ADAM_2.12: Core 0.27.0 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

# DatasetBoundFeatureDataset 

###

#### case class DatasetBoundFeatureDataset extends FeatureDataset with DatasetBoundGenomicDataset[Feature, Feature, FeatureDataset] with Product with Serializable

Linear Supertypes
Serializable, Serializable, Product, Equals, DatasetBoundGenomicDataset[Feature, Feature, FeatureDataset], FeatureDataset, MultisampleGenomicDataset[Feature, Feature, FeatureDataset], AvroGenomicDataset[Feature, Feature, FeatureDataset], GenomicDataset[Feature, Feature, FeatureDataset], Logging, AnyRef, Any
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Inherited

1. DatasetBoundFeatureDataset
2. Serializable
3. Serializable
4. Product
5. Equals
6. DatasetBoundGenomicDataset
7. FeatureDataset
8. MultisampleGenomicDataset
9. AvroGenomicDataset
10. GenomicDataset
11. Logging
12. AnyRef
13. Any

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Visibility

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### 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): FeatureDataset

   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]): FeatureDataset

   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): FeatureDataset

   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): FeatureDataset

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

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

12.  def broadcastRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Feature, X), (Feature, 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
13.  def broadcastRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Feature, X), (Feature, 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
14.  def broadcastRegionJoinAgainst[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](broadcast: GenomicBroadcast[X, Y, Z])(implicit tTag: ClassTag[Feature], xTag: ClassTag[X], uyTag: scala.reflect.api.JavaUniverse.TypeTag[(Y, Feature)]): GenericGenomicDataset[(X, Feature), (Y, Feature)]

    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

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

    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

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

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

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

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

20.  def buildTree(rdd: RDD[(ReferenceRegion, Feature)])(implicit tTag: ClassTag[Feature]): IntervalArray[ReferenceRegion, Feature]
    Attributes
      protected
    Definition Classes
      FeatureDataset → GenomicDataset
21.  def cache(): FeatureDataset

    Caches underlying RDD in memory.

    Caches underlying RDD in memory.

    returns

      Cached GenomicDataset.

    Definition Classes
      DatasetBoundGenomicDataset → GenomicDataset
22.  def clone(): AnyRef
    Attributes
      protected[java.lang]
    Definition Classes
      AnyRef
    Annotations
      @native() @throws( ... )
23.  val dataset: Dataset[Feature]

    These data as a Spark SQL Dataset.

    These data as a Spark SQL Dataset.

    Definition Classes
      DatasetBoundFeatureDataset → GenomicDataset
24.  def debug(mkr: Marker, msg: ⇒ Any, t: ⇒ Throwable): Unit
    Attributes
      protected
    Definition Classes
      Logging
25.  def debug(msg: ⇒ Any, t: ⇒ Throwable): Unit
    Attributes
      protected
    Definition Classes
      Logging
26.  def debug(msg: ⇒ Any): Unit
    Attributes
      protected
    Definition Classes
      Logging
27.  final def eq(arg0: AnyRef): Boolean
    Definition Classes
      AnyRef
28.  def error(mkr: Marker, msg: ⇒ Any, t: ⇒ Throwable): Unit
    Attributes
      protected
    Definition Classes
      Logging
29.  def error(msg: ⇒ Any, t: ⇒ Throwable): Unit
    Attributes
      protected
    Definition Classes
      Logging
30.  def error(msg: ⇒ Any): Unit
    Attributes
      protected
    Definition Classes
      Logging
31.  def filterByAttribute(key: String, value: String): FeatureDataset

    Filter this FeatureDataset by attribute to those that match the specified attribute key and value.

    Filter this FeatureDataset by attribute to those that match the specified attribute key and value.

    key

      Attribute key to filter by.

    value

      Attribute value to filter by.

    returns

      FeatureDataset filtered by the specified attribute.

    Definition Classes
      DatasetBoundFeatureDataset → FeatureDataset
32.  def filterByOverlappingRegion(query: ReferenceRegion): FeatureDataset

    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
33.  def filterByOverlappingRegions(querys: Iterable[ReferenceRegion]): FeatureDataset

    (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
34.  def filterByOverlappingRegions(querys: Iterable[ReferenceRegion]): FeatureDataset

    (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
35.  def filterByScore(minimumScore: Double): FeatureDataset

    Filter this FeatureDataset by score.

    Filter this FeatureDataset by score.

    minimumScore

      Minimum score to filter by, inclusive.

    returns

      FeatureDataset filtered by the specified minimum score.

