sealed abstract class FeatureDataset extends AvroGenomicDataset[Feature, Feature, FeatureDataset] with MultisampleGenomicDataset[Feature, Feature, FeatureDataset]

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  1. FeatureDataset
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Abstract Value Members

  1. abstract val dataset: Dataset[Feature]

    These data as a Spark SQL Dataset.

    These data as a Spark SQL Dataset.

    Definition Classes
    GenomicDataset
  2. abstract val optPartitionMap: Option[Array[Option[(ReferenceRegion, ReferenceRegion)]]]
    Attributes
    protected
    Definition Classes
    GenomicDataset
  3. abstract val rdd: RDD[Feature]

    The RDD of genomic data that we are wrapping.

    The RDD of genomic data that we are wrapping.

    Definition Classes
    GenomicDataset
  4. abstract val references: 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
    GenomicDataset
  5. abstract def replaceReferences(newReferences: SequenceDictionary): FeatureDataset

    Replaces the reference sequence dictionary attached to a GenomicDataset.

    Replaces the reference sequence dictionary attached to a GenomicDataset.

    newReferences

    The new reference sequence dictionary to attach.

    returns

    Returns a new GenomicDataset with the reference sequences replaced.

    Definition Classes
    GenomicDataset
  6. abstract 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
    MultisampleGenomicDataset
  7. abstract val samples: Seq[Sample]

    The samples who have data contained in this GenomicDataset.

    The samples who have data contained in this GenomicDataset.

    Definition Classes
    MultisampleGenomicDataset
  8. abstract def toCoverage(): CoverageDataset

    Converts the FeatureDataset to a CoverageDataset.

    Converts the FeatureDataset to a CoverageDataset.

    returns

    Genomic dataset containing Coverage records.

Concrete 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 addReference(referenceToAdd: SequenceRecord): FeatureDataset

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

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

    referenceToAdd

    The reference sequence to add.

    returns

    Returns a new GenomicDataset with this reference sequence appended.

    Definition Classes
    GenomicDataset
  5. def addReferences(referencesToAdd: SequenceDictionary): FeatureDataset

    Appends reference sequence metadata to the current genomic dataset.

    Appends reference sequence metadata to the current genomic dataset.

    referencesToAdd

    The new reference sequences to append.

    returns

    Returns a new GenomicDataset with the reference sequences appended.

    Definition Classes
    GenomicDataset
  6. 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
  7. 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
  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
    FeatureDatasetGenomicDataset
  21. def cache(): FeatureDataset

    Caches underlying RDD in memory.

    Caches underlying RDD in memory.

    returns

    Cached GenomicDataset.

    Definition Classes
    GenomicDataset
  22. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  23. def debug(mkr: Marker, msg: ⇒ Any, t: ⇒ Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  24. def debug(msg: ⇒ Any, t: ⇒ Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  25. def debug(msg: ⇒ Any): Unit
    Attributes
    protected
    Definition Classes
    Logging
  26. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  27. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  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.

  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

    (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
  34. 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
    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.

  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.

  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.

  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.

  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.

  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.

  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.

  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.

  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.

  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.

  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.

  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.

  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.

  48. def filterToProtein(proteinId: String): FeatureDataset

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

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

    proteinId

    Protein to filter by.

    returns

    FeatureDataset filtered by the specified protein.

  49. def filterToProteins(proteinIds: Seq[String]): FeatureDataset

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

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

    proteinIds

    Sequence of proteins to filter by.

    returns

    FeatureDataset filtered by the specified proteins.

  50. def filterToProteins(proteinIds: List[String]): FeatureDataset

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

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

    proteinIds

    List of proteins to filter by.

    returns

    FeatureDataset filtered by the specified proteins.

  51. def filterToReferenceName(referenceName: String): FeatureDataset

    Filter this FeatureDataset by reference name to those that match the specified reference name.

    Filter this FeatureDataset by reference name to those that match the specified reference name.

    referenceName

    Reference name to filter by.

    returns

    FeatureDataset filtered by the specified reference name.

  52. 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.

  53. 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.

  54. 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.

  55. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  56. def flattenRddByRegions(): RDD[(ReferenceRegion, Feature)]
    Attributes
    protected
    Definition Classes
    GenomicDataset
  57. 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
  58. 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
  59. 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
  60. 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
  61. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  62. 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
    FeatureDatasetGenomicDataset
  63. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  64. def info(mkr: Marker, msg: ⇒ Any, t: ⇒ Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  65. def info(msg: ⇒ Any, t: ⇒ Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  66. def info(msg: ⇒ Any): Unit
    Attributes
    protected
    Definition Classes
    Logging
  67. def isDebugEnabled: Boolean
    Attributes
    protected
    Definition Classes
    Logging
  68. def isErrorEnabled: Boolean
    Attributes
    protected
    Definition Classes
    Logging
  69. def isInfoEnabled: Boolean
    Attributes
    protected
    Definition Classes
    Logging
  70. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  71. def isSorted: Boolean
    Definition Classes
    GenomicDataset
  72. def isTraceEnabled: Boolean
    Attributes
    protected
    Definition Classes
    Logging
  73. def isWarnEnabled: Boolean
    Attributes
    protected
    Definition Classes
    Logging
  74. 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
  75. 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
  76. 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
  77. 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
  78. 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
  79. 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
  80. 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
  81. 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
  82. 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
  83. def logger: Logger
    Attributes
    protected
    Definition Classes
    Logging
  84. def loggerName: String
    Attributes
    protected
    Definition Classes
    Logging
  85. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  86. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  87. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  88. 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
    GenomicDataset
  89. 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
  90. 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
  91. 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
  92. val productFn: (Feature) ⇒ Feature
    Attributes
    protected
    Definition Classes
    FeatureDatasetGenomicDataset
  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
    FeatureDatasetGenomicDataset
  94. 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

