ADAM_2.12: Core 0.33.0 API < Back
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# Packages

-  package root
  Definition Classes
    root
-  package org
  Definition Classes
    root
-  package bdgenomics
  Definition Classes
    org
-  package adam
  Definition Classes
    bdgenomics
-  package rdd
  Definition Classes
    adam
-  package feature
  Definition Classes
    rdd
- BEDInFormatter
- BEDOutFormatter
- CoverageDataset
- DatasetBoundCoverageDataset
- DatasetBoundFeatureDataset
- FeatureDataset
- GFF3InFormatter
- GFF3OutFormatter
- GTFInFormatter
- GTFOutFormatter
- NarrowPeakInFormatter
- NarrowPeakOutFormatter
- ParquetUnboundCoverageDataset
- ParquetUnboundFeatureDataset
- RDDBoundCoverageDataset
- RDDBoundFeatureDataset

c

org.bdgenomics.adam.rdd.feature

# DatasetBoundCoverageDataset 

###

#### case class DatasetBoundCoverageDataset extends CoverageDataset with DatasetBoundGenomicDataset[Coverage, Coverage, CoverageDataset] with Product with Serializable

Linear Supertypes
Serializable, Serializable, Product, Equals, DatasetBoundGenomicDataset[Coverage, Coverage, CoverageDataset], CoverageDataset, MultisampleGenomicDataset[Coverage, Coverage, CoverageDataset], GenomicDataset[Coverage, Coverage, CoverageDataset], Logging, AnyRef, Any
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1. DatasetBoundCoverageDataset
2. Serializable
3. Serializable
4. Product
5. Equals
6. DatasetBoundGenomicDataset
7. CoverageDataset
8. MultisampleGenomicDataset
9. GenomicDataset
10. Logging
11. AnyRef
12. Any

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Visibility

1. Public
2. All

### Value Members

1.  final def !=(arg0: Any): Boolean
   Definition Classes
     AnyRef → Any
2.  final def ##(): Int
   Definition Classes
     AnyRef → Any
3.  final def ==(arg0: Any): Boolean
   Definition Classes
     AnyRef → Any
4.  def addSample(sampleToAdd: Sample): CoverageDataset

   Adds a single sample to the current genomic dataset.

   Adds a single sample to the current genomic dataset.

   sampleToAdd

     A single sample to add.

   returns

     Returns a new genomic dataset with this sample added.

   Definition Classes
     MultisampleGenomicDataset
5.  def addSamples(samplesToAdd: Iterable[Sample]): CoverageDataset

   Adds samples to the current genomic dataset.

   Adds samples to the current genomic dataset.

   samplesToAdd

     Zero or more samples to add.

   returns

     Returns a new genomic dataset with samples added.

   Definition Classes
     MultisampleGenomicDataset
6.  def addSequence(sequenceToAdd: SequenceRecord): CoverageDataset

   Appends metadata for a single sequence to the current genomic dataset.

   Appends metadata for a single sequence to the current genomic dataset.

   sequenceToAdd

     The sequence to add.

   returns

     Returns a new GenomicDataset with this sequence appended.

   Definition Classes
     GenomicDataset
7.  def addSequences(sequencesToAdd: SequenceDictionary): CoverageDataset

   Appends sequence metadata to the current genomic dataset.

   Appends sequence metadata to the current genomic dataset.

   sequencesToAdd

     The new sequences to append.

   returns

     Returns a new GenomicDataset with the sequences appended.

   Definition Classes
     GenomicDataset
8.  def aggregatedCoverage(bpPerBin: Int = 1): CoverageDataset

   (Scala-specific) Gets coverage overlapping specified ReferenceRegion.

   (Scala-specific) Gets coverage overlapping specified ReferenceRegion.

   For large ReferenceRegions, base pairs per bin (bpPerBin) can be specified to bin together ReferenceRegions of equal size. The coverage of each bin is the mean coverage over all base pairs in that bin.

   bpPerBin

     base pairs per bin, number of bases to combine to one bin.

   returns

     Genomic dataset of Coverage Records.

   Definition Classes
     CoverageDataset
9.  def aggregatedCoverage(bpPerBin: Integer): CoverageDataset

   (Java-specific) Gets coverage overlapping specified ReferenceRegion.

   (Java-specific) Gets coverage overlapping specified ReferenceRegion.

   For large ReferenceRegions, base pairs per bin (bpPerBin) can be specified to bin together ReferenceRegions of equal size. The coverage of each bin is the mean coverage over all base pairs in that bin.

   bpPerBin

     base pairs per bin, number of bases to combine to one bin.

   returns

     Genomic dataset of Coverage Records.

   Definition Classes
     CoverageDataset
10.  final def asInstanceOf[T0]: T0
    Definition Classes
      Any
11.  def broadcast()(implicit tTag: ClassTag[Coverage]): GenomicBroadcast[Coverage, Coverage, CoverageDataset]
    Definition Classes
      GenomicDataset
12.  def broadcastRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[Coverage], xTag: ClassTag[X], txTag: ClassTag[(Coverage, X)], uyTag: scala.reflect.api.JavaUniverse.TypeTag[(Coverage, Y)]): GenericGenomicDataset[(Coverage, X), (Coverage, Y)]

    Performs a broadcast inner join between this genomic dataset and another genomic dataset.

    Performs a broadcast inner join between this genomic dataset and another genomic dataset.

    In a broadcast join, the left genomic dataset (this genomic dataset) is collected to the driver, and broadcast to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is an inner join, all values who do not overlap a value from the other genomic dataset are dropped.

    genomicDataset

      The right genomic dataset in the join.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space.

    Definition Classes
      GenomicDataset
    See also

      broadcastRegionJoinAgainst

13.  def broadcastRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[Coverage], xTag: ClassTag[X], txTag: ClassTag[(Coverage, X)], uyTag: scala.reflect.api.JavaUniverse.TypeTag[(Coverage, Y)]): GenericGenomicDataset[(Coverage, X), (Coverage, Y)]

    Performs a broadcast inner join between this genomic dataset and another genomic dataset.

    Performs a broadcast inner join between this genomic dataset and another genomic dataset.

    In a broadcast join, the left genomic dataset (this genomic dataset) is collected to the driver, and broadcast to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is an inner join, all values who do not overlap a value from the other genomic dataset are dropped.

    genomicDataset

      The right genomic dataset in the join.

    flankSize

      Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space.

    Definition Classes
      GenomicDataset
    See also

      broadcastRegionJoinAgainst

14.  def broadcastRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Coverage, X), (Coverage, Y)]

    (Java-specific) Performs a broadcast inner join between this genomic dataset and another genomic dataset.

    (Java-specific) Performs a broadcast inner join between this genomic dataset and another genomic dataset.

    In a broadcast join, the left genomic dataset (this genomic dataset) is collected to the driver, and broadcast to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is an inner join, all values who do not overlap a value from the other genomic dataset are dropped.

    genomicDataset

      The right genomic dataset in the join.

    flankSize

      Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space.

    Definition Classes
      GenomicDataset
15.  def broadcastRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Coverage, X), (Coverage, Y)]

    (R-specific) Performs a broadcast inner join between this genomic dataset and another genomic dataset.

    (R-specific) Performs a broadcast inner join between this genomic dataset and another genomic dataset.

    In a broadcast join, the left genomic dataset (this genomic dataset) is collected to the driver, and broadcast to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is an inner join, all values who do not overlap a value from the other genomic dataset are dropped.

    genomicDataset

      The right genomic dataset in the join.

    flankSize

      Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space.

    Definition Classes
      GenomicDataset
16.  def broadcastRegionJoinAgainst[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](broadcast: GenomicBroadcast[X, Y, Z])(implicit tTag: ClassTag[Coverage], xTag: ClassTag[X], uyTag: scala.reflect.api.JavaUniverse.TypeTag[(Y, Coverage)]): GenericGenomicDataset[(X, Coverage), (Y, Coverage)]

    Performs a broadcast inner join between this genomic dataset and data that has been broadcast.

    Performs a broadcast inner join between this genomic dataset and data that has been broadcast.

    In a broadcast join, the left side of the join (broadcastTree) is broadcast to to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is an inner join, all values who do not overlap a value from the other genomic dataset are dropped. As compared to broadcastRegionJoin, this function allows the broadcast object to be reused across multiple joins.

    broadcast

      The data on the left side of the join.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space.

    Definition Classes
      GenomicDataset
    Note

      This function differs from other region joins as it treats the calling genomic dataset as the right side of the join, and not the left.

    See also

      broadcastRegionJoin

17.  def broadcastRegionJoinAgainstAndGroupByRight[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](broadcast: GenomicBroadcast[X, Y, Z])(implicit tTag: ClassTag[Coverage], xTag: ClassTag[X], syuTag: scala.reflect.api.JavaUniverse.TypeTag[(Seq[Y], Coverage)]): GenericGenomicDataset[(Iterable[X], Coverage), (Seq[Y], Coverage)]

    Performs a broadcast inner join between this genomic dataset and another genomic dataset.

    Performs a broadcast inner join between this genomic dataset and another genomic dataset.

    In a broadcast join, the left side of the join (broadcastTree) is broadcast to to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is an inner join, all values who do not overlap a value from the other genomic dataset are dropped. As compared to broadcastRegionJoin, this function allows the broadcast object to be reused across multiple joins.

    broadcast

      The data on the left side of the join.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space.

