WindowFlatMapUtils

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17. def splitPartitionByContigAndMap[R <: ReferenceRegion, T](perSampleTaskRegions: PerSample[Iterator[R]], partitionLoci: LociSet, halfWindowSize: Int, generateFromWindows: (LociIterator, PerSample[SlidingWindow[R]]) ⇒ Iterator[T])(implicit arg0: ClassTag[R], arg1: ClassTag[T]): Iterator[T]

    For a given partition, step through its loci and the reads overlapping each one, applying an arbitrary function and returning its emitted objects.

    For a given partition, step through its loci and the reads overlapping each one, applying an arbitrary function and returning its emitted objects.

    T

    result data type

    perSampleTaskRegions

    this partition's regions, split by sample

    partitionLoci

    this partition's loci

    halfWindowSize

    a margin within which reads are considered to effectively overlap a locus

    generateFromWindows

    function that maps a contig's loci and regions to a sequence of result objects.

    returns

    Iterator[T] collected from each contig

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23. def windowFlatMapWithState[R <: SampleRegion, T, S](numSamples: NumSamples, partitionedReads: PartitionedRegions[R], skipEmpty: Boolean, halfWindowSize: Int, initialState: S, function: (S, PerSample[SlidingWindow[R]]) ⇒ (S, Iterator[T]))(implicit arg0: ClassTag[R], arg1: ClassTag[T]): RDD[T]

    FlatMap across loci, and any number of RDDs of regions, where at each locus the provided function is passed a sliding window instance for each RDD containing the regions overlapping an interval of halfWindowSize to either side of a locus.

    FlatMap across loci, and any number of RDDs of regions, where at each locus the provided function is passed a sliding window instance for each RDD containing the regions overlapping an interval of halfWindowSize to either side of a locus.

    This function supports maintaining some state from one locus to another within a task. The state maintained is of type S. The user function will receive the current state in addition to the sliding windows, and returns a pair of (new state, result data). The state is initialized to initialState for each task, and for each new contig handled by a single task.

    R

    region data type (e.g. MappedRead)

    T

    result data type

    S

    state type

    numSamples

    number of samples / input-files whose reads are in @partitionedReads.

    partitionedReads

    partitioned reads RDD; reads that straddle partition boundaries will occur more than once herein.

    skipEmpty

    If True, then the function will only be called on loci where at least one region maps within a window around the locus. If False, then the function will be called at all loci in lociPartitions.

    halfWindowSize

    if another region overlaps a halfWindowSize to either side of a locus under consideration, then it is included.

    initialState

    initial state to use for each task and each contig analyzed within a task.

    function

    function to flatmap, of type (state, sliding windows) -> (new state, result data)

    returns

    RDD[T] of flatmap results