunction<SexGenotypeData, Target, STATE> referenceStateFactory = this.referenceStateFactory;
    return fetchCopyRatioEmissionDataSpark().mapPartitionsToPair(it -> {
        final List<Tuple2<Integer, CopyRatioHMMResults<CoverageModelCopyRatioEmissionData, STATE>>> newPartitionData = new ArrayList<>();
        while (it.hasNext()) {
            final Tuple2<Integer, List<CoverageModelCopyRatioEmissionData>> prevDatum = it.next();
            final int sampleIndex = prevDatum._1;
            final CopyRatioCallingMetadata copyRatioCallingMetadata = CopyRatioCallingMetadata.builder().sampleName(processedSampleNameList.get(sampleIndex)).sampleSexGenotypeData(processedSampleSexGenotypeData.get(sampleIndex)).sampleCoverageDepth(sampleReadDepths.getDouble(sampleIndex)).emissionCalculationStrategy(EmissionCalculationStrategy.HYBRID_POISSON_GAUSSIAN).build();
            newPartitionData.add(new Tuple2<>(sampleIndex, copyRatioExpectationsCalculator.getCopyRatioHMMResults(copyRatioCallingMetadata, processedTargetList, prevDatum._2)));
        }
        return newPartitionData.iterator();
    }, true).mapPartitionsToPair(it -> {
        final List<Tuple2<Integer, List<HiddenStateSegmentRecord<STATE, Target>>>> newPartitionData = new ArrayList<>();
        while (it.hasNext()) {
            final Tuple2<Integer, CopyRatioHMMResults<CoverageModelCopyRatioEmissionData, STATE>> prevDatum = it.next();
            final int sampleIndex = prevDatum._1;
            final CopyRatioHMMResults<CoverageModelCopyRatioEmissionData, STATE> result = prevDatum._2;
            final HMMSegmentProcessor<CoverageModelCopyRatioEmissionData, STATE, Target> processor = new HMMSegmentProcessor<>(Collections.singletonList(result.getMetaData().getSampleName()), Collections.singletonList(result.getMetaData().getSampleSexGenotypeData()), referenceStateFactory, Collections.singletonList(new HashedListTargetCollection<>(processedTargetList)), Collections.singletonList(result.getForwardBackwardResult()), Collections.singletonList(result.getViterbiResult()));
            newPartitionData.add(new Tuple2<>(sampleIndex, processor.getSegmentsAsList()));
        }
        return newPartitionData.iterator();
    }).collect().stream().sorted(Comparator.comparingInt(t -> t._1)).map(t -> t._2).collect(Collectors.toList());
}
Also used : ScalarProducer(org.broadinstitute.hellbender.utils.hmm.interfaces.ScalarProducer) Function2(org.apache.spark.api.java.function.Function2) HMMSegmentProcessor(org.broadinstitute.hellbender.utils.hmm.segmentation.HMMSegmentProcessor) GermlinePloidyAnnotatedTargetCollection(org.broadinstitute.hellbender.tools.exome.sexgenotyper.GermlinePloidyAnnotatedTargetCollection) HiddenStateSegmentRecordWriter(org.broadinstitute.hellbender.utils.hmm.segmentation.HiddenStateSegmentRecordWriter) BiFunction(java.util.function.BiFunction) GATKException(org.broadinstitute.hellbender.exceptions.GATKException) SexGenotypeData(org.broadinstitute.hellbender.tools.exome.sexgenotyper.SexGenotypeData) ParamUtils(org.broadinstitute.hellbender.utils.param.ParamUtils) CallStringProducer(org.broadinstitute.hellbender.utils.hmm.interfaces.CallStringProducer) StorageLevel(org.apache.spark.storage.StorageLevel) SynchronizedUnivariateSolver(org.broadinstitute.hellbender.tools.coveragemodel.math.SynchronizedUnivariateSolver) CopyRatioExpectationsCalculator(org.broadinstitute.hellbender.tools.coveragemodel.interfaces.CopyRatioExpectationsCalculator) UnivariateSolverSpecifications