    Definition Classes
      GenomicDataset
    Note

      This function differs from other region joins as it treats the calling genomic dataset as the right side of the join, and not the left.

    See also

      broadcastRegionJoinAndGroupByRight

18.  def broadcastRegionJoinAndGroupByRight[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[Coverage], xTag: ClassTag[X], itxTag: ClassTag[(Iterable[Coverage], X)], iuyTag: scala.reflect.api.JavaUniverse.TypeTag[(Seq[Coverage], Y)]): GenericGenomicDataset[(Iterable[Coverage], X), (Seq[Coverage], Y)]

    Performs a broadcast inner join between this genomic dataset and another genomic dataset.

    Performs a broadcast inner join between this genomic dataset and another genomic dataset.

    In a broadcast join, the left genomic dataset (this genomic dataset) is collected to the driver, and broadcast to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is an inner join, all values who do not overlap a value from the other genomic dataset are dropped.

    genomicDataset

      The right genomic dataset in the join.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space.

    Definition Classes
      GenomicDataset
    See also

      broadcastRegionJoinAgainstAndGroupByRight

19.  def broadcastRegionJoinAndGroupByRight[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[Coverage], xTag: ClassTag[X], itxTag: ClassTag[(Iterable[Coverage], X)], iuyTag: scala.reflect.api.JavaUniverse.TypeTag[(Seq[Coverage], Y)]): GenericGenomicDataset[(Iterable[Coverage], X), (Seq[Coverage], Y)]

    Performs a broadcast inner join between this genomic dataset and another genomic dataset.

    Performs a broadcast inner join between this genomic dataset and another genomic dataset.

    In a broadcast join, the left genomic dataset (this genomic dataset) is collected to the driver, and broadcast to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is an inner join, all values who do not overlap a value from the other genomic dataset are dropped.

    genomicDataset

      The right genomic dataset in the join.

    flankSize

      Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space.

    Definition Classes
      GenomicDataset
    See also

      broadcastRegionJoinAgainstAndGroupByRight

20.  def broadcastRegionJoinAndGroupByRight[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Iterable[Coverage], X), (Seq[Coverage], Y)]

    (Java-specific) Performs a broadcast inner join between this genomic dataset and another genomic dataset.

    (Java-specific) Performs a broadcast inner join between this genomic dataset and another genomic dataset.

    In a broadcast join, the left genomic dataset (this genomic dataset) is collected to the driver, and broadcast to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is an inner join, all values who do not overlap a value from the other genomic dataset are dropped.

    genomicDataset

      The right genomic dataset in the join.

    flankSize

      Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space.

    Definition Classes
      GenomicDataset
    See also

      broadcastRegionJoinAgainstAndGroupByRight

21.  def broadcastRegionJoinAndGroupByRight[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Iterable[Coverage], X), (Seq[Coverage], Y)]

    (R-specific) Performs a broadcast inner join between this genomic dataset and another genomic dataset.

    (R-specific) Performs a broadcast inner join between this genomic dataset and another genomic dataset.

    In a broadcast join, the left genomic dataset (this genomic dataset) is collected to the driver, and broadcast to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is an inner join, all values who do not overlap a value from the other genomic dataset are dropped.

    genomicDataset

      The right genomic dataset in the join.

    flankSize

      Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space.

    Definition Classes
      GenomicDataset
    See also

      broadcastRegionJoinAgainstAndGroupByRight

22.  def buildTree(rdd: RDD[(ReferenceRegion, Coverage)])(implicit tTag: ClassTag[Coverage]): IntervalArray[ReferenceRegion, Coverage]
    Attributes
      protected
    Definition Classes
      CoverageDataset → GenomicDataset
23.  def cache(): CoverageDataset

    Caches underlying RDD in memory.

    Caches underlying RDD in memory.

    returns

      Cached GenomicDataset.

    Definition Classes
      DatasetBoundGenomicDataset → GenomicDataset
24.  def clone(): AnyRef
    Attributes
      protected[java.lang]
    Definition Classes
      AnyRef
    Annotations
      @native() @throws( ... )
25.  def collapse(): CoverageDataset

    Merges adjacent ReferenceRegions with the same coverage value.

    Merges adjacent ReferenceRegions with the same coverage value. This reduces the loss of coverage information while reducing the number of records in the RDD. For example, adjacent records Coverage("chr1", 1, 10, 3.0) and Coverage("chr1", 10, 20, 3.0) would be merged into one record Coverage("chr1", 1, 20, 3.0).

    returns

      merged tuples of adjacent ReferenceRegions and coverage.

    Definition Classes
      CoverageDataset
    Note

      Data must be sorted before collapse is called.

26.  def coverage(bpPerBin: Int = 1): CoverageDataset

    (Scala-specific) Gets coverage overlapping specified ReferenceRegion.

    (Scala-specific) Gets coverage overlapping specified ReferenceRegion.

    For large ReferenceRegions, base pairs per bin (bpPerBin) can be specified to bin together ReferenceRegions of equal size. The coverage of each bin is coverage of the first base pair in that bin.

    bpPerBin

      base pairs per bin, number of bases to combine to one bin.

    returns

      Genomic dataset of Coverage Records.

    Definition Classes
      CoverageDataset
27.  def coverage(bpPerBin: Integer): CoverageDataset

    (Java-specific) Gets coverage overlapping specified ReferenceRegion.

    (Java-specific) Gets coverage overlapping specified ReferenceRegion.

    For large ReferenceRegions, base pairs per bin (bpPerBin) can be specified to bin together ReferenceRegions of equal size. The coverage of each bin is coverage of the first base pair in that bin.

    bpPerBin

      base pairs per bin, number of bases to combine to one bin.

    returns

      Genomic dataset of Coverage Records.

    Definition Classes
      CoverageDataset
28.  val dataset: Dataset[Coverage]

    These data as a Spark SQL Dataset.

    These data as a Spark SQL Dataset.

    Definition Classes
      DatasetBoundCoverageDataset → GenomicDataset
29.  def debug(mkr: Marker, msg: ⇒ Any, t: ⇒ Throwable): Unit
    Attributes
      protected
    Definition Classes
      Logging
30.  def debug(msg: ⇒ Any, t: ⇒ Throwable): Unit
    Attributes
      protected
    Definition Classes
      Logging
31.  def debug(msg: ⇒ Any): Unit
    Attributes
      protected
    Definition Classes
      Logging
32.  final def eq(arg0: AnyRef): Boolean
    Definition Classes
      AnyRef
33.  def error(mkr: Marker, msg: ⇒ Any, t: ⇒ Throwable): Unit
    Attributes
      protected
    Definition Classes
      Logging
34.  def error(msg: ⇒ Any, t: ⇒ Throwable): Unit
    Attributes
      protected
    Definition Classes
      Logging
35.  def error(msg: ⇒ Any): Unit
    Attributes
      protected
    Definition Classes
      Logging
36.  def filterByOverlappingRegion(query: ReferenceRegion): CoverageDataset

    Runs a filter that selects data in the underlying RDD that overlaps a single genomic region.

    Runs a filter that selects data in the underlying RDD that overlaps a single genomic region.

    query

      The region to query for.

    returns

      Returns a new GenomicDataset containing only data that overlaps the query region.

    Definition Classes
      GenomicDataset
37.  def filterByOverlappingRegions(querys: Iterable[ReferenceRegion]): CoverageDataset

    (Scala-specific) Runs a filter that selects data in the underlying RDD that overlaps several genomic regions.

    (Scala-specific) Runs a filter that selects data in the underlying RDD that overlaps several genomic regions.

    querys

      The regions to query for.

    returns

      Returns a new GenomicDataset containing only data that overlaps the querys region.

    Definition Classes
      DatasetBoundGenomicDataset → GenomicDataset
38.  def filterByOverlappingRegions(querys: Iterable[ReferenceRegion]): CoverageDataset

    (Java-specific) Runs a filter that selects data in the underlying RDD that overlaps several genomic regions.

    (Java-specific) Runs a filter that selects data in the underlying RDD that overlaps several genomic regions.

    querys

      The regions to query for.

    returns

      Returns a new GenomicDataset containing only data that overlaps the querys region.

    Definition Classes
      GenomicDataset
39.  def finalize(): Unit
    Attributes
      protected[java.lang]
    Definition Classes
      AnyRef
    Annotations
      @throws( classOf[java.lang.Throwable] )
40.  def flatten(): CoverageDataset

    Gets flattened genomic dataset of coverage, with coverage mapped to a ReferenceRegion at each base pair.

    Gets flattened genomic dataset of coverage, with coverage mapped to a ReferenceRegion at each base pair.

    returns

      CoverageDataset of flattened Coverage records.

    Definition Classes
      CoverageDataset
41.  def flattenRddByRegions(): RDD[(ReferenceRegion, Coverage)]
    Attributes
      protected
    Definition Classes
      GenomicDataset
42.  def fullOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[Coverage], xTag: ClassTag[X], otoxTag: ClassTag[(Option[Coverage], Option[X])], ouoyTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[Coverage], Option[Y])]): GenericGenomicDataset[(Option[Coverage], Option[X]), (Option[Coverage], Option[Y])]

    Performs a sort-merge full outer join between this genomic dataset and another genomic dataset.

    Performs a sort-merge full outer join between this genomic dataset and another genomic dataset.

