org.bdgenomics.adam.rdd

# GenomicDataset

###
Related Doc: package rdd

#### trait GenomicDataset[T, U <: Product, V <: GenomicDataset[T, U, V]] extends Logging

A trait that wraps an RDD or Dataset of genomic data with helpful metadata.

T

  The type of the data in the wrapped RDD or Dataset.

U

  The type of this GenomicDataset.

Linear Supertypes
Logging, AnyRef, Any
Known Subclasses
AlignmentRecordDataset, AvroGenomicDataset, AvroReadGroupGenomicDataset, CoverageDataset, DatasetBoundAlignmentRecordDataset, DatasetBoundCoverageDataset, DatasetBoundFeatureDataset, DatasetBoundFragmentDataset, DatasetBoundGenericGenomicDataset, DatasetBoundGenomicDataset, DatasetBoundGenotypeDataset, DatasetBoundReadDataset, DatasetBoundSequenceDataset, DatasetBoundSliceDataset, DatasetBoundVariantContextDataset, DatasetBoundVariantDataset, FeatureDataset, FragmentDataset, GenericGenomicDataset, GenomicDatasetWithLineage, GenotypeDataset, MultisampleAvroGenomicDataset, MultisampleGenomicDataset, ParquetUnboundAlignmentRecordDataset, ParquetUnboundCoverageDataset, ParquetUnboundFeatureDataset, ParquetUnboundFragmentDataset, ParquetUnboundGenotypeDataset, ParquetUnboundReadDataset, ParquetUnboundSequenceDataset, ParquetUnboundSliceDataset, ParquetUnboundVariantDataset, RDDBoundAlignmentRecordDataset, RDDBoundCoverageDataset, RDDBoundFeatureDataset, RDDBoundFragmentDataset, RDDBoundGenericGenomicDataset, RDDBoundGenotypeDataset, RDDBoundReadDataset, RDDBoundSequenceDataset, RDDBoundSliceDataset, RDDBoundVariantContextDataset, RDDBoundVariantDataset, ReadDataset, SequenceDataset, SliceDataset, VariantContextDataset, VariantDataset
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1. GenomicDataset
2. Logging
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### Abstract Value Members

1. #### abstract def buildTree(rdd: RDD[(ReferenceRegion, T)])(implicit tTag: ClassTag[T]): IntervalArray[ReferenceRegion, T]

   Attributes
     protected

2. #### abstract val dataset: Dataset[U]

   These data as a Spark SQL Dataset.

3. #### abstract def getReferenceRegions(elem: T): Seq[ReferenceRegion]

   Attributes
     protected

4. #### abstract val optPartitionMap: Option[Array[Option[(ReferenceRegion, ReferenceRegion)]]]

   Attributes
     protected

5. #### abstract val productFn: (T) ⇒ U

   Attributes
     protected

6. #### abstract val rdd: RDD[T]

   The RDD of genomic data that we are wrapping.

7. #### abstract def replaceRdd(newRdd: RDD[T], newPartitionMap: Option[Array[Option[(ReferenceRegion, ReferenceRegion)]]] = None): V

   Attributes
     protected

8. #### abstract def replaceSequences(newSequences: SequenceDictionary): V

   Replaces the sequence dictionary attached to a GenomicDataset.

   Replaces the sequence dictionary attached to a GenomicDataset.

   newSequences

     The new sequence dictionary to attach.

   returns

     Returns a new GenomicDataset with the sequences replaced.

9. #### abstract def saveAsParquet(pathName: String, blockSize: Int = 128 * 1024 * 1024, pageSize: Int = 1 * 1024 * 1024, compressCodec: CompressionCodecName = CompressionCodecName.GZIP, disableDictionaryEncoding: Boolean = false): Unit

   Saves a genomic dataset to Parquet.

   Saves a genomic dataset to Parquet.

   pathName

     The path to save the file to.

   blockSize

     The size in bytes of blocks to write.

   pageSize

     The size in bytes of pages to write.

   compressCodec

     The compression codec to apply to pages.

   disableDictionaryEncoding

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

10. #### abstract val sequences: SequenceDictionary

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

11. #### abstract def transformDataset(tFn: Function[Dataset[U], Dataset[U]]): V

    (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.

12. #### abstract def transformDataset(tFn: (Dataset[U]) ⇒ Dataset[U]): V

    (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.