    Definition Classes
      DatasetBoundFeatureDataset → FeatureDataset
36.  def filterToExon(exonId: String): FeatureDataset

    Filter this FeatureDataset by exon to those that match the specified exon.

    Filter this FeatureDataset by exon to those that match the specified exon.

    exonId

      Exon to filter by.

    returns

      FeatureDataset filtered by the specified exon.

    Definition Classes
      DatasetBoundFeatureDataset → FeatureDataset
37.  def filterToExons(exonIds: Seq[String]): FeatureDataset

    (Scala-specific) Filter this FeatureDataset by exon to those that match the specified exons.

    (Scala-specific) Filter this FeatureDataset by exon to those that match the specified exons.

    exonIds

      Sequence of exons to filter by.

    returns

      FeatureDataset filtered by the specified exons.

    Definition Classes
      DatasetBoundFeatureDataset → FeatureDataset
38.  def filterToExons(exonIds: List[String]): FeatureDataset

    (Java-specific) Filter this FeatureDataset by exon to those that match the specified exons.

    (Java-specific) Filter this FeatureDataset by exon to those that match the specified exons.

    exonIds

      List of exons to filter by.

    returns

      FeatureDataset filtered by the specified exons.

    Definition Classes
      FeatureDataset
39.  def filterToFeatureType(featureType: String): FeatureDataset

    Filter this FeatureDataset by feature type to those that match the specified feature type.

    Filter this FeatureDataset by feature type to those that match the specified feature type.

    featureType

      Feature type to filter by.

    returns

      FeatureDataset filtered by the specified feature type.

    Definition Classes
      DatasetBoundFeatureDataset → FeatureDataset
40.  def filterToFeatureTypes(featureTypes: Seq[String]): FeatureDataset

    (Scala-specific) Filter this FeatureDataset by feature type to those that match the specified feature types.

    (Scala-specific) Filter this FeatureDataset by feature type to those that match the specified feature types.

    returns

      FeatureDataset filtered by the specified feature types.

    Definition Classes
      DatasetBoundFeatureDataset → FeatureDataset
41.  def filterToFeatureTypes(featureTypes: List[String]): FeatureDataset

    (Java-specific) Filter this FeatureDataset by feature type to those that match the specified feature types.

    (Java-specific) Filter this FeatureDataset by feature type to those that match the specified feature types.

    returns

      FeatureDataset filtered by the specified feature types.

    Definition Classes
      FeatureDataset
42.  def filterToGene(geneId: String): FeatureDataset

    Filter this FeatureDataset by gene to those that match the specified gene.

    Filter this FeatureDataset by gene to those that match the specified gene.

    geneId

      Gene to filter by.

    returns

      FeatureDataset filtered by the specified gene.

    Definition Classes
      DatasetBoundFeatureDataset → FeatureDataset
43.  def filterToGenes(geneIds: Seq[String]): FeatureDataset

    (Scala-specific) Filter this FeatureDataset by gene to those that match the specified genes.

    (Scala-specific) Filter this FeatureDataset by gene to those that match the specified genes.

    geneIds

      Sequence of genes to filter by.

    returns

      FeatureDataset filtered by the specified genes.

    Definition Classes
      DatasetBoundFeatureDataset → FeatureDataset
44.  def filterToGenes(geneIds: List[String]): FeatureDataset

    (Java-specific) Filter this FeatureDataset by gene to those that match the specified genes.

    (Java-specific) Filter this FeatureDataset by gene to those that match the specified genes.

    geneIds

      List of genes to filter by.

    returns

      FeatureDataset filtered by the specified genes.

    Definition Classes
      FeatureDataset
45.  def filterToParent(parentId: String): FeatureDataset

    Filter this FeatureDataset by parent to those that match the specified parent.

    Filter this FeatureDataset by parent to those that match the specified parent.

    parentId

      Parent to filter by.

    returns

      FeatureDataset filtered by the specified parent.

    Definition Classes
      DatasetBoundFeatureDataset → FeatureDataset
46.  def filterToParents(parentIds: Seq[String]): FeatureDataset

    (Scala-specific) Filter this FeatureDataset by parent to those that match the specified parents.

    (Scala-specific) Filter this FeatureDataset by parent to those that match the specified parents.

    parentIds

      Sequence of parents to filter by.

    returns

      FeatureDataset filtered by the specified parents.