    In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is a full outer join, if a value from either genomic dataset does not overlap any values in the other genomic dataset, it will be paired with a `None` in the product of the join.

    genomicDataset

      The right genomic dataset in the join.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and values that did not overlap will be paired with a `None`.

    Definition Classes
      GenomicDataset
43.  def fullOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[Coverage], xTag: ClassTag[X], otoxTag: ClassTag[(Option[Coverage], Option[X])], ouoyTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[Coverage], Option[Y])]): GenericGenomicDataset[(Option[Coverage], Option[X]), (Option[Coverage], Option[Y])]

    Performs a sort-merge full outer join between this genomic dataset and another genomic dataset.

    Performs a sort-merge full outer join between this genomic dataset and another genomic dataset.

    In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is a full outer join, if a value from either genomic dataset does not overlap any values in the other genomic dataset, it will be paired with a `None` in the product of the join.

    genomicDataset

      The right genomic dataset in the join.

    flankSize

      Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and values that did not overlap will be paired with a `None`.

    Definition Classes
      GenomicDataset
44.  def fullOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Option[Coverage], Option[X]), (Option[Coverage], Option[Y])]

    (Python-specific) Performs a sort-merge full outer join between this genomic dataset and another genomic dataset.

    (Python-specific) Performs a sort-merge full outer join between this genomic dataset and another genomic dataset.

    In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is a full outer join, if a value from either genomic dataset does not overlap any values in the other genomic dataset, it will be paired with a `None` in the product of the join.

    genomicDataset

      The right genomic dataset in the join.

    flankSize

      Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and values that did not overlap will be paired with a `None`.

    Definition Classes
      GenomicDataset
45.  def fullOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Option[Coverage], Option[X]), (Option[Coverage], Option[Y])]

    (R-specific) Performs a sort-merge full outer join between this genomic dataset and another genomic dataset.

    (R-specific) Performs a sort-merge full outer join between this genomic dataset and another genomic dataset.

    In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is a full outer join, if a value from either genomic dataset does not overlap any values in the other genomic dataset, it will be paired with a `None` in the product of the join.

    genomicDataset

      The right genomic dataset in the join.

    flankSize

      Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and values that did not overlap will be paired with a `None`.

    Definition Classes
      GenomicDataset
46.  final def getClass(): Class[_]
    Definition Classes
      AnyRef → Any
    Annotations
      @native()
47.  def getReferenceRegions(elem: Coverage): Seq[ReferenceRegion]

    Gets sequence of ReferenceRegions from Coverage element.

    Gets sequence of ReferenceRegions from Coverage element. Since coverage maps directly to a single genomic region, this method will always return a Seq of exactly one ReferenceRegion.

    elem

      The Coverage to get an underlying region for.

    returns

      Sequence of ReferenceRegions extracted from Coverage.

    Attributes
      protected
    Definition Classes
      CoverageDataset → GenomicDataset
48.  def info(mkr: Marker, msg: ⇒ Any, t: ⇒ Throwable): Unit
    Attributes
      protected
    Definition Classes
      Logging
49.  def info(msg: ⇒ Any, t: ⇒ Throwable): Unit
    Attributes
      protected
    Definition Classes
      Logging
50.  def info(msg: ⇒ Any): Unit
    Attributes
      protected
    Definition Classes
      Logging
51.  def isDebugEnabled: Boolean
    Attributes
      protected
    Definition Classes
      Logging
52.  def isErrorEnabled: Boolean
    Attributes
      protected
    Definition Classes
      Logging
53.  def isInfoEnabled: Boolean
    Attributes
      protected
    Definition Classes
      Logging
54.  final def isInstanceOf[T0]: Boolean
    Definition Classes
      Any
55.  val isPartitioned: Boolean
    Definition Classes
      DatasetBoundCoverageDataset → DatasetBoundGenomicDataset
56.  def isSorted: Boolean
    Definition Classes
      GenomicDataset
57.  def isTraceEnabled: Boolean
    Attributes
      protected
    Definition Classes
      Logging
58.  def isWarnEnabled: Boolean
    Attributes
      protected
    Definition Classes
      Logging
59.  lazy val jrdd: JavaRDD[Coverage]

    The underlying RDD of genomic data, as a JavaRDD.

    The underlying RDD of genomic data, as a JavaRDD.

    Definition Classes
      GenomicDataset
60.  def leftOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[Coverage], xTag: ClassTag[X], toxTag: ClassTag[(Coverage, Option[X])], uoyTag: scala.reflect.api.JavaUniverse.TypeTag[(Coverage, Option[Y])]): GenericGenomicDataset[(Coverage, Option[X]), (Coverage, Option[Y])]

    Performs a sort-merge left outer join between this genomic dataset and another genomic dataset.

    Performs a sort-merge left outer join between this genomic dataset and another genomic dataset.

    In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is a left outer join, all values in the right genomic dataset that do not overlap a value from the left genomic dataset are dropped. If a value from the left genomic dataset does not overlap any values in the right genomic dataset, it will be paired with a `None` in the product of the join.

    genomicDataset

      The right genomic dataset in the join.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the left genomic dataset that did not overlap a key in the right genomic dataset.

    Definition Classes
      GenomicDataset
61.  def leftOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[Coverage], xTag: ClassTag[X], toxTag: ClassTag[(Coverage, Option[X])], uoyTag: scala.reflect.api.JavaUniverse.TypeTag[(Coverage, Option[Y])]): GenericGenomicDataset[(Coverage, Option[X]), (Coverage, Option[Y])]

    Performs a sort-merge left outer join between this genomic dataset and another genomic dataset.

    Performs a sort-merge left outer join between this genomic dataset and another genomic dataset.

    In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is a left outer join, all values in the right genomic dataset that do not overlap a value from the left genomic dataset are dropped. If a value from the left genomic dataset does not overlap any values in the right genomic dataset, it will be paired with a `None` in the product of the join.

    genomicDataset

      The right genomic dataset in the join.

    flankSize

      Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the left genomic dataset that did not overlap a key in the right genomic dataset.

    Definition Classes
      GenomicDataset
62.  def leftOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Coverage, Option[X]), (Coverage, Option[Y])]

    (Java-specific) Performs a sort-merge left outer join between this genomic dataset and another genomic dataset.

    (Java-specific) Performs a sort-merge left outer join between this genomic dataset and another genomic dataset.

    In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is a left outer join, all values in the right genomic dataset that do not overlap a value from the left genomic dataset are dropped. If a value from the left genomic dataset does not overlap any values in the right genomic dataset, it will be paired with a `None` in the product of the join.

    genomicDataset

      The right genomic dataset in the join.

    flankSize

      Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the left genomic dataset that did not overlap a key in the right genomic dataset.

    Definition Classes
      GenomicDataset
63.  def leftOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Coverage, Option[X]), (Coverage, Option[Y])]

    (R-specific) Performs a sort-merge left outer join between this genomic dataset and another genomic dataset.

    (R-specific) Performs a sort-merge left outer join between this genomic dataset and another genomic dataset.

    In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is a left outer join, all values in the right genomic dataset that do not overlap a value from the left genomic dataset are dropped. If a value from the left genomic dataset does not overlap any values in the right genomic dataset, it will be paired with a `None` in the product of the join.

    genomicDataset

      The right genomic dataset in the join.

    flankSize

      Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the left genomic dataset that did not overlap a key in the right genomic dataset.

    Definition Classes
      GenomicDataset
64.  def leftOuterShuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[Coverage], xTag: ClassTag[X], toxTag: ClassTag[(Coverage, Iterable[X])], uiyTag: scala.reflect.api.JavaUniverse.TypeTag[(Coverage, Seq[Y])]): GenericGenomicDataset[(Coverage, Iterable[X]), (Coverage, Seq[Y])]

    Performs a sort-merge left outer join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value.

    Performs a sort-merge left outer join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value.

    In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is a left outer join, all values in the right genomic dataset that do not overlap a value from the left genomic dataset are dropped. If a value from the left genomic dataset does not overlap any values in the right genomic dataset, it will be paired with an empty Iterable in the product of the join.

    genomicDataset

      The right genomic dataset in the join.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the left genomic dataset that did not overlap a key in the right genomic dataset.

    Definition Classes
      GenomicDataset
65.  def leftOuterShuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[Coverage], xTag: ClassTag[X], toxTag: ClassTag[(Coverage, Iterable[X])], uiyTag: scala.reflect.api.JavaUniverse.TypeTag[(Coverage, Seq[Y])]): GenericGenomicDataset[(Coverage, Iterable[X]), (Coverage, Seq[Y])]

    Performs a sort-merge left outer join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value.

    Performs a sort-merge left outer join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value.

    In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is a left outer join, all values in the right genomic dataset that do not overlap a value from the left genomic dataset are dropped. If a value from the left genomic dataset does not overlap any values in the right genomic dataset, it will be paired with an empty Iterable in the product of the join.

    genomicDataset

      The right genomic dataset in the join.

    flankSize

      Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the left genomic dataset that did not overlap a key in the right genomic dataset.

    Definition Classes
      GenomicDataset
66.  def leftOuterShuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Coverage, Iterable[X]), (Coverage, Seq[Y])]

    (Java-specific) Performs a sort-merge left outer join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value.

    (Java-specific) Performs a sort-merge left outer join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value.