13. #### abstract val uTag: scala.reflect.api.JavaUniverse.TypeTag[U]

14. #### abstract def union(datasets: V*): V

    (Scala-specific) Unions together multiple genomic datasets.

    (Scala-specific) Unions together multiple genomic datasets.

    datasets

      Genomic datasets to union with this genomic dataset.

15. #### abstract val unproductFn: (U) ⇒ T

    Attributes
      protected

### 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 addSequence(sequenceToAdd: SequenceRecord): V

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

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

   sequenceToAdd

     The sequence to add.

   returns

     Returns a new GenomicDataset with this sequence appended.

5. #### def addSequences(sequencesToAdd: SequenceDictionary): V

   Appends sequence metadata to the current genomic dataset.

   Appends sequence metadata to the current genomic dataset.

   sequencesToAdd

     The new sequences to append.

   returns

     Returns a new GenomicDataset with the sequences appended.

6. #### final def asInstanceOf[T0]: T0

   Definition Classes
     Any

7. #### def broadcast()(implicit tTag: ClassTag[T]): GenomicBroadcast[T, U, V]

8. #### def broadcastRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[T], xTag: ClassTag[X], txTag: ClassTag[(T, X)], uyTag: scala.reflect.api.JavaUniverse.TypeTag[(U, Y)]): GenericGenomicDataset[(T, X), (U, 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.

   See also

     broadcastRegionJoinAgainst

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

   See also

     broadcastRegionJoinAgainst

10. #### def broadcastRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(T, X), (U, 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.

11. #### def broadcastRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(T, X), (U, 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.

12. #### def broadcastRegionJoinAgainst[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](broadcast: GenomicBroadcast[X, Y, Z])(implicit tTag: ClassTag[T], xTag: ClassTag[X], uyTag: scala.reflect.api.JavaUniverse.TypeTag[(Y, U)]): GenericGenomicDataset[(X, T), (Y, U)]

    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.

    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

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

    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.

    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

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

    See also

      broadcastRegionJoinAgainstAndGroupByRight

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

    See also

      broadcastRegionJoinAgainstAndGroupByRight

16. #### def broadcastRegionJoinAndGroupByRight[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Iterable[T], X), (Seq[U], 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.

    See also

      broadcastRegionJoinAgainstAndGroupByRight

17. #### def broadcastRegionJoinAndGroupByRight[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Iterable[T], X), (Seq[U], 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.

    See also

      broadcastRegionJoinAgainstAndGroupByRight

18. #### def cache(): V

    Caches underlying RDD in memory.

    Caches underlying RDD in memory.

    returns

      Cached GenomicDataset.

19. #### def clone(): AnyRef

    Attributes
      protected[java.lang]
    Definition Classes
      AnyRef
    Annotations
      @throws( ... )

20. #### def debug(mkr: Marker, msg: ⇒ Any, t: ⇒ Throwable): Unit

    Attributes
      protected
    Definition Classes
      Logging

21. #### def debug(msg: ⇒ Any, t: ⇒ Throwable): Unit

    Attributes
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    Definition Classes
      Logging

22. #### def debug(msg: ⇒ Any): Unit

    Attributes
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    Definition Classes
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23. #### final def eq(arg0: AnyRef): Boolean

    Definition Classes
      AnyRef

24. #### def equals(arg0: Any): Boolean

    Definition Classes
      AnyRef → Any

25. #### def error(mkr: Marker, msg: ⇒ Any, t: ⇒ Throwable): Unit

    Attributes
      protected
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26. #### def error(msg: ⇒ Any, t: ⇒ Throwable): Unit

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27. #### def error(msg: ⇒ Any): Unit

    Attributes
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28. #### def filterByOverlappingRegion(query: ReferenceRegion): V

    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.

29. #### def filterByOverlappingRegions(querys: Iterable[ReferenceRegion]): V

    (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.

30. #### def filterByOverlappingRegions(querys: Iterable[ReferenceRegion]): V

    (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.

31. #### def finalize(): Unit

    Attributes
      protected[java.lang]
    Definition Classes
      AnyRef
    Annotations
      @throws( classOf[java.lang.Throwable] )

32. #### def flattenRddByRegions(): RDD[(ReferenceRegion, T)]

    Attributes
      protected

33. #### def fullOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[T], xTag: ClassTag[X], otoxTag: ClassTag[(Option[T], Option[X])], ouoyTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[U], Option[Y])]): GenericGenomicDataset[(Option[T], Option[X]), (Option[U], 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`.