    Definition Classes
      DatasetBoundFeatureDataset → FeatureDataset
47.  def filterToParents(parentIds: List[String]): FeatureDataset

    (Java-specific) Filter this FeatureDataset by parent to those that match the specified parents.

    (Java-specific) Filter this FeatureDataset by parent to those that match the specified parents.

    parentIds

      List of parents to filter by.

    returns

      FeatureDataset filtered by the specified parents.

    Definition Classes
      FeatureDataset
48.  def filterToTranscript(transcriptId: String): FeatureDataset

    Filter this FeatureDataset by transcript to those that match the specified transcript.

    Filter this FeatureDataset by transcript to those that match the specified transcript.

    transcriptId

      Transcript to filter by.

    returns

      FeatureDataset filtered by the specified transcript.

    Definition Classes
      DatasetBoundFeatureDataset → FeatureDataset
49.  def filterToTranscripts(transcriptIds: Seq[String]): FeatureDataset

    (Scala-specific) Filter this FeatureDataset by transcript to those that match the specified transcripts.

    (Scala-specific) Filter this FeatureDataset by transcript to those that match the specified transcripts.

    transcriptIds

      Sequence of transcripts to filter by.

    returns

      FeatureDataset filtered by the specified transcripts.

    Definition Classes
      DatasetBoundFeatureDataset → FeatureDataset
50.  def filterToTranscripts(transcriptIds: List[String]): FeatureDataset

    (Java-specific) Filter this FeatureDataset by transcript to those that match the specified transcripts.

    (Java-specific) Filter this FeatureDataset by transcript to those that match the specified transcripts.

    transcriptIds

      List of transcripts to filter by.

    returns

      FeatureDataset filtered by the specified transcripts.

    Definition Classes
      FeatureDataset
51.  def finalize(): Unit
    Attributes
      protected[java.lang]
    Definition Classes
      AnyRef
    Annotations
      @throws( classOf[java.lang.Throwable] )
52.  def flattenRddByRegions(): RDD[(ReferenceRegion, Feature)]
    Attributes
      protected
    Definition Classes
      GenomicDataset
53.  def fullOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[Feature], xTag: ClassTag[X], otoxTag: ClassTag[(Option[Feature], Option[X])], ouoyTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[Feature], Option[Y])]): GenericGenomicDataset[(Option[Feature], Option[X]), (Option[Feature], 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
54.  def fullOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[Feature], xTag: ClassTag[X], otoxTag: ClassTag[(Option[Feature], Option[X])], ouoyTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[Feature], Option[Y])]): GenericGenomicDataset[(Option[Feature], Option[X]), (Option[Feature], 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
55.  def fullOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Option[Feature], Option[X]), (Option[Feature], 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
56.  def fullOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Option[Feature], Option[X]), (Option[Feature], 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
57.  final def getClass(): Class[_]
    Definition Classes
      AnyRef → Any
    Annotations
      @native()
58.  def getReferenceRegions(elem: Feature): Seq[ReferenceRegion]

    elem

      The Feature to get an underlying region for.

    returns

      Since a feature maps directly to a single genomic region, this method will always return a Seq of exactly one ReferenceRegion.

    Attributes
      protected
    Definition Classes
      FeatureDataset → GenomicDataset
59.  def info(mkr: Marker, msg: ⇒ Any, t: ⇒ Throwable): Unit
    Attributes
      protected
    Definition Classes
      Logging
60.  def info(msg: ⇒ Any, t: ⇒ Throwable): Unit
    Attributes
      protected
    Definition Classes
      Logging
61.  def info(msg: ⇒ Any): Unit
    Attributes
      protected
    Definition Classes
      Logging
62.  def isDebugEnabled: Boolean
    Attributes
      protected
    Definition Classes
      Logging
63.  def isErrorEnabled: Boolean
    Attributes
      protected
    Definition Classes
      Logging
64.  def isInfoEnabled: Boolean
    Attributes
      protected
    Definition Classes
      Logging
65.  final def isInstanceOf[T0]: Boolean
    Definition Classes
      Any
66.  val isPartitioned: Boolean
    Definition Classes
      DatasetBoundFeatureDataset → DatasetBoundGenomicDataset
67.  def isSorted: Boolean
    Definition Classes
      GenomicDataset
68.  def isTraceEnabled: Boolean
    Attributes
      protected
    Definition Classes
      Logging
69.  def isWarnEnabled: Boolean
    Attributes
      protected
    Definition Classes
      Logging
70.  lazy val jrdd: JavaRDD[Feature]

    The underlying RDD of genomic data, as a JavaRDD.