    In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is a left outer join, all values in the right genomic dataset that do not overlap a value from the left genomic dataset are dropped. If a value from the left genomic dataset does not overlap any values in the right genomic dataset, it will be paired with an empty Iterable in the product of the join.

    genomicDataset

      The right genomic dataset in the join.

    flankSize

      Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the left genomic dataset that did not overlap a key in the right genomic dataset.

    Definition Classes
      GenomicDataset
67.  def leftOuterShuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Coverage, Iterable[X]), (Coverage, Seq[Y])]

    (R-specific) Performs a sort-merge left outer join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value.

    (R-specific) Performs a sort-merge left outer join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value.

    In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is a left outer join, all values in the right genomic dataset that do not overlap a value from the left genomic dataset are dropped. If a value from the left genomic dataset does not overlap any values in the right genomic dataset, it will be paired with an empty Iterable in the product of the join.

    genomicDataset

      The right genomic dataset in the join.

    flankSize

      Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the left genomic dataset that did not overlap a key in the right genomic dataset.

    Definition Classes
      GenomicDataset
68.  def logger: Logger
    Attributes
      protected
    Definition Classes
      Logging
69.  def loggerName: String
    Attributes
      protected
    Definition Classes
      Logging
70.  final def ne(arg0: AnyRef): Boolean
    Definition Classes
      AnyRef
71.  final def notify(): Unit
    Definition Classes
      AnyRef
    Annotations
      @native()
72.  final def notifyAll(): Unit
    Definition Classes
      AnyRef
    Annotations
      @native()
73.  val optLookbackPartitions: Option[Int]
    Definition Classes
      DatasetBoundCoverageDataset → DatasetBoundGenomicDataset
74.  val optPartitionBinSize: Option[Int]
    Definition Classes
      DatasetBoundCoverageDataset → DatasetBoundGenomicDataset
75.  lazy val optPartitionMap: None.type
    Attributes
      protected
    Definition Classes
      DatasetBoundCoverageDataset → GenomicDataset
76.  def persist(sl: StorageLevel): CoverageDataset

    Persists underlying RDD in memory or disk.

    Persists underlying RDD in memory or disk.

    sl

      new StorageLevel

    returns

      Persisted GenomicDataset.

    Definition Classes
      DatasetBoundGenomicDataset → GenomicDataset
77.  def pipe[X, Y <: Product, Z <: GenomicDataset[X, Y, Z], W <: InFormatter[Coverage, Coverage, CoverageDataset, W]](cmd: List[String], files: List[String], environment: Map[String, String], flankSize: Integer, tFormatter: Class[W], xFormatter: OutFormatter[X], convFn: Function2[CoverageDataset, RDD[X], Z]): Z

    (Java/Python-specific) Pipes genomic data to a subprocess that runs in parallel using Spark.

    (Java/Python-specific) Pipes genomic data to a subprocess that runs in parallel using Spark.

    X

      The type of the record created by the piped command.

    Y

      A GenomicDataset containing X's.

    cmd

      Command to run.

    files

      Files to make locally available to the commands being run. Default is empty.

    environment

      A map containing environment variable/value pairs to set in the environment for the newly created process. Default is empty.

    flankSize

      Number of bases to flank each command invocation by.

    tFormatter

      Class of formatter for data going into pipe command.

    xFormatter

      Formatter for data coming out of the pipe command.

    convFn

      The conversion function used to build the final genomic dataset.

    returns

      Returns a new GenomicDataset of type Y.

    Definition Classes
      GenomicDataset
78.  def pipe[X, Y <: Product, Z <: GenomicDataset[X, Y, Z], W <: InFormatter[Coverage, Coverage, CoverageDataset, W]](cmd: Seq[Any], files: Seq[Any], environment: Map[Any, Any], flankSize: Double, tFormatter: Class[W], xFormatter: OutFormatter[X], convFn: Function2[CoverageDataset, RDD[X], Z]): Z

    (R-specific) Pipes genomic data to a subprocess that runs in parallel using Spark.

    (R-specific) Pipes genomic data to a subprocess that runs in parallel using Spark.

    X

      The type of the record created by the piped command.

    Y

      A GenomicDataset containing X's.

    cmd

      Command to run.

    files

      Files to make locally available to the commands being run. Default is empty.

    environment

      A map containing environment variable/value pairs to set in the environment for the newly created process. Default is empty.

    flankSize

      Number of bases to flank each command invocation by.

    tFormatter

      Class of formatter for data going into pipe command.

    xFormatter

      Formatter for data coming out of the pipe command.

    convFn

      The conversion function used to build the final genomic dataset.

    returns

      Returns a new GenomicDataset of type Y.

    Definition Classes
      GenomicDataset
79.  def pipe[X, Y <: Product, Z <: GenomicDataset[X, Y, Z], W <: InFormatter[Coverage, Coverage, CoverageDataset, W]](cmd: Seq[String], files: Seq[String] = Seq.empty, environment: Map[String, String] = Map.empty, flankSize: Int = 0, optTimeout: Option[Int] = None)(implicit tFormatterCompanion: InFormatterCompanion[Coverage, Coverage, CoverageDataset, W], xFormatter: OutFormatter[X], convFn: (CoverageDataset, RDD[X]) ⇒ Z, tManifest: ClassTag[Coverage], xManifest: ClassTag[X]): Z

    (Scala-specific) Pipes genomic data to a subprocess that runs in parallel using Spark.

    (Scala-specific) Pipes genomic data to a subprocess that runs in parallel using Spark.

    Files are substituted in to the command with a $x syntax. E.g., to invoke a command that uses the first file from the files Seq, use $0. To access the path to the directory where the files are copied, use $root.

    Pipes require the presence of an InFormatterCompanion and an OutFormatter as implicit values. The InFormatterCompanion should be a singleton whose apply method builds an InFormatter given a specific type of GenomicDataset. The implicit InFormatterCompanion yields an InFormatter which is used to format the input to the pipe, and the implicit OutFormatter is used to parse the output from the pipe.

    X

      The type of the record created by the piped command.

    Y

      A GenomicDataset containing X's.

    cmd

      Command to run.

    files

      Files to make locally available to the commands being run. Default is empty.

    environment

      A map containing environment variable/value pairs to set in the environment for the newly created process. Default is empty.

    flankSize

      Number of bases to flank each command invocation by.

    optTimeout

      An optional parameter specifying how long to let a single partition run for, in seconds. If the partition times out, the partial results will be returned, and no exception will be logged. The partition will log that the command timed out.

    returns

      Returns a new GenomicDataset of type Y.

    Definition Classes
      GenomicDataset
80.  val productFn: (Coverage) ⇒ Coverage
    Attributes
      protected
    Definition Classes
      CoverageDataset → GenomicDataset
81.  lazy val rdd: RDD[Coverage]

    The RDD of genomic data that we are wrapping.

    The RDD of genomic data that we are wrapping.

    Definition Classes
      DatasetBoundCoverageDataset → GenomicDataset
82.  def replaceRdd(newRdd: RDD[Coverage], newPartitionMap: Option[Array[Option[(ReferenceRegion, ReferenceRegion)]]] = None): CoverageDataset

    newRdd

      The RDD to replace the underlying RDD with.

    returns

      Returns a new CoverageDataset with the underlying RDD replaced.

    Attributes
      protected
    Definition Classes
      CoverageDataset → GenomicDataset
83.  def replaceSamples(newSamples: Iterable[Sample]): CoverageDataset

    Replaces the sample metadata attached to the genomic dataset.

    Replaces the sample metadata attached to the genomic dataset.

    newSamples

      The new sample metadata to attach.

    returns

      A GenomicDataset with new sample metadata.

    Definition Classes
      DatasetBoundCoverageDataset → MultisampleGenomicDataset
84.  def replaceSequences(newSequences: SequenceDictionary): CoverageDataset

    Replaces the sequence dictionary attached to a GenomicDataset.

    Replaces the sequence dictionary attached to a GenomicDataset.

    newSequences

      The new sequence dictionary to attach.

    returns

      Returns a new GenomicDataset with the sequences replaced.

    Definition Classes
      DatasetBoundCoverageDataset → GenomicDataset
85.  def rightOuterBroadcastRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[Coverage], xTag: ClassTag[X], otxTag: ClassTag[(Option[Coverage], X)], ouyTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[Coverage], Y)]): GenericGenomicDataset[(Option[Coverage], X), (Option[Coverage], Y)]

    Performs a broadcast right outer join between this genomic dataset and another genomic dataset.

    Performs a broadcast right outer join between this genomic dataset and another genomic dataset.

    In a broadcast join, the left genomic dataset (this genomic dataset) is collected to the driver, and broadcast to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is a right outer join, all values in the left genomic dataset that do not overlap a value from the right genomic dataset are dropped. If a value from the right genomic dataset does not overlap any values in the left genomic dataset, it will be paired with a `None` in the product of the join.

    genomicDataset

      The right genomic dataset in the join.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the right genomic dataset that did not overlap a key in the left genomic dataset.

    Definition Classes
      GenomicDataset
    See also

      rightOuterBroadcastRegionJoin

86.  def rightOuterBroadcastRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[Coverage], xTag: ClassTag[X], otxTag: ClassTag[(Option[Coverage], X)], ouyTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[Coverage], Y)]): GenericGenomicDataset[(Option[Coverage], X), (Option[Coverage], Y)]

    Performs a broadcast right outer join between this genomic dataset and another genomic dataset.