34. #### def fullOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[T], xTag: ClassTag[X], otoxTag: ClassTag[(Option[T], Option[X])], ouoyTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[U], Option[Y])]): GenericGenomicDataset[(Option[T], Option[X]), (Option[U], 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`.

35. #### def fullOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Option[T], Option[X]), (Option[U], 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`.

36. #### def fullOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Option[T], Option[X]), (Option[U], 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`.

37. #### final def getClass(): Class[_]

    Definition Classes
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38. #### def hashCode(): Int

    Definition Classes
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39. #### def info(mkr: Marker, msg: ⇒ Any, t: ⇒ Throwable): Unit

    Attributes
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40. #### def info(msg: ⇒ Any, t: ⇒ Throwable): Unit

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41. #### def info(msg: ⇒ Any): Unit

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42. #### def isDebugEnabled: Boolean

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43. #### def isErrorEnabled: Boolean

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44. #### def isInfoEnabled: Boolean

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45. #### final def isInstanceOf[T0]: Boolean

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46. #### def isSorted: Boolean

47. #### def isTraceEnabled: Boolean

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48. #### def isWarnEnabled: Boolean

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49. #### lazy val jrdd: JavaRDD[T]

    The underlying RDD of genomic data, as a JavaRDD.

50. #### def leftOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[T], xTag: ClassTag[X], toxTag: ClassTag[(T, Option[X])], uoyTag: scala.reflect.api.JavaUniverse.TypeTag[(U, Option[Y])]): GenericGenomicDataset[(T, Option[X]), (U, 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.

51. #### def leftOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[T], xTag: ClassTag[X], toxTag: ClassTag[(T, Option[X])], uoyTag: scala.reflect.api.JavaUniverse.TypeTag[(U, Option[Y])]): GenericGenomicDataset[(T, Option[X]), (U, 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.

52. #### def leftOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(T, Option[X]), (U, 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.

53. #### def leftOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(T, Option[X]), (U, 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.

54. #### def leftOuterShuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[T], xTag: ClassTag[X], toxTag: ClassTag[(T, Iterable[X])], uiyTag: scala.reflect.api.JavaUniverse.TypeTag[(U, Seq[Y])]): GenericGenomicDataset[(T, Iterable[X]), (U, 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.

55. #### def leftOuterShuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[T], xTag: ClassTag[X], toxTag: ClassTag[(T, Iterable[X])], uiyTag: scala.reflect.api.JavaUniverse.TypeTag[(U, Seq[Y])]): GenericGenomicDataset[(T, Iterable[X]), (U, 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.

56. #### def leftOuterShuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(T, Iterable[X]), (U, 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.

57. #### def leftOuterShuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(T, Iterable[X]), (U, 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.

58. #### def logger: Logger

    Attributes
      protected
    Definition Classes
      Logging

59. #### def loggerName: String

    Attributes
      protected
    Definition Classes
      Logging

60. #### final def ne(arg0: AnyRef): Boolean

    Definition Classes
      AnyRef

61. #### final def notify(): Unit

    Definition Classes
      AnyRef

62. #### final def notifyAll(): Unit

    Definition Classes
      AnyRef

63. #### def persist(sl: StorageLevel): V

    Persists underlying RDD in memory or disk.

    Persists underlying RDD in memory or disk.

    sl

      new StorageLevel

    returns

      Persisted GenomicDataset.

64. #### def pipe[X, Y <: Product, Z <: GenomicDataset[X, Y, Z], W <: InFormatter[T, U, V, W]](cmd: List[String], files: List[String], environment: Map[String, String], flankSize: Integer, tFormatter: Class[W], xFormatter: OutFormatter[X], convFn: Function2[V, 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.

65. #### def pipe[X, Y <: Product, Z <: GenomicDataset[X, Y, Z], W <: InFormatter[T, U, V, W]](cmd: Seq[Any], files: Seq[Any], environment: Map[Any, Any], flankSize: Double, tFormatter: Class[W], xFormatter: OutFormatter[X], convFn: Function2[V, 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.

66. #### def pipe[X, Y <: Product, Z <: GenomicDataset[X, Y, Z], W <: InFormatter[T, U, V, 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[T, U, V, W], xFormatter: OutFormatter[X], convFn: (V, RDD[X]) ⇒ Z, tManifest: ClassTag[T], 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.

