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class Kmers extends AnyRef

Convenience methods for interacting with k-mers from a set of input files.

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Instance Constructors

  1. new Kmers(discount: Discount, inFiles: Seq[String], knownSplitter: Option[Broadcast[AnyMinSplitter]] = None)(implicit spark: SparkSession)

    discount

    The Discount object

    inFiles

    Input files

    knownSplitter

    The splitter/minimizer scheme to use, if one is available. Otherwise, a new one will be constructed.

Value Members

  1. final def !=(arg0: Any): Boolean
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  2. final def ##(): Int
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  3. final def ==(arg0: Any): Boolean
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  4. final def asInstanceOf[T0]: T0
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  5. lazy val bcSplit: Broadcast[AnyMinSplitter]

    Broadcast of the read splitter associated with this set of inputs.

  6. def clone(): AnyRef
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    @throws( ... ) @native()
  7. def constructSampledMinimizerOrdering(writeLocation: String): MinSplitter[_]

    Sample the input data, counting minimizers and writing the generated frequency ordering to HDFS.

    Sample the input data, counting minimizers and writing the generated frequency ordering to HDFS.

    writeLocation

    Location to write the frequency ordering to

    returns

    A splitter object corresponding to the generated ordering

  8. val discount: Discount
  9. final def eq(arg0: AnyRef): Boolean
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  10. def equals(arg0: Any): Boolean
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  11. def finalize(): Unit
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  12. final def getClass(): Class[_]
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  13. def hashCode(): Int
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  14. val inFiles: Seq[String]
  15. lazy val index: Index

    A counting k-mer index containing all k-mers from the input sequences.

  16. def inputFragments: Dataset[InputFragment]

    Input fragments associated with these inputs.

  17. final def isInstanceOf[T0]: Boolean
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  18. lazy val method: CountMethod

    The overall method used for k-mer counting.

    The overall method used for k-mer counting. If not specified, this will be guessed from the input data according to a heuristic.

  19. final def ne(arg0: AnyRef): Boolean
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  20. final def notify(): Unit
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  21. final def notifyAll(): Unit
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  22. def sampledIndex(fraction: Double): Index

    Construct an index from a sampled fraction of this input data.

    Construct an index from a sampled fraction of this input data. Because repeated calls will sample the input differently, it is recommended to cache the Index if it will be used repeatedly.

  23. def segments: GroupedSegments
  24. def sequenceTitles: Dataset[SeqTitle]
  25. final def synchronized[T0](arg0: ⇒ T0): T0
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  26. def toString(): String
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  27. final def wait(): Unit
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  28. final def wait(arg0: Long, arg1: Int): Unit
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  29. final def wait(arg0: Long): Unit
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