    The underlying RDD of genomic data, as a JavaRDD.

    Definition Classes
      GenomicDataset
71.  def leftOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[Feature], xTag: ClassTag[X], toxTag: ClassTag[(Feature, Option[X])], uoyTag: scala.reflect.api.JavaUniverse.TypeTag[(Feature, Option[Y])]): GenericGenomicDataset[(Feature, Option[X]), (Feature, 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
72.  def leftOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[Feature], xTag: ClassTag[X], toxTag: ClassTag[(Feature, Option[X])], uoyTag: scala.reflect.api.JavaUniverse.TypeTag[(Feature, Option[Y])]): GenericGenomicDataset[(Feature, Option[X]), (Feature, 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
73.  def leftOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Feature, Option[X]), (Feature, 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
74.  def leftOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Feature, Option[X]), (Feature, 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
75.  def leftOuterShuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[Feature], xTag: ClassTag[X], toxTag: ClassTag[(Feature, Iterable[X])], uiyTag: scala.reflect.api.JavaUniverse.TypeTag[(Feature, Seq[Y])]): GenericGenomicDataset[(Feature, Iterable[X]), (Feature, 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
76.  def leftOuterShuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[Feature], xTag: ClassTag[X], toxTag: ClassTag[(Feature, Iterable[X])], uiyTag: scala.reflect.api.JavaUniverse.TypeTag[(Feature, Seq[Y])]): GenericGenomicDataset[(Feature, Iterable[X]), (Feature, 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
77.  def leftOuterShuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Feature, Iterable[X]), (Feature, 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
78.  def leftOuterShuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Feature, Iterable[X]), (Feature, 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
79.  def logger: Logger
    Attributes
      protected
    Definition Classes
      Logging
80.  def loggerName: String
    Attributes
      protected
    Definition Classes
      Logging
81.  final def ne(arg0: AnyRef): Boolean
    Definition Classes
      AnyRef
82.  final def notify(): Unit
    Definition Classes
      AnyRef
    Annotations
      @native()
83.  final def notifyAll(): Unit
    Definition Classes
      AnyRef
    Annotations
      @native()
84.  val optLookbackPartitions: Option[Int]
    Definition Classes
      DatasetBoundFeatureDataset → DatasetBoundGenomicDataset
85.  val optPartitionBinSize: Option[Int]
    Definition Classes
      DatasetBoundFeatureDataset → DatasetBoundGenomicDataset
86.  lazy val optPartitionMap: None.type
    Attributes
      protected
    Definition Classes
      DatasetBoundFeatureDataset → GenomicDataset
87.  def persist(sl: StorageLevel): FeatureDataset

    Persists underlying RDD in memory or disk.

    Persists underlying RDD in memory or disk.

    sl

      new StorageLevel

    returns

      Persisted GenomicDataset.

    Definition Classes
      DatasetBoundGenomicDataset → GenomicDataset
88.  def pipe[X, Y <: Product, Z <: GenomicDataset[X, Y, Z], W <: InFormatter[Feature, Feature, FeatureDataset, W]](cmd: List[String], files: List[String], environment: Map[String, String], flankSize: Integer, tFormatter: Class[W], xFormatter: OutFormatter[X], convFn: Function2[FeatureDataset, 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
89.  def pipe[X, Y <: Product, Z <: GenomicDataset[X, Y, Z], W <: InFormatter[Feature, Feature, FeatureDataset, W]](cmd: Seq[Any], files: Seq[Any], environment: Map[Any, Any], flankSize: Double, tFormatter: Class[W], xFormatter: OutFormatter[X], convFn: Function2[FeatureDataset, 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
90.  def pipe[X, Y <: Product, Z <: GenomicDataset[X, Y, Z], W <: InFormatter[Feature, Feature, FeatureDataset, 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[Feature, Feature, FeatureDataset, W], xFormatter: OutFormatter[X], convFn: (FeatureDataset, RDD[X]) ⇒ Z, tManifest: ClassTag[Feature], 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
91.  val productFn: (Feature) ⇒ Feature
    Attributes
      protected
    Definition Classes
      FeatureDataset → GenomicDataset
92.  lazy val rdd: RDD[Feature]

    The RDD of genomic data that we are wrapping.

    The RDD of genomic data that we are wrapping.