67. #### def rightOuterBroadcastRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[T], xTag: ClassTag[X], otxTag: ClassTag[(Option[T], X)], ouyTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[U], Y)]): GenericGenomicDataset[(Option[T], X), (Option[U], 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.

    See also

      rightOuterBroadcastRegionJoin

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

    See also

      rightOuterBroadcastRegionJoin

69. #### def rightOuterBroadcastRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Option[T], X), (Option[U], 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.

70. #### def rightOuterBroadcastRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Option[T], X), (Option[U], 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.

71. #### def rightOuterBroadcastRegionJoinAgainst[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](broadcast: GenomicBroadcast[X, Y, Z])(implicit tTag: ClassTag[T], xTag: ClassTag[X], oyuTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[Y], U)]): GenericGenomicDataset[(Option[X], T), (Option[Y], U)]

    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.

    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

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

    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.

    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

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

    See also

      rightOuterBroadcastRegionJoinAgainstAndGroupByRight

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

    See also

      rightOuterBroadcastRegionJoinAgainstAndGroupByRight

75. #### def rightOuterBroadcastRegionJoinAndGroupByRight[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Iterable[T], X), (Seq[U], 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.

    See also

      rightOuterBroadcastRegionJoinAgainstAndGroupByRight

76. #### def rightOuterBroadcastRegionJoinAndGroupByRight[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Iterable[T], X), (Seq[U], 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.

    See also

      rightOuterBroadcastRegionJoinAgainstAndGroupByRight

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

78. #### def rightOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[T], xTag: ClassTag[X], otxTag: ClassTag[(Option[T], X)], ouyTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[U], Y)]): GenericGenomicDataset[(Option[T], X), (Option[U], 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.

79. #### def rightOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Option[T], X), (Option[U], 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.

80. #### def rightOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Option[T], X), (Option[U], 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.

81. #### def rightOuterShuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[T], xTag: ClassTag[X], otixTag: ClassTag[(Option[T], Iterable[X])], otsyTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[U], Seq[Y])]): GenericGenomicDataset[(Option[T], Iterable[X]), (Option[U], 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.

82. #### def rightOuterShuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[T], xTag: ClassTag[X], otixTag: ClassTag[(Option[T], Iterable[X])], ousyTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[U], Seq[Y])]): GenericGenomicDataset[(Option[T], Iterable[X]), (Option[U], 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.

83. #### def rightOuterShuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Option[T], Iterable[X]), (Option[U], 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.

84. #### def rightOuterShuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Option[T], Iterable[X]), (Option[U], 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.

85. #### 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.

86. #### def saveAsPartitionedParquet(pathName: String, compressCodec: CompressionCodecName = CompressionCodecName.GZIP, partitionSize: Int = 1000000): Unit

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

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

    pathName

      The path to save the partitioned Parquet file to.

    compressCodec

      Name of the compression codec to use.

    partitionSize

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

87. #### 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

88. #### def saveMetadata(pathName: String): Unit

    Writes any necessary metadata to disk.

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

    pathName

      The path to save metadata to.

    Attributes
      protected

89. #### def saveSequences(pathName: String): Unit

    Save the sequence dictionary to disk.

    Save the sequence dictionary to disk.

    pathName

      The path to save the sequence dictionary to.

    Attributes
      protected

90. #### def shuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[T], xTag: ClassTag[X], txTag: ClassTag[(T, X)], uyTag: scala.reflect.api.JavaUniverse.TypeTag[(U, Y)]): GenericGenomicDataset[(T, X), (U, 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.

91. #### def shuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[T], xTag: ClassTag[X], txTag: ClassTag[(T, X)], uyTag: scala.reflect.api.JavaUniverse.TypeTag[(U, Y)]): GenericGenomicDataset[(T, X), (U, 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.

92. #### def shuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(T, X), (U, 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.

93. #### def shuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(T, X), (U, 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.

94. #### def shuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[T], xTag: ClassTag[X], tixTag: ClassTag[(T, Iterable[X])], uiyTag: scala.reflect.api.JavaUniverse.TypeTag[(U, Seq[Y])]): GenericGenomicDataset[(T, Iterable[X]), (U, 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.

95. #### def shuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[T], xTag: ClassTag[X], tixTag: ClassTag[(T, Iterable[X])], uiyTag: scala.reflect.api.JavaUniverse.TypeTag[(U, Seq[Y])]): GenericGenomicDataset[(T, Iterable[X]), (U, 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.

