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class GroupedSegments extends AnyRef

A collection of counted super-mers grouped into bins (by minimizer). Super-mers are segments of length >= k where every k-mer shares the same minimizer.

Unlike with the Index, every k-mer in the super-mers is guaranteed to be present.

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Instance Constructors

  1. new GroupedSegments(segments: Dataset[(BucketId, Array[ZeroNTBitArray], Array[Abundance])], splitter: Broadcast[AnyMinSplitter])(implicit spark: SparkSession)

    segments

    The super-mers in binary format, together with their abundances.

    splitter

    The read splitter

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  15. val segments: Dataset[(BucketId, Array[ZeroNTBitArray], Array[Abundance])]
  16. val splitter: Broadcast[AnyMinSplitter]
  17. def superkmerStrings: DataFrame

    Convert this dataset to human-readable pairs of (minimizer, super-mer string).

  18. final def synchronized[T0](arg0: ⇒ T0): T0
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  19. def toIndex(filterOrientation: Boolean, numBuckets: Int = 200): Index

    Construct a counting index from the input data in these grouped segments

  20. def toReducibleBuckets(filterOrientation: Boolean): Dataset[ReducibleBucket]
  21. def toString(): String
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  22. final def wait(): Unit
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  25. def writeSupermerStrings(outputLocation: String): Unit

    Write these segments (as pairs of minimizers and strings) to HDFS.

    Write these segments (as pairs of minimizers and strings) to HDFS. This action triggers a computation.

    outputLocation

    A directory (prefix name) where the super-mers will be stored.

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