    Definition Classes
      DatasetBoundFeatureDataset → GenomicDataset
93.  def replaceRdd(newRdd: RDD[Feature], newPartitionMap: Option[Array[Option[(ReferenceRegion, ReferenceRegion)]]] = None): FeatureDataset

    newRdd

      The RDD to replace the underlying RDD with.

    returns

      Returns a new FeatureDataset with the underlying RDD replaced.

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

    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
      DatasetBoundFeatureDataset → MultisampleGenomicDataset
95.  def replaceSequences(newSequences: SequenceDictionary): FeatureDataset

    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
      DatasetBoundFeatureDataset → GenomicDataset
96.  def rightOuterBroadcastRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[Feature], xTag: ClassTag[X], otxTag: ClassTag[(Option[Feature], X)], ouyTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[Feature], Y)]): GenericGenomicDataset[(Option[Feature], X), (Option[Feature], 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

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

98.  def rightOuterBroadcastRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Option[Feature], X), (Option[Feature], 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
99.  def rightOuterBroadcastRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Option[Feature], X), (Option[Feature], 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
100.  def rightOuterBroadcastRegionJoinAgainst[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](broadcast: GenomicBroadcast[X, Y, Z])(implicit tTag: ClassTag[Feature], xTag: ClassTag[X], oyuTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[Y], Feature)]): GenericGenomicDataset[(Option[X], Feature), (Option[Y], Feature)]

     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

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

     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

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

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

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

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

106.  def rightOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[Feature], xTag: ClassTag[X], otxTag: ClassTag[(Option[Feature], X)], ouyTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[Feature], Y)]): GenericGenomicDataset[(Option[Feature], X), (Option[Feature], 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
107.  def rightOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[Feature], xTag: ClassTag[X], otxTag: ClassTag[(Option[Feature], X)], ouyTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[Feature], Y)]): GenericGenomicDataset[(Option[Feature], X), (Option[Feature], 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
108.  def rightOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Option[Feature], X), (Option[Feature], 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
109.  def rightOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Option[Feature], X), (Option[Feature], 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
110.  def rightOuterShuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[Feature], xTag: ClassTag[X], otixTag: ClassTag[(Option[Feature], Iterable[X])], otsyTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[Feature], Seq[Y])]): GenericGenomicDataset[(Option[Feature], Iterable[X]), (Option[Feature], 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
111.  def rightOuterShuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[Feature], xTag: ClassTag[X], otixTag: ClassTag[(Option[Feature], Iterable[X])], ousyTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[Feature], Seq[Y])]): GenericGenomicDataset[(Option[Feature], Iterable[X]), (Option[Feature], 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
112.  def rightOuterShuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Option[Feature], Iterable[X]), (Option[Feature], 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
113.  def rightOuterShuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Option[Feature], Iterable[X]), (Option[Feature], 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
114.  val samples: Seq[Sample]

     The samples who have data contained in this GenomicDataset.

     The samples who have data contained in this GenomicDataset.

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

     Java friendly save function.

     Java friendly save function. Automatically detects the output format.

     Writes files ending in .bed as BED6/12, .gff3 as GFF3, .gtf/.gff as GTF/GFF2, .narrow[pP]eak as NarrowPeak, and .interval_list as IntervalList. If none of these match, we fall back to Parquet. These files are written as sharded text files.

     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
       FeatureDataset
116.  def saveAsBed(fileName: String, asSingleFile: Boolean = false, disableFastConcat: Boolean = false): Unit

     Save this FeatureDataset in bedtools2 BED format, where score is formatted as double floating point values with missing values.

     Save this FeatureDataset in bedtools2 BED format, where score is formatted as double floating point values with missing values.

     fileName

       The path to save BED formatted text file(s) to.

     asSingleFile

       By default (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 parallel file merging engine.

     Definition Classes
       FeatureDataset
117.  def saveAsGff3(fileName: String, asSingleFile: Boolean = false, disableFastConcat: Boolean = false): Unit

     Save this FeatureDataset in GFF3 format.

     Save this FeatureDataset in GFF3 format.

     fileName

       The path to save GFF3 formatted text file(s) to.

     asSingleFile

       By default (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 parallel file merging engine.

     Definition Classes
       FeatureDataset
118.  def saveAsGtf(fileName: String, asSingleFile: Boolean = false, disableFastConcat: Boolean = false): Unit

     Save this FeatureDataset in GTF format.