    Performs a broadcast right outer join between this genomic dataset and another genomic dataset.

    In a broadcast join, the left genomic dataset (this genomic dataset) is collected to the driver, and broadcast to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is a right outer join, all values in the left genomic dataset that do not overlap a value from the right genomic dataset are dropped. If a value from the right genomic dataset does not overlap any values in the left genomic dataset, it will be paired with a `None` in the product of the join.

    genomicDataset

      The right genomic dataset in the join.

    flankSize

      Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the right genomic dataset that did not overlap a key in the left genomic dataset.

    Definition Classes
      GenomicDataset
    See also

      rightOuterBroadcastRegionJoin

87.  def rightOuterBroadcastRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Option[Coverage], X), (Option[Coverage], Y)]

    (Java-specific) Performs a broadcast right outer join between this genomic dataset and another genomic dataset.

    (Java-specific) Performs a broadcast right outer join between this genomic dataset and another genomic dataset.

    In a broadcast join, the left genomic dataset (this genomic dataset) is collected to the driver, and broadcast to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is a right outer join, all values in the left genomic dataset that do not overlap a value from the right genomic dataset are dropped. If a value from the right genomic dataset does not overlap any values in the left genomic dataset, it will be paired with a `None` in the product of the join.

    genomicDataset

      The right genomic dataset in the join.

    flankSize

      Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the right genomic dataset that did not overlap a key in the left genomic dataset.

    Definition Classes
      GenomicDataset
88.  def rightOuterBroadcastRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Option[Coverage], X), (Option[Coverage], Y)]

    (R-specific) Performs a broadcast right outer join between this genomic dataset and another genomic dataset.

    (R-specific) Performs a broadcast right outer join between this genomic dataset and another genomic dataset.

    In a broadcast join, the left genomic dataset (this genomic dataset) is collected to the driver, and broadcast to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is a right outer join, all values in the left genomic dataset that do not overlap a value from the right genomic dataset are dropped. If a value from the right genomic dataset does not overlap any values in the left genomic dataset, it will be paired with a `None` in the product of the join.

    genomicDataset

      The right genomic dataset in the join.

    flankSize

      Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the right genomic dataset that did not overlap a key in the left genomic dataset.

    Definition Classes
      GenomicDataset
89.  def rightOuterBroadcastRegionJoinAgainst[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](broadcast: GenomicBroadcast[X, Y, Z])(implicit tTag: ClassTag[Coverage], xTag: ClassTag[X], oyuTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[Y], Coverage)]): GenericGenomicDataset[(Option[X], Coverage), (Option[Y], Coverage)]

    Performs a broadcast right outer join between this genomic dataset and data that has been broadcast.

    Performs a broadcast right outer join between this genomic dataset and data that has been broadcast.

    In a broadcast join, the left side of the join (broadcastTree) is broadcast to to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is a right outer join, all values in the left table that do not overlap a value from the right genomic dataset are dropped. If a value from the right genomic dataset does not overlap any values in the left table, it will be paired with a `None` in the product of the join. As compared to broadcastRegionJoin, this function allows the broadcast object to be reused across multiple joins.

    broadcast

      The data on the left side of the join.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space.

    Definition Classes
      GenomicDataset
    Note

      This function differs from other region joins as it treats the calling genomic dataset as the right side of the join, and not the left.

    See also

      rightOuterBroadcastRegionJoin

90.  def rightOuterBroadcastRegionJoinAgainstAndGroupByRight[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](broadcast: GenomicBroadcast[X, Y, Z])(implicit tTag: ClassTag[Coverage], xTag: ClassTag[X], syuTag: scala.reflect.api.JavaUniverse.TypeTag[(Seq[Y], Coverage)]): GenericGenomicDataset[(Iterable[X], Coverage), (Seq[Y], Coverage)]

    Performs a broadcast right outer join between this genomic dataset and another genomic dataset.

    Performs a broadcast right outer join between this genomic dataset and another genomic dataset.

    In a broadcast join, the left side of the join (broadcastTree) is broadcast to to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is a right outer join, all values in the left table that do not overlap a value from the right genomic dataset are dropped. If a value from the right genomic dataset does not overlap any values in the left table, it will be paired with a `None` in the product of the join. As compared to broadcastRegionJoin, this function allows the broadcast object to be reused across multiple joins.

    broadcast

      The data on the left side of the join.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space.

    Definition Classes
      GenomicDataset
    Note

      This function differs from other region joins as it treats the calling genomic dataset as the right side of the join, and not the left.

    See also

      rightOuterBroadcastRegionJoinAndGroupByRight

91.  def rightOuterBroadcastRegionJoinAndGroupByRight[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[Coverage], xTag: ClassTag[X], itxTag: ClassTag[(Iterable[Coverage], X)], iuyTag: scala.reflect.api.JavaUniverse.TypeTag[(Seq[Coverage], Y)]): GenericGenomicDataset[(Iterable[Coverage], X), (Seq[Coverage], Y)]

    Performs a broadcast right outer join between this genomic dataset and another genomic dataset.

    Performs a broadcast right outer join between this genomic dataset and another genomic dataset.

    In a broadcast join, the left side of the join (broadcastTree) is broadcast to to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is a right outer join, all values in the left genomic dataset that do not overlap a value from the right genomic dataset are dropped. If a value from the right genomic dataset does not overlap any values in the left genomic dataset, it will be paired with a `None` in the product of the join.

    genomicDataset

      The right genomic dataset in the join.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the right genomic dataset that did not overlap a key in the left genomic dataset.

    Definition Classes
      GenomicDataset
    See also

      rightOuterBroadcastRegionJoinAgainstAndGroupByRight

92.  def rightOuterBroadcastRegionJoinAndGroupByRight[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[Coverage], xTag: ClassTag[X], itxTag: ClassTag[(Iterable[Coverage], X)], iuyTag: scala.reflect.api.JavaUniverse.TypeTag[(Seq[Coverage], Y)]): GenericGenomicDataset[(Iterable[Coverage], X), (Seq[Coverage], Y)]

    Performs a broadcast right outer join between this genomic dataset and another genomic dataset.

    Performs a broadcast right outer join between this genomic dataset and another genomic dataset.

    In a broadcast join, the left side of the join (broadcastTree) is broadcast to to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is a right outer join, all values in the left genomic dataset that do not overlap a value from the right genomic dataset are dropped. If a value from the right genomic dataset does not overlap any values in the left genomic dataset, it will be paired with a `None` in the product of the join.

    genomicDataset

      The right genomic dataset in the join.

    flankSize

      Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the right genomic dataset that did not overlap a key in the left genomic dataset.

    Definition Classes
      GenomicDataset
    See also

      rightOuterBroadcastRegionJoinAgainstAndGroupByRight

93.  def rightOuterBroadcastRegionJoinAndGroupByRight[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Iterable[Coverage], X), (Seq[Coverage], Y)]

    (Java-specific) Performs a broadcast right outer join between this genomic dataset and another genomic dataset.

    (Java-specific) Performs a broadcast right outer join between this genomic dataset and another genomic dataset.

    In a broadcast join, the left side of the join (broadcastTree) is broadcast to to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is a right outer join, all values in the left genomic dataset that do not overlap a value from the right genomic dataset are dropped. If a value from the right genomic dataset does not overlap any values in the left genomic dataset, it will be paired with a `None` in the product of the join.

    genomicDataset

      The right genomic dataset in the join.

    flankSize

      Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the right genomic dataset that did not overlap a key in the left genomic dataset.

    Definition Classes
      GenomicDataset
    See also

      rightOuterBroadcastRegionJoinAgainstAndGroupByRight

94.  def rightOuterBroadcastRegionJoinAndGroupByRight[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Iterable[Coverage], X), (Seq[Coverage], Y)]

    (R-specific) Performs a broadcast right outer join between this genomic dataset and another genomic dataset.

    (R-specific) Performs a broadcast right outer join between this genomic dataset and another genomic dataset.

    In a broadcast join, the left side of the join (broadcastTree) is broadcast to to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is a right outer join, all values in the left genomic dataset that do not overlap a value from the right genomic dataset are dropped. If a value from the right genomic dataset does not overlap any values in the left genomic dataset, it will be paired with a `None` in the product of the join.

    genomicDataset

      The right genomic dataset in the join.

    flankSize

      Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the right genomic dataset that did not overlap a key in the left genomic dataset.

    Definition Classes
      GenomicDataset
    See also

      rightOuterBroadcastRegionJoinAgainstAndGroupByRight

95.  def rightOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[Coverage], xTag: ClassTag[X], otxTag: ClassTag[(Option[Coverage], X)], ouyTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[Coverage], Y)]): GenericGenomicDataset[(Option[Coverage], X), (Option[Coverage], Y)]

    Performs a sort-merge right outer join between this genomic dataset and another genomic dataset.

    Performs a sort-merge right outer join between this genomic dataset and another genomic dataset.

    In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is a right outer join, all values in the left genomic dataset that do not overlap a value from the right genomic dataset are dropped. If a value from the right genomic dataset does not overlap any values in the left genomic dataset, it will be paired with a `None` in the product of the join.

    genomicDataset

      The right genomic dataset in the join.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the right genomic dataset that did not overlap a key in the left genomic dataset.