  95. 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

  96. 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
  97. 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
  98. 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

  99. 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

  100. 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

  101. 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

  102. 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

  103. 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

  104. 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
  105. 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
  106. 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
  107. 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
  108. 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
  109. 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
  110. 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
  111. 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
  112. 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.

  113. 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.

  114. 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.

  115. 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.

  116. 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.

  117. 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.

  118. 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
  119. def saveAsParquet(pathName: String, blockSize: Integer, pageSize: Integer, compressionCodec: 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.

    compressionCodec

    The compression codec to apply to pages.

    disableDictionaryEncoding

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

    Definition Classes
    AvroGenomicDataset
  120. def saveAsParquet(pathName: String, blockSize: Int = 128 * 1024 * 1024, pageSize: Int = 1 * 1024 * 1024, compressionCodec: 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.

    pathName

    Path to save the file at.

    blockSize

    Size per block.

    pageSize

    Size per page.

    compressionCodec

    Name of the compression codec to use.

    disableDictionaryEncoding

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

    Definition Classes
    AvroGenomicDatasetGenomicDataset
  121. 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
  122. def saveAsPartitionedParquet(pathName: String, compressionCodec: CompressionCodecName = CompressionCodecName.GZIP, partitionSize: Int = 1000000): Unit

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

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

    pathName

    The path to save the partitioned Parquet file to.

    compressionCodec

    Name of the compression codec to use.

    partitionSize

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

    Definition Classes
    GenomicDataset
  123. 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.

  124. 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
  125. 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
    FeatureDatasetAvroGenomicDatasetGenomicDataset
  126. 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
  127. def saveRddAsParquet(pathName: String, blockSize: Int = 128 * 1024 * 1024, pageSize: Int = 1 * 1024 * 1024, compressionCodec: 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.

    compressionCodec

    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
  128. def saveRddAsParquet(args: SaveArgs): Unit
    Attributes
    protected
    Definition Classes
    AvroGenomicDataset
  129. def saveReferences(pathName: String): Unit

    Save the reference sequence dictionary to disk.

    Save the reference sequence dictionary to disk.

    pathName

    The path to save the reference sequence dictionary to.

    Attributes
    protected
    Definition Classes
    GenomicDataset
  130. 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
  131. 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
  132. 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
  133. 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
  134. 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
  135. 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
  136. 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
  137. 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
  138. 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
  139. 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

  140. 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

  141. 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.

  142. 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

  143. 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

  144. lazy val spark: SparkSession
    Definition Classes
    GenomicDataset
    Annotations
    @transient()
  145. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  146. def toDF(): DataFrame

    returns

    These data as a Spark SQL DataFrame.

    Definition Classes
    GenomicDataset
  147. def toString(): String
    Definition Classes
    MultisampleGenomicDatasetGenomicDataset → AnyRef → Any
  148. def trace(mkr: Marker, msg: ⇒ Any, t: ⇒ Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  149. def trace(msg: ⇒ Any, t: ⇒ Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  150. def trace(msg: ⇒ Any): Unit
    Attributes
    protected
    Definition Classes
    Logging
  151. 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
  152. 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
  153. 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
  154. 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
  155. 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
    FeatureDatasetGenomicDataset
  156. 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
    FeatureDatasetGenomicDataset
  157. 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
  158. 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
  159. 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
  160. 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
  161. 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
  162. 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
  163. val uTag: scala.reflect.api.JavaUniverse.TypeTag[Feature]
    Definition Classes
    FeatureDatasetGenomicDataset
  164. 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
    FeatureDatasetGenomicDataset
  165. 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
  166. def unpersist(): FeatureDataset

    Unpersists underlying RDD from memory or disk.

    Unpersists underlying RDD from memory or disk.

    returns

    Uncached GenomicDataset.

    Definition Classes
    GenomicDataset
  167. val unproductFn: (Feature) ⇒ Feature
    Attributes
    protected
    Definition Classes
    FeatureDatasetGenomicDataset
  168. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  169. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  170. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  171. def warn(mkr: Marker, msg: ⇒ Any, t: ⇒ Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  172. def warn(msg: ⇒ Any, t: ⇒ Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  173. def warn(msg: ⇒ Any): Unit
    Attributes
    protected
    Definition Classes
    Logging
  174. 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
    AvroGenomicDatasetGenomicDataset
  175. 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 AvroGenomicDataset[Feature, Feature, FeatureDataset]

Inherited from GenomicDataset[Feature, Feature, FeatureDataset]

Inherited from Logging

Inherited from AnyRef

Inherited from Any

Ungrouped