     Save this FeatureDataset in GTF format.

     fileName

       The path to save GTF formatted text file(s) to.

     asSingleFile

       By default (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 parallel file merging engine.

     Definition Classes
       FeatureDataset
119.  def saveAsIntervalList(fileName: String, asSingleFile: Boolean = false, disableFastConcat: Boolean = false): Unit

     Save this FeatureDataset in interval list format.

     Save this FeatureDataset in interval list format.

     fileName

       The path to save interval list formatted text file(s) to.

     asSingleFile

       By default (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 parallel file merging engine.

     Definition Classes
       FeatureDataset
120.  def saveAsNarrowPeak(fileName: String, asSingleFile: Boolean = false, disableFastConcat: Boolean = false): Unit

     Save this FeatureDataset in NarrowPeak format.

     Save this FeatureDataset in NarrowPeak format.

     fileName

       The path to save NarrowPeak formatted text file(s) to.

     asSingleFile

       By default (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 parallel file merging engine.

     Definition Classes
       FeatureDataset
121.  def saveAsParquet(filePath: String, blockSize: Int = 128 * 1024 * 1024, pageSize: Int = 1 * 1024 * 1024, compressCodec: CompressionCodecName = CompressionCodecName.GZIP, disableDictionaryEncoding: Boolean = false): Unit

     Saves this genomic dataset to disk as a Parquet file.

     Saves this genomic dataset to disk as a Parquet file.

     blockSize

       Size per block.

     pageSize

       Size per page.

     compressCodec

       Name of the compression codec to use.

     disableDictionaryEncoding

       Whether or not to disable bit-packing. Default is false.

     Definition Classes
       DatasetBoundFeatureDataset → AvroGenomicDataset → GenomicDataset
122.  def saveAsParquet(pathName: String): Unit

     Saves this genomic dataset to disk as a Parquet file.

     Saves this genomic dataset to disk as a Parquet file.

     pathName

       Path to save the file at.

     Definition Classes
       AvroGenomicDataset
123.  def saveAsParquet(pathName: String, blockSize: Integer, pageSize: Integer, compressCodec: CompressionCodecName, disableDictionaryEncoding: Boolean): Unit

     (Java-specific) Saves this genomic dataset to disk as a Parquet file.

     (Java-specific) Saves this genomic dataset to disk as a Parquet file.

     pathName

       Path to save the file at.

     blockSize

       The size in bytes of blocks to write.

     pageSize

       The size in bytes of pages to write.

     compressCodec

       The compression codec to apply to pages.

     disableDictionaryEncoding

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

     Definition Classes
       AvroGenomicDataset
124.  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
125.  def saveAsPartitionedParquet(pathName: String, compressCodec: 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.

     compressCodec

       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
126.  def saveAsUcscBed(fileName: String, asSingleFile: Boolean = false, disableFastConcat: Boolean = false, minimumScore: Double, maximumScore: Double, missingValue: Int = 0): Unit

     Save this FeatureDataset in UCSC BED format, where score is formatted as integer values between 0 and 1000, with missing value as specified.

     Save this FeatureDataset in UCSC BED format, where score is formatted as integer values between 0 and 1000, with missing value as specified.

     fileName

       The path to save BED formatted text file(s) to.

     asSingleFile

       By default (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 parallel file merging engine.

     minimumScore

       Minimum score, interpolated to 0.

     maximumScore

       Maximum score, interpolated to 1000.

     missingValue

       Value to use if score is not specified. Defaults to 0.

     Definition Classes
       FeatureDataset
127.  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
128.  def saveMetadata(pathName: String): Unit

     Saves metadata for a FeatureDataset, including partition map, sequences, and samples.

     Saves metadata for a FeatureDataset, including partition map, sequences, and samples.

     pathName

       The path name to save meta data for this FeatureDataset.

     Attributes
       protected
     Definition Classes
       FeatureDataset → AvroGenomicDataset → GenomicDataset
129.  def savePartitionMap(pathName: String): Unit

     Save the partition map to disk.

     Save the partition map to disk. This is done by adding the partition map to the schema.

     pathName

       The filepath where we will save the partition map.

     Attributes
       protected
     Definition Classes
       AvroGenomicDataset
130.  def saveRddAsParquet(pathName: String, blockSize: Int = 128 * 1024 * 1024, pageSize: Int = 1 * 1024 * 1024, compressCodec: CompressionCodecName = CompressionCodecName.GZIP, disableDictionaryEncoding: Boolean = false, optSchema: Option[Schema] = None): Unit

     Saves a genomic dataset of Avro data to Parquet.