    Definition Classes
      GenomicDataset
96.  def rightOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[Coverage], xTag: ClassTag[X], otxTag: ClassTag[(Option[Coverage], X)], ouyTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[Coverage], Y)]): GenericGenomicDataset[(Option[Coverage], X), (Option[Coverage], Y)]

    Performs a sort-merge right outer join between this genomic dataset and another genomic dataset.

    Performs a sort-merge right outer join between this genomic dataset and another genomic dataset.

    In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is a right outer join, all values in the left genomic dataset that do not overlap a value from the right genomic dataset are dropped. If a value from the right genomic dataset does not overlap any values in the left genomic dataset, it will be paired with a `None` in the product of the join.

    genomicDataset

      The right genomic dataset in the join.

    flankSize

      Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the right genomic dataset that did not overlap a key in the left genomic dataset.

    Definition Classes
      GenomicDataset
97.  def rightOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Option[Coverage], X), (Option[Coverage], Y)]

    (Java-specific) Performs a sort-merge right outer join between this genomic dataset and another genomic dataset.

    (Java-specific) Performs a sort-merge right outer join between this genomic dataset and another genomic dataset.

    In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is a right outer join, all values in the left genomic dataset that do not overlap a value from the right genomic dataset are dropped. If a value from the right genomic dataset does not overlap any values in the left genomic dataset, it will be paired with a `None` in the product of the join.

    genomicDataset

      The right genomic dataset in the join.

    flankSize

      Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the right genomic dataset that did not overlap a key in the left genomic dataset.

    Definition Classes
      GenomicDataset
98.  def rightOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Option[Coverage], X), (Option[Coverage], Y)]

    (R-specific) Performs a sort-merge right outer join between this genomic dataset and another genomic dataset.

    (R-specific) Performs a sort-merge right outer join between this genomic dataset and another genomic dataset.

    In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is a right outer join, all values in the left genomic dataset that do not overlap a value from the right genomic dataset are dropped. If a value from the right genomic dataset does not overlap any values in the left genomic dataset, it will be paired with a `None` in the product of the join.

    genomicDataset

      The right genomic dataset in the join.

    flankSize

      Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the right genomic dataset that did not overlap a key in the left genomic dataset.

    Definition Classes
      GenomicDataset
99.  def rightOuterShuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[Coverage], xTag: ClassTag[X], otixTag: ClassTag[(Option[Coverage], Iterable[X])], otsyTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[Coverage], Seq[Y])]): GenericGenomicDataset[(Option[Coverage], Iterable[X]), (Option[Coverage], Seq[Y])]

    Performs a sort-merge right outer join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value, if not null.

    Performs a sort-merge right outer join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value, if not null.

    In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. In the same operation, we group all values by the left item in the genomic dataset. Since this is a right outer join, all values from the right genomic dataset who did not overlap a value from the left genomic dataset are placed into a length-1 Iterable with a `None` key.

    genomicDataset

      The right genomic dataset in the join.

    returns

      Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, grouped together by the value they overlapped in the left genomic dataset, and all values from the right genomic dataset that did not overlap an item in the left genomic dataset.

    Definition Classes
      GenomicDataset
100.  def rightOuterShuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[Coverage], xTag: ClassTag[X], otixTag: ClassTag[(Option[Coverage], Iterable[X])], ousyTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[Coverage], Seq[Y])]): GenericGenomicDataset[(Option[Coverage], Iterable[X]), (Option[Coverage], Seq[Y])]

     Performs a sort-merge right outer join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value, if not null.

     Performs a sort-merge right outer join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value, if not null.

     In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. In the same operation, we group all values by the left item in the genomic dataset. Since this is a right outer join, all values from the right genomic dataset who did not overlap a value from the left genomic dataset are placed into a length-1 Iterable with a `None` key.

     genomicDataset

       The right genomic dataset in the join.

     flankSize

       Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

     returns

       Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, grouped together by the value they overlapped in the left genomic dataset, and all values from the right genomic dataset that did not overlap an item in the left genomic dataset.

     Definition Classes
       GenomicDataset
101.  def rightOuterShuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Option[Coverage], Iterable[X]), (Option[Coverage], Seq[Y])]

     (Java-specific) Performs a sort-merge right outer join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value, if not null.

     (Java-specific) Performs a sort-merge right outer join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value, if not null.

     In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. In the same operation, we group all values by the left item in the genomic dataset. Since this is a right outer join, all values from the right genomic dataset who did not overlap a value from the left genomic dataset are placed into a length-1 Iterable with a `None` key.

     genomicDataset

       The right genomic dataset in the join.

     flankSize

       Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

     returns

       Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, grouped together by the value they overlapped in the left genomic dataset, and all values from the right genomic dataset that did not overlap an item in the left genomic dataset.

     Definition Classes
       GenomicDataset
102.  def rightOuterShuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Option[Coverage], Iterable[X]), (Option[Coverage], Seq[Y])]

     (R-specific) Performs a sort-merge right outer join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value, if not null.

     (R-specific) Performs a sort-merge right outer join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value, if not null.

     In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. In the same operation, we group all values by the left item in the genomic dataset. Since this is a right outer join, all values from the right genomic dataset who did not overlap a value from the left genomic dataset are placed into a length-1 Iterable with a `None` key.

     genomicDataset

       The right genomic dataset in the join.

     flankSize

       Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

     returns

       Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, grouped together by the value they overlapped in the left genomic dataset, and all values from the right genomic dataset that did not overlap an item in the left genomic dataset.

     Definition Classes
       GenomicDataset
103.  val samples: Seq[Sample]

     The samples who have data contained in this GenomicDataset.

     The samples who have data contained in this GenomicDataset.

     Definition Classes
       DatasetBoundCoverageDataset → MultisampleGenomicDataset
104.  def save(filePath: String, asSingleFile: Boolean, disableFastConcat: Boolean): Unit

     Saves coverage as feature file.

     Saves coverage as feature file.

     filePath

       The location to write the output.

     asSingleFile

       If false, writes file to disk as shards with one shard per partition. If true, we save the file to disk as a single file by merging the shards.

     disableFastConcat

       If asSingleFile is true, disables the use of the fast file concatenation engine.

     Definition Classes
       CoverageDataset
     See also

       FeatureDataset.save Coverage is saved as a feature where coverage is stored in the score column and sampleId is stored in attributes, if available.

105.  def saveAsParquet(filePath: String, blockSize: Int = 128 * 1024 * 1024, pageSize: Int = 1 * 1024 * 1024, compressionCodec: CompressionCodecName = CompressionCodecName.GZIP, disableDictionaryEncoding: Boolean = false): Unit

     Saves a genomic dataset to Parquet.

     Saves a genomic dataset to Parquet.

     blockSize

       The size in bytes of blocks to write.

     pageSize

       The size in bytes of pages to write.

     compressionCodec

       The compression codec to apply to pages.

     disableDictionaryEncoding

       If false, dictionary encoding is used. If true, delta encoding is used.

     Definition Classes
       CoverageDataset → GenomicDataset
106.  def saveAsParquet(args: SaveArgs): Unit

     Saves a genomic dataset to Parquet.

     Saves a genomic dataset to Parquet.

     args

       The output format configuration to use when saving the data.

     Definition Classes
       GenomicDataset
107.  def saveAsPartitionedParquet(pathName: String, compressionCodec: CompressionCodecName = CompressionCodecName.GZIP, partitionSize: Int = 1000000): Unit

     Saves this RDD to disk in range binned partitioned Parquet format.

     Saves this RDD to disk in range binned partitioned Parquet format.

     pathName

       The path to save the partitioned Parquet file to.

     compressionCodec

       Name of the compression codec to use.

     partitionSize

       Size of partitions used when writing Parquet, in base pairs (bp). Defaults to 1,000,000 bp.

     Definition Classes
       GenomicDataset
108.  def saveAvro[U <: SpecificRecordBase](pathName: String, sc: SparkContext, schema: Schema, avro: Seq[U])(implicit tUag: ClassTag[U]): Unit

     Saves Avro data to a Hadoop file system.

     Saves Avro data to a Hadoop file system.

     This method uses a SparkContext to identify our underlying file system, which we then save to.

     Frustratingly enough, although all records generated by the Avro IDL compiler have a static SCHEMA$ field, this field does not belong to the SpecificRecordBase abstract class, or the SpecificRecord interface. As such, we must force the user to pass in the schema.

     U

       The type of the specific record we are saving.

     pathName

       Path to save records to.

     sc

       SparkContext used for identifying underlying file system.

     schema

       Schema of records we are saving.

     avro

       Seq of records we are saving.

     Attributes
       protected
     Definition Classes
       GenomicDataset
109.  def saveMetadata(pathName: String): Unit

     Writes any necessary metadata to disk.

     Writes any necessary metadata to disk. If not overridden, writes the sequence dictionary to disk as Avro.

     pathName

       The path to save metadata to.

     Attributes
       protected
     Definition Classes
       GenomicDataset
110.  def saveSamples(pathName: String): Unit

     Save the samples to disk.

     Save the samples to disk.

     pathName

       The path to save samples to.

     Attributes
       protected
     Definition Classes
       MultisampleGenomicDataset
111.  def saveSequences(pathName: String): Unit

     Save the sequence dictionary to disk.

     Save the sequence dictionary to disk.

     pathName

       The path to save the sequence dictionary to.

     Attributes
       protected
     Definition Classes
       GenomicDataset
112.  val sequences: SequenceDictionary

     The sequence dictionary describing the reference assembly this dataset is aligned to.