(org.broadinstitute.hellbender.tools.coveragemodel.math.UnivariateSolverSpecifications) IndexRange(org.broadinstitute.hellbender.utils.IndexRange) Broadcast(org.apache.spark.broadcast.Broadcast) ExitStatus(org.broadinstitute.hellbender.tools.coveragemodel.linalg.IterativeLinearSolverNDArray.ExitStatus) SexGenotypeDataCollection(org.broadinstitute.hellbender.tools.exome.sexgenotyper.SexGenotypeDataCollection) HashPartitioner(org.apache.spark.HashPartitioner) Predicate(java.util.function.Predicate) GeneralLinearOperator(org.broadinstitute.hellbender.tools.coveragemodel.linalg.GeneralLinearOperator) Nd4j(org.nd4j.linalg.factory.Nd4j) INDArrayIndex(org.nd4j.linalg.indexing.INDArrayIndex) FastMath(org.apache.commons.math3.util.FastMath) org.broadinstitute.hellbender.tools.exome(org.broadinstitute.hellbender.tools.exome) Tuple2(scala.Tuple2) Collectors(java.util.stream.Collectors) Sets(com.google.common.collect.Sets) AbstractUnivariateSolver(org.apache.commons.math3.analysis.solvers.AbstractUnivariateSolver) FourierLinearOperatorNDArray(org.broadinstitute.hellbender.tools.coveragemodel.linalg.FourierLinearOperatorNDArray) Logger(org.apache.logging.log4j.Logger) Stream(java.util.stream.Stream) UserException(org.broadinstitute.hellbender.exceptions.UserException) UnivariateFunction(org.apache.commons.math3.analysis.UnivariateFunction) TooManyEvaluationsException(org.apache.commons.math3.exception.TooManyEvaluationsException) Utils(org.broadinstitute.hellbender.utils.Utils) Function(org.apache.spark.api.java.function.Function) DataBuffer(org.nd4j.linalg.api.buffer.DataBuffer) IntStream(java.util.stream.IntStream) java.util(java.util) NDArrayIndex(org.nd4j.linalg.indexing.NDArrayIndex) JavaSparkContext(org.apache.spark.api.java.JavaSparkContext) AlleleMetadataProducer(org.broadinstitute.hellbender.utils.hmm.interfaces.AlleleMetadataProducer) EmissionCalculationStrategy(org.broadinstitute.hellbender.tools.coveragemodel.CoverageModelCopyRatioEmissionProbabilityCalculator.EmissionCalculationStrategy) RobustBrentSolver(org.broadinstitute.hellbender.tools.coveragemodel.math.RobustBrentSolver) IntervalUtils(org.broadinstitute.hellbender.utils.IntervalUtils) Nonnull(javax.annotation.Nonnull) Nullable(javax.annotation.Nullable) HiddenStateSegmentRecord(org.broadinstitute.hellbender.utils.hmm.segmentation.HiddenStateSegmentRecord) ImmutableTriple(org.apache.commons.lang3.tuple.ImmutableTriple) IterativeLinearSolverNDArray(org.broadinstitute.hellbender.tools.coveragemodel.linalg.IterativeLinearSolverNDArray) GATKProtectedMathUtils(org.broadinstitute.hellbender.utils.GATKProtectedMathUtils) Nd4jIOUtils(org.broadinstitute.hellbender.tools.coveragemodel.nd4jutils.Nd4jIOUtils) IOException(java.io.IOException) JavaPairRDD(org.apache.spark.api.java.JavaPairRDD) ImmutablePair(org.apache.commons.lang3.tuple.ImmutablePair) File(java.io.File) INDArray(org.nd4j.linalg.api.ndarray.INDArray) VisibleForTesting(com.google.common.annotations.VisibleForTesting) Transforms(org.nd4j.linalg.ops.transforms.Transforms) LogManager(org.apache.logging.log4j.LogManager) NoBracketingException(org.apache.commons.math3.exception.NoBracketingException) INDArray(org.nd4j.linalg.api.ndarray.INDArray) Tuple2(scala.Tuple2) SexGenotypeData(org.broadinstitute.hellbender.tools.exome.sexgenotyper.SexGenotypeData) HMMSegmentProcessor(org.broadinstitute.hellbender.utils.hmm.segmentation.HMMSegmentProcessor)

Aggregations

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