     Saves a genomic dataset of Avro data to Parquet.

     pathName

       The path to save the file to.

     blockSize

       The size in bytes of blocks to write. Defaults to 128 * 1024 * 1024.

     pageSize

       The size in bytes of pages to write. Defaults to 1 * 1024 * 1024.

     compressCodec

       The compression codec to apply to pages. Defaults to CompressionCodecName.GZIP.

     disableDictionaryEncoding

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

     optSchema

       The optional schema to set. Defaults to None.

     Attributes
       protected
     Definition Classes
       AvroGenomicDataset
131.  def saveRddAsParquet(args: SaveArgs): Unit
     Attributes
       protected
     Definition Classes
       AvroGenomicDataset
132.  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
133.  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
134.  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
       DatasetBoundFeatureDataset → GenomicDataset
135.  def shuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[Feature], xTag: ClassTag[X], txTag: ClassTag[(Feature, X)], uyTag: scala.reflect.api.JavaUniverse.TypeTag[(Feature, Y)]): GenericGenomicDataset[(Feature, X), (Feature, 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
136.  def shuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[Feature], xTag: ClassTag[X], txTag: ClassTag[(Feature, X)], uyTag: scala.reflect.api.JavaUniverse.TypeTag[(Feature, Y)]): GenericGenomicDataset[(Feature, X), (Feature, 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
137.  def shuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Feature, X), (Feature, 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
138.  def shuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Feature, X), (Feature, 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
139.  def shuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[Feature], xTag: ClassTag[X], tixTag: ClassTag[(Feature, Iterable[X])], uiyTag: scala.reflect.api.JavaUniverse.TypeTag[(Feature, Seq[Y])]): GenericGenomicDataset[(Feature, Iterable[X]), (Feature, 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
140.  def shuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[Feature], xTag: ClassTag[X], tixTag: ClassTag[(Feature, Iterable[X])], uiyTag: scala.reflect.api.JavaUniverse.TypeTag[(Feature, Seq[Y])]): GenericGenomicDataset[(Feature, Iterable[X]), (Feature, 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
141.  def shuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Feature, Iterable[X]), (Feature, 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
142.  def shuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Feature, Iterable[X]), (Feature, 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
143.  def sort(partitions: Int = rdd.partitions.length, stringency: ValidationStringency = ValidationStringency.STRICT)(implicit tTag: ClassTag[Feature]): FeatureDataset

     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

144.  def sort(): FeatureDataset

     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

145.  def sortByReference(ascending: Boolean = true, numPartitions: Int = rdd.partitions.length): FeatureDataset

     Sorts the RDD by the reference ordering.

     Sorts the RDD by the reference ordering.

     ascending

       Whether to sort in ascending order or not.

     numPartitions

       The number of partitions to have after sorting. Defaults to the partition count of the underlying RDD.

     Definition Classes
       FeatureDataset
146.  def sortLexicographically(partitions: Int = rdd.partitions.length, storePartitionMap: Boolean = false, storageLevel: StorageLevel = StorageLevel.MEMORY_ONLY, stringency: ValidationStringency = ValidationStringency.STRICT)(implicit tTag: ClassTag[Feature]): FeatureDataset

     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

147.  def sortLexicographically(): FeatureDataset

     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

148.  final def synchronized[T0](arg0: ⇒ T0): T0
     Definition Classes
       AnyRef
149.  def toCoverage(): CoverageDataset

     Converts the FeatureDataset to a CoverageDataset.

     Converts the FeatureDataset to a CoverageDataset.

     returns

       Genomic dataset containing Coverage records.

     Definition Classes
       DatasetBoundFeatureDataset → FeatureDataset
150.  def toDF(): DataFrame

     returns

       These data as a Spark SQL DataFrame.