     The sequence dictionary describing the reference assembly this dataset is aligned to.

     Definition Classes
       DatasetBoundCoverageDataset → GenomicDataset
113.  def shuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[Coverage], xTag: ClassTag[X], txTag: ClassTag[(Coverage, X)], uyTag: scala.reflect.api.JavaUniverse.TypeTag[(Coverage, Y)]): GenericGenomicDataset[(Coverage, X), (Coverage, Y)]

     Performs a sort-merge inner join between this genomic dataset and another genomic dataset.

     Performs a sort-merge inner join between this genomic dataset and another genomic dataset.

     In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is an inner join, all values who do not overlap a value from the other genomic dataset are dropped.

     genomicDataset

       The right genomic dataset in the join.

     returns

       Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space.

     Definition Classes
       GenomicDataset
114.  def shuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[Coverage], xTag: ClassTag[X], txTag: ClassTag[(Coverage, X)], uyTag: scala.reflect.api.JavaUniverse.TypeTag[(Coverage, Y)]): GenericGenomicDataset[(Coverage, X), (Coverage, Y)]

     Performs a sort-merge inner join between this genomic dataset and another genomic dataset.

     Performs a sort-merge inner join between this genomic dataset and another genomic dataset.

     In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is an inner join, all values who do not overlap a value from the other genomic dataset are dropped.

     genomicDataset

       The right genomic dataset in the join.

     flankSize

       Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

     returns

       Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space.

     Definition Classes
       GenomicDataset
115.  def shuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Coverage, X), (Coverage, Y)]

     (Java-specific) Performs a sort-merge inner join between this genomic dataset and another genomic dataset.

     (Java-specific) Performs a sort-merge inner join between this genomic dataset and another genomic dataset.

     In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is an inner join, all values who do not overlap a value from the other genomic dataset are dropped.

     genomicDataset

       The right genomic dataset in the join.

     flankSize

       Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

     returns

       Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space.

     Definition Classes
       GenomicDataset
116.  def shuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Coverage, X), (Coverage, Y)]

     (R-specific) Performs a sort-merge inner join between this genomic dataset and another genomic dataset.

     (R-specific) Performs a sort-merge inner join between this genomic dataset and another genomic dataset.

     In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is an inner join, all values who do not overlap a value from the other genomic dataset are dropped.

     genomicDataset

       The right genomic dataset in the join.

     flankSize

       Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

     returns

       Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space.

     Definition Classes
       GenomicDataset
117.  def shuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[Coverage], xTag: ClassTag[X], tixTag: ClassTag[(Coverage, Iterable[X])], uiyTag: scala.reflect.api.JavaUniverse.TypeTag[(Coverage, Seq[Y])]): GenericGenomicDataset[(Coverage, Iterable[X]), (Coverage, Seq[Y])]

     Performs a sort-merge inner join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value.

     Performs a sort-merge inner join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value.

     In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is an inner join, all values who do not overlap a value from the other genomic dataset are dropped. In the same operation, we group all values by the left item in the genomic dataset.

     genomicDataset

       The right genomic dataset in the join.

     returns

       Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, grouped together by the value they overlapped in the left genomic dataset.

     Definition Classes
       GenomicDataset
118.  def shuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[Coverage], xTag: ClassTag[X], tixTag: ClassTag[(Coverage, Iterable[X])], uiyTag: scala.reflect.api.JavaUniverse.TypeTag[(Coverage, Seq[Y])]): GenericGenomicDataset[(Coverage, Iterable[X]), (Coverage, Seq[Y])]

     Performs a sort-merge inner join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value.

     Performs a sort-merge inner join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value.

     In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is an inner join, all values who do not overlap a value from the other genomic dataset are dropped. In the same operation, we group all values by the left item in the genomic dataset.

     genomicDataset

       The right genomic dataset in the join.

     flankSize

       Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

     returns

       Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, grouped together by the value they overlapped in the left genomic dataset.

     Definition Classes
       GenomicDataset
119.  def shuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Coverage, Iterable[X]), (Coverage, Seq[Y])]

     (Java-specific) Performs a sort-merge inner join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value.

     (Java-specific) Performs a sort-merge inner join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value.

     In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. In the same operation, we group all values by the left item in the genomic dataset.

     genomicDataset

       The right genomic dataset in the join.

     flankSize

       Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

     returns

       Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, grouped together by the value they overlapped in the left genomic dataset.

     Definition Classes
       GenomicDataset
120.  def shuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Coverage, Iterable[X]), (Coverage, Seq[Y])]

     (R-specific) Performs a sort-merge inner join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value.

     (R-specific) Performs a sort-merge inner join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value.

     In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. In the same operation, we group all values by the left item in the genomic dataset.

     genomicDataset

       The right genomic dataset in the join.

     flankSize

       Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.

     returns

       Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, grouped together by the value they overlapped in the left genomic dataset.

     Definition Classes
       GenomicDataset
121.  def sort(partitions: Int = rdd.partitions.length, stringency: ValidationStringency = ValidationStringency.STRICT)(implicit tTag: ClassTag[Coverage]): CoverageDataset

     Sorts our genome aligned data by reference positions, with references ordered by index.

     Sorts our genome aligned data by reference positions, with references ordered by index.

     partitions

       The number of partitions for the new genomic dataset.

     stringency

       The level of ValidationStringency to enforce.

     returns

       Returns a new genomic dataset containing sorted data.

     Definition Classes
       GenomicDataset
     Note

       Uses ValidationStringency to handle unaligned or where objects align to multiple positions.

     See also

       sortLexicographically

122.  def sort(): CoverageDataset

     Sorts our genome aligned data by reference positions, with references ordered by index.

     Sorts our genome aligned data by reference positions, with references ordered by index.

     returns

       Returns a new genomic dataset containing sorted data.

     Definition Classes
       GenomicDataset
     See also

       sortLexicographically

123.  def sortLexicographically(partitions: Int = rdd.partitions.length, storePartitionMap: Boolean = false, storageLevel: StorageLevel = StorageLevel.MEMORY_ONLY, stringency: ValidationStringency = ValidationStringency.STRICT)(implicit tTag: ClassTag[Coverage]): CoverageDataset

     Sorts our genome aligned data by reference positions, with references ordered lexicographically.

     Sorts our genome aligned data by reference positions, with references ordered lexicographically.

     partitions

       The number of partitions for the new genomic dataset.

     storePartitionMap

       A Boolean flag to determine whether to store the partition bounds from the resulting genomic dataset.

     storageLevel

       The level at which to persist the resulting genomic dataset.

     stringency

       The level of ValidationStringency to enforce.

     returns

       Returns a new genomic dataset containing sorted data.

     Definition Classes
       GenomicDataset
     Note

       Uses ValidationStringency to handle data that is unaligned or where objects align to multiple positions.

     See also

       sort

124.  def sortLexicographically(): CoverageDataset

     Sorts our genome aligned data by reference positions, with references ordered lexicographically.

     Sorts our genome aligned data by reference positions, with references ordered lexicographically.

     returns

       Returns a new genomic dataset containing sorted data.

     Definition Classes
       GenomicDataset
     See also

       sort

125.  lazy val spark: SparkSession
     Definition Classes
       GenomicDataset
     Annotations
       @transient()
126.  final def synchronized[T0](arg0: ⇒ T0): T0
     Definition Classes
       AnyRef
127.  def toDF(): DataFrame

     returns

       These data as a Spark SQL DataFrame.

     Definition Classes
       GenomicDataset
128.  def toFeatures(): FeatureDataset

     Converts CoverageDataset to FeatureDataset.

     Converts CoverageDataset to FeatureDataset.

     returns

       Returns a FeatureDataset from CoverageDataset.

     Definition Classes
       DatasetBoundCoverageDataset → CoverageDataset
129.  def toString(): String
     Definition Classes
       MultisampleGenomicDataset → GenomicDataset → AnyRef → Any
130.  def trace(mkr: Marker, msg: ⇒ Any, t: ⇒ Throwable): Unit
     Attributes
       protected
     Definition Classes
       Logging
131.  def trace(msg: ⇒ Any, t: ⇒ Throwable): Unit
     Attributes
       protected
     Definition Classes
       Logging
132.  def trace(msg: ⇒ Any): Unit
     Attributes
       protected
     Definition Classes
       Logging
133.  def transform(tFn: Function[JavaRDD[Coverage], JavaRDD[Coverage]]): CoverageDataset

     (Java-specific) Applies a function that transforms the underlying RDD into a new RDD.

     (Java-specific) Applies a function that transforms the underlying RDD into a new RDD.

     tFn

       A function that transforms the underlying RDD.

     returns

       A new genomic dataset where the RDD of genomic data has been replaced, but the metadata (sequence dictionary, and etc) are copied without modification.

     Definition Classes
       GenomicDataset
134.  def transform(tFn: (RDD[Coverage]) ⇒ RDD[Coverage]): CoverageDataset

     (Scala-specific) Applies a function that transforms the underlying RDD into a new RDD.

     (Scala-specific) Applies a function that transforms the underlying RDD into a new RDD.

     tFn

       A function that transforms the underlying RDD.

     returns

       A new genomic dataset where the RDD of genomic data has been replaced, but the metadata (sequence dictionary, and etc) are copied without modification.

     Definition Classes
       GenomicDataset
135.  def transformDataFrame(tFn: Function[DataFrame, DataFrame]): CoverageDataset

     (Java-specific) Applies a function that transforms the underlying DataFrame into a new DataFrame using the Spark SQL API.