96. #### def shuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(T, Iterable[X]), (U, 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.

97. #### def shuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(T, Iterable[X]), (U, 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.

98. #### def sort(partitions: Int = rdd.partitions.length, stringency: ValidationStringency = ValidationStringency.STRICT)(implicit tTag: ClassTag[T]): V

    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.

    Note

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

    See also

      sortLexicographically

99. #### def sort(): V

    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.

    See also

      sortLexicographically

100. #### def sortLexicographically(partitions: Int = rdd.partitions.length, storePartitionMap: Boolean = false, storageLevel: StorageLevel = StorageLevel.MEMORY_ONLY, stringency: ValidationStringency = ValidationStringency.STRICT)(implicit tTag: ClassTag[T]): V

     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.

     Note

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

     See also

       sort

101. #### def sortLexicographically(): V

     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.

     See also

       sort

102. #### final def synchronized[T0](arg0: ⇒ T0): T0

     Definition Classes
       AnyRef

103. #### def toDF(): DataFrame

     returns

       These data as a Spark SQL DataFrame.

104. #### def toString(): String

     Definition Classes
       GenomicDataset → AnyRef → Any

105. #### def trace(mkr: Marker, msg: ⇒ Any, t: ⇒ Throwable): Unit

     Attributes
       protected
     Definition Classes
       Logging

106. #### def trace(msg: ⇒ Any, t: ⇒ Throwable): Unit

     Attributes
       protected
     Definition Classes
       Logging

107. #### def trace(msg: ⇒ Any): Unit

     Attributes
       protected
     Definition Classes
       Logging

108. #### def transform(tFn: Function[JavaRDD[T], JavaRDD[T]]): V

     (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.

109. #### def transform(tFn: (RDD[T]) ⇒ RDD[T]): V

     (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.

110. #### def transformDataFrame(tFn: Function[DataFrame, DataFrame]): V

     (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.

111. #### def transformDataFrame(tFn: (DataFrame) ⇒ DataFrame)(implicit uTag: scala.reflect.api.JavaUniverse.TypeTag[U]): V

     (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.

112. #### def transmute[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](tFn: Function[JavaRDD[T], JavaRDD[X]], convFn: Function2[V, 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.

113. #### def transmute[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](tFn: (RDD[T]) ⇒ RDD[X])(implicit convFn: (V, 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.

114. #### def transmuteDataFrame[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](tFn: Function[DataFrame, DataFrame], convFn: GenomicDatasetConversion[T, U, V, 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.

115. #### def transmuteDataFrame[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](tFn: (DataFrame) ⇒ DataFrame)(implicit yTag: scala.reflect.api.JavaUniverse.TypeTag[Y], convFn: (V, 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.

116. #### def transmuteDataset[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](tFn: Function[Dataset[U], Dataset[Y]], convFn: GenomicDatasetConversion[T, U, V, 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.

117. #### def transmuteDataset[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](tFn: (Dataset[U]) ⇒ Dataset[Y])(implicit yTag: scala.reflect.api.JavaUniverse.TypeTag[Y], convFn: (V, 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.

118. #### def union(datasets: List[V]): V

     (Java-specific) Unions together multiple genomic datasets.

     (Java-specific) Unions together multiple genomic datasets.

     datasets

       Genomic datasets to union with this genomic dataset.

119. #### def unpersist(): V

     Unpersists underlying RDD from memory or disk.

     Unpersists underlying RDD from memory or disk.

     returns

       Uncached GenomicDataset.

120. #### final def wait(): Unit

     Definition Classes
       AnyRef
     Annotations
       @throws( ... )

121. #### final def wait(arg0: Long, arg1: Int): Unit

     Definition Classes
       AnyRef
     Annotations
       @throws( ... )

122. #### final def wait(arg0: Long): Unit

     Definition Classes
       AnyRef
     Annotations
       @throws( ... )

123. #### def warn(mkr: Marker, msg: ⇒ Any, t: ⇒ Throwable): Unit

     Attributes
       protected
     Definition Classes
       Logging

124. #### def warn(msg: ⇒ Any, t: ⇒ Throwable): Unit

     Attributes
       protected
     Definition Classes
       Logging

125. #### def warn(msg: ⇒ Any): Unit

     Attributes
       protected
     Definition Classes
       Logging

126. #### 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

### Inherited from Logging

### Inherited from AnyRef

### Inherited from Any

### Ungrouped