     Definition Classes
       GenomicDataset
151.  def toString(): String
     Definition Classes
       MultisampleGenomicDataset → GenomicDataset → AnyRef → Any
152.  def trace(mkr: Marker, msg: ⇒ Any, t: ⇒ Throwable): Unit
     Attributes
       protected
     Definition Classes
       Logging
153.  def trace(msg: ⇒ Any, t: ⇒ Throwable): Unit
     Attributes
       protected
     Definition Classes
       Logging
154.  def trace(msg: ⇒ Any): Unit
     Attributes
       protected
     Definition Classes
       Logging
155.  def transform(tFn: Function[JavaRDD[Feature], JavaRDD[Feature]]): FeatureDataset

     (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
156.  def transform(tFn: (RDD[Feature]) ⇒ RDD[Feature]): FeatureDataset

     (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
157.  def transformDataFrame(tFn: Function[DataFrame, DataFrame]): FeatureDataset

     (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
158.  def transformDataFrame(tFn: (DataFrame) ⇒ DataFrame)(implicit uTag: scala.reflect.api.JavaUniverse.TypeTag[Feature]): FeatureDataset

     (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
159.  def transformDataset(tFn: Function[Dataset[Feature], Dataset[Feature]]): FeatureDataset

     (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
       DatasetBoundFeatureDataset → FeatureDataset → GenomicDataset
160.  def transformDataset(tFn: (Dataset[Feature]) ⇒ Dataset[Feature]): FeatureDataset

     (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
       DatasetBoundFeatureDataset → FeatureDataset → GenomicDataset
161.  def transmute[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](tFn: Function[JavaRDD[Feature], JavaRDD[X]], convFn: Function2[FeatureDataset, 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
162.  def transmute[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](tFn: (RDD[Feature]) ⇒ RDD[X])(implicit convFn: (FeatureDataset, 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
163.  def transmuteDataFrame[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](tFn: Function[DataFrame, DataFrame], convFn: GenomicDatasetConversion[Feature, Feature, FeatureDataset, 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
164.  def transmuteDataFrame[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](tFn: (DataFrame) ⇒ DataFrame)(implicit yTag: scala.reflect.api.JavaUniverse.TypeTag[Y], convFn: (FeatureDataset, 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
165.  def transmuteDataset[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](tFn: Function[Dataset[Feature], Dataset[Y]], convFn: GenomicDatasetConversion[Feature, Feature, FeatureDataset, 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
166.  def transmuteDataset[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](tFn: (Dataset[Feature]) ⇒ Dataset[Y])(implicit yTag: scala.reflect.api.JavaUniverse.TypeTag[Y], convFn: (FeatureDataset, 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
167.  val uTag: scala.reflect.api.JavaUniverse.TypeTag[Feature]
     Definition Classes
       FeatureDataset → GenomicDataset
168.  def union(datasets: FeatureDataset*): FeatureDataset

     (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
       FeatureDataset → GenomicDataset
169.  def union(datasets: List[FeatureDataset]): FeatureDataset

     (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
170.  def unpersist(): FeatureDataset

     Unpersists underlying RDD from memory or disk.

     Unpersists underlying RDD from memory or disk.

     returns

       Uncached GenomicDataset.

     Definition Classes
       DatasetBoundGenomicDataset → GenomicDataset
171.  val unproductFn: (Feature) ⇒ Feature
     Attributes
       protected
     Definition Classes
       FeatureDataset → GenomicDataset
172.  final def wait(): Unit
     Definition Classes
       AnyRef
     Annotations
       @throws( ... )
173.  final def wait(arg0: Long, arg1: Int): Unit
     Definition Classes
       AnyRef
     Annotations
       @throws( ... )
174.  final def wait(arg0: Long): Unit
     Definition Classes
       AnyRef
     Annotations
       @native() @throws( ... )
175.  def warn(mkr: Marker, msg: ⇒ Any, t: ⇒ Throwable): Unit
     Attributes
       protected
     Definition Classes
       Logging
176.  def warn(msg: ⇒ Any, t: ⇒ Throwable): Unit
     Attributes
       protected
     Definition Classes
       Logging
177.  def warn(msg: ⇒ Any): Unit
     Attributes
       protected
     Definition Classes
       Logging
178.  def writePartitionedParquetFlag(pathName: String, partitionSize: Int): Unit

     Save partition size into the partitioned Parquet flag file.

     Save partition size into the partitioned Parquet flag file.

     pathName

       Path to save the file at.

     partitionSize

       Partition bin size, in base pairs, used in Hive-style partitioning.

     Definition Classes
       AvroGenomicDataset → GenomicDataset
179.  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[Feature, Feature, FeatureDataset]

### Inherited from FeatureDataset

### Inherited from MultisampleGenomicDataset[Feature, Feature, FeatureDataset]

### Inherited from AvroGenomicDataset[Feature, Feature, FeatureDataset]

### Inherited from GenomicDataset[Feature, Feature, FeatureDataset]

### Inherited from Logging

### Inherited from AnyRef

### Inherited from Any

### Ungrouped