     (Java-specific) Applies a function that transforms the underlying DataFrame into a new DataFrame using the Spark SQL API.

     tFn

       A function that transforms the underlying DataFrame as a DataFrame.

     returns

       A new genomic dataset where the DataFrame of genomic data has been replaced, but the metadata (sequence dictionary, and etc) are copied without modification.

     Definition Classes
       GenomicDataset
136.  def transformDataFrame(tFn: (DataFrame) ⇒ DataFrame)(implicit uTag: scala.reflect.api.JavaUniverse.TypeTag[Coverage]): CoverageDataset

     (Scala-specific) Applies a function that transforms the underlying DataFrame into a new DataFrame using the Spark SQL API.

     (Scala-specific) Applies a function that transforms the underlying DataFrame into a new DataFrame using the Spark SQL API.

     tFn

       A function that transforms the underlying data as a DataFrame.

     returns

       A new genomic dataset where the DataFrame of genomic data has been replaced, but the metadata (sequence dictionary, and etc) are copied without modification.

     Definition Classes
       GenomicDataset
137.  def transformDataset(tFn: Function[Dataset[Coverage], Dataset[Coverage]]): CoverageDataset

     (Java-specific) Applies a function that transforms the underlying Dataset into a new Dataset using the Spark SQL API.

     (Java-specific) Applies a function that transforms the underlying Dataset into a new Dataset using the Spark SQL API.

     tFn

       A function that transforms the underlying Dataset as a Dataset.

     returns

       A new genomic dataset where the Dataset of genomic data has been replaced, but the metadata (sequence dictionary, and etc) are copied without modification.

     Definition Classes
       CoverageDataset → GenomicDataset
138.  def transformDataset(tFn: (Dataset[Coverage]) ⇒ Dataset[Coverage]): CoverageDataset

     (Scala-specific) Applies a function that transforms the underlying Dataset into a new Dataset using the Spark SQL API.

     (Scala-specific) Applies a function that transforms the underlying Dataset into a new Dataset using the Spark SQL API.

     tFn

       A function that transforms the underlying Dataset as a Dataset.

     returns

       A new genomic dataset where the Dataset of genomic data has been replaced, but the metadata (sequence dictionary, and etc) are copied without modification.

     Definition Classes
       CoverageDataset → GenomicDataset
139.  def transmute[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](tFn: Function[JavaRDD[Coverage], JavaRDD[X]], convFn: Function2[CoverageDataset, RDD[X], Z]): Z

     (Java-specific) Applies a function that transmutes the underlying RDD into a new RDD of a different type.

     (Java-specific) Applies a function that transmutes the underlying RDD into a new RDD of a different type.

     tFn

       A function that transforms the underlying RDD.

     convFn

       The conversion function used to build the final RDD.

     returns

       A new genomid dataset where the RDD of genomic data has been replaced, but the metadata (sequence dictionary, and etc) are copied without modification.

     Definition Classes
       GenomicDataset
140.  def transmute[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](tFn: (RDD[Coverage]) ⇒ RDD[X])(implicit convFn: (CoverageDataset, RDD[X]) ⇒ Z): Z

     (Scala-specific) Applies a function that transmutes the underlying RDD into a new RDD of a different type.

     (Scala-specific) Applies a function that transmutes the underlying RDD into a new RDD of a different type.

     tFn

       A function that transforms the underlying RDD.

     returns

       A new genomic dataset where the RDD of genomic data has been replaced, but the metadata (sequence dictionary, and etc) are copied without modification.

     Definition Classes
       GenomicDataset
141.  def transmuteDataFrame[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](tFn: Function[DataFrame, DataFrame], convFn: GenomicDatasetConversion[Coverage, Coverage, CoverageDataset, X, Y, Z]): Z

     (Java-specific) Applies a function that transmutes the underlying DataFrame into a new DataFrame of a different type.

     (Java-specific) Applies a function that transmutes the underlying DataFrame into a new DataFrame of a different type.

     tFn

       A function that transforms the underlying DataFrame.

     returns

       A new genomic dataset where the DataFrame of genomic data has been replaced, but the metadata (sequence dictionary, and etc) are copied without modification.

     Definition Classes
       GenomicDataset
142.  def transmuteDataFrame[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](tFn: (DataFrame) ⇒ DataFrame)(implicit yTag: scala.reflect.api.JavaUniverse.TypeTag[Y], convFn: (CoverageDataset, Dataset[Y]) ⇒ Z): Z

     (Java-specific) Applies a function that transmutes the underlying DataFrame into a new DataFrame of a different type.

     (Java-specific) Applies a function that transmutes the underlying DataFrame into a new DataFrame of a different type.

     tFn

       A function that transforms the underlying DataFrame.

     returns

       A new genomic dataset where the DataFrame of genomic data has been replaced, but the metadata (sequence dictionary, and etc) are copied without modification.

     Definition Classes
       GenomicDataset
143.  def transmuteDataset[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](tFn: Function[Dataset[Coverage], Dataset[Y]], convFn: GenomicDatasetConversion[Coverage, Coverage, CoverageDataset, X, Y, Z]): Z

     (Java-specific) Applies a function that transmutes the underlying Dataset into a new Dataset of a different type.

     (Java-specific) Applies a function that transmutes the underlying Dataset into a new Dataset of a different type.

     tFn

       A function that transforms the underlying Dataset.

     returns

       A new genomic dataset where the Dataset of genomic data has been replaced, but the metadata (sequence dictionary, and etc) are copied without modification.

     Definition Classes
       GenomicDataset
144.  def transmuteDataset[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](tFn: (Dataset[Coverage]) ⇒ Dataset[Y])(implicit yTag: scala.reflect.api.JavaUniverse.TypeTag[Y], convFn: (CoverageDataset, Dataset[Y]) ⇒ Z): Z

     (Scala-specific) Applies a function that transmutes the underlying Dataset into a new Dataset of a different type.

     (Scala-specific) Applies a function that transmutes the underlying Dataset into a new Dataset of a different type.

     tFn

       A function that transforms the underlying Dataset.

     returns

       A new genomic dataset where the Dataset of genomic data has been replaced, but the metadata (sequence dictionary, and etc) are copied without modification.

     Definition Classes
       GenomicDataset
145.  val uTag: scala.reflect.api.JavaUniverse.TypeTag[Coverage]
     Definition Classes
       CoverageDataset → GenomicDataset
146.  def union(datasets: CoverageDataset*): CoverageDataset

     (Scala-specific) Unions together multiple genomic datasets.

     (Scala-specific) Unions together multiple genomic datasets.

     datasets

       Genomic datasets to union with this genomic dataset.

     Definition Classes
       CoverageDataset → GenomicDataset
147.  def union(datasets: List[CoverageDataset]): CoverageDataset

     (Java-specific) Unions together multiple genomic datasets.

     (Java-specific) Unions together multiple genomic datasets.

     datasets

       Genomic datasets to union with this genomic dataset.

     Definition Classes
       GenomicDataset
148.  def unpersist(): CoverageDataset

     Unpersists underlying RDD from memory or disk.

     Unpersists underlying RDD from memory or disk.

     returns

       Uncached GenomicDataset.

     Definition Classes
       DatasetBoundGenomicDataset → GenomicDataset
149.  val unproductFn: (Coverage) ⇒ Coverage
     Attributes
       protected
     Definition Classes
       CoverageDataset → GenomicDataset
150.  final def wait(): Unit
     Definition Classes
       AnyRef
     Annotations
       @throws( ... )
151.  final def wait(arg0: Long, arg1: Int): Unit
     Definition Classes
       AnyRef
     Annotations
       @throws( ... )
152.  final def wait(arg0: Long): Unit
     Definition Classes
       AnyRef
     Annotations
       @native() @throws( ... )
153.  def warn(mkr: Marker, msg: ⇒ Any, t: ⇒ Throwable): Unit
     Attributes
       protected
     Definition Classes
       Logging
154.  def warn(msg: ⇒ Any, t: ⇒ Throwable): Unit
     Attributes
       protected
     Definition Classes
       Logging
155.  def warn(msg: ⇒ Any): Unit
     Attributes
       protected
     Definition Classes
       Logging
156.  def writeTextRdd[T](rdd: RDD[T], outputPath: String, asSingleFile: Boolean, disableFastConcat: Boolean, optHeaderPath: Option[String] = None): Unit

     Writes an RDD to disk as text and optionally merges.

     Writes an RDD to disk as text and optionally merges.

     rdd

       RDD to save.

     outputPath

       Output path to save text files to.

     asSingleFile

       If true, combines all partition shards.

     disableFastConcat

       If asSingleFile is true, disables the use of the parallel file merging engine.

     optHeaderPath

       If provided, the header file to include.

     Attributes
       protected
     Definition Classes
       GenomicDataset

### Inherited from Serializable

### Inherited from Product

### Inherited from Equals

### Inherited from DatasetBoundGenomicDataset[Coverage, Coverage, CoverageDataset]

### Inherited from CoverageDataset

### Inherited from MultisampleGenomicDataset[Coverage, Coverage, CoverageDataset]

### Inherited from GenomicDataset[Coverage, Coverage, CoverageDataset]

### Inherited from Logging

### Inherited from AnyRef

### Inherited from Any

### Ungrouped