case class DatasetBoundAlignmentDataset extends AlignmentDataset with DatasetBoundGenomicDataset[Alignment, Alignment, AlignmentDataset] with Product with Serializable
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- DatasetBoundGenomicDataset
- AlignmentDataset
- AvroReadGroupGenomicDataset
- GenomicDatasetWithLineage
- AvroGenomicDataset
- GenomicDataset
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-
def
addProcessingStep(newProcessingStep: ProcessingStep): AlignmentDataset
Merges a new processing record with the extant computational lineage.
Merges a new processing record with the extant computational lineage.
- returns
Returns a new GenomicDataset with new read groups merged in.
- Definition Classes
- GenomicDatasetWithLineage
-
def
addReadGroup(readGroupToAdd: ReadGroup): AlignmentDataset
Adds a single read group to the extant read groups.
Adds a single read group to the extant read groups.
- readGroupToAdd
The read group to append to the extant read groups.
- returns
Returns a new GenomicDataset with the new read group added.
- Definition Classes
- AvroReadGroupGenomicDataset
-
def
addReadGroups(readGroupsToAdd: ReadGroupDictionary): AlignmentDataset
Merges a new set of read groups with the extant read groups.
Merges a new set of read groups with the extant read groups.
- readGroupsToAdd
The read group dictionary to append to the extant read groups.
- returns
Returns a new GenomicDataset with new read groups merged in.
- Definition Classes
- AvroReadGroupGenomicDataset
-
def
addSequence(sequenceToAdd: SequenceRecord): AlignmentDataset
Appends metadata for a single sequence to the current genomic dataset.
Appends metadata for a single sequence to the current genomic dataset.
- sequenceToAdd
The sequence to add.
- returns
Returns a new GenomicDataset with this sequence appended.
- Definition Classes
- GenomicDataset
-
def
addSequences(sequencesToAdd: SequenceDictionary): AlignmentDataset
Appends sequence metadata to the current genomic dataset.
Appends sequence metadata to the current genomic dataset.
- sequencesToAdd
The new sequences to append.
- returns
Returns a new GenomicDataset with the sequences appended.
- Definition Classes
- GenomicDataset
-
final
def
asInstanceOf[T0]: T0
- Definition Classes
- Any
-
def
binQualityScores(bins: Seq[QualityScoreBin]): AlignmentDataset
(Scala-specific) Rewrites the quality scores of reads to place all quality scores in bins.
(Scala-specific) Rewrites the quality scores of reads to place all quality scores in bins.
Quality score binning maps all quality scores to a limited number of discrete values, thus reducing the entropy of the quality score distribution, and reducing the amount of space that reads consume on disk.
- bins
The bins to use.
- returns
Reads whose quality scores are binned.
- Definition Classes
- AlignmentDataset
-
def
binQualityScores(bins: List[QualityScoreBin]): AlignmentDataset
(Java-specific) Rewrites the quality scores of reads to place all quality scores in bins.
(Java-specific) Rewrites the quality scores of reads to place all quality scores in bins.
Quality score binning maps all quality scores to a limited number of discrete values, thus reducing the entropy of the quality score distribution, and reducing the amount of space that reads consume on disk.
- bins
The bins to use.
- returns
Reads whose quality scores are binned.
- Definition Classes
- AlignmentDataset
-
def
broadcast()(implicit tTag: ClassTag[Alignment]): GenomicBroadcast[Alignment, Alignment, AlignmentDataset]
- Definition Classes
- GenomicDataset
-
def
broadcastRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[Alignment], xTag: ClassTag[X], txTag: ClassTag[(Alignment, X)], uyTag: scala.reflect.api.JavaUniverse.TypeTag[(Alignment, Y)]): GenericGenomicDataset[(Alignment, X), (Alignment, Y)]
Performs a broadcast inner join between this genomic dataset and another genomic dataset.
Performs a broadcast inner join between this genomic dataset and another genomic dataset.
In a broadcast join, the left genomic dataset (this genomic dataset) is collected to the driver, and broadcast to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is an inner join, all values who do not overlap a value from the other genomic dataset are dropped.
- genomicDataset
The right genomic dataset in the join.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space.
- Definition Classes
- GenomicDataset
- See also
broadcastRegionJoinAgainst
-
def
broadcastRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[Alignment], xTag: ClassTag[X], txTag: ClassTag[(Alignment, X)], uyTag: scala.reflect.api.JavaUniverse.TypeTag[(Alignment, Y)]): GenericGenomicDataset[(Alignment, X), (Alignment, Y)]
Performs a broadcast inner join between this genomic dataset and another genomic dataset.
Performs a broadcast inner join between this genomic dataset and another genomic dataset.
In a broadcast join, the left genomic dataset (this genomic dataset) is collected to the driver, and broadcast to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is an inner join, all values who do not overlap a value from the other genomic dataset are dropped.
- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space.
- Definition Classes
- GenomicDataset
- See also
broadcastRegionJoinAgainst
-
def
broadcastRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Alignment, X), (Alignment, Y)]
(Java-specific) Performs a broadcast inner join between this genomic dataset and another genomic dataset.
(Java-specific) Performs a broadcast inner join between this genomic dataset and another genomic dataset.
In a broadcast join, the left genomic dataset (this genomic dataset) is collected to the driver, and broadcast to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is an inner join, all values who do not overlap a value from the other genomic dataset are dropped.
- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space.
- Definition Classes
- GenomicDataset
-
def
broadcastRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Alignment, X), (Alignment, Y)]
(R-specific) Performs a broadcast inner join between this genomic dataset and another genomic dataset.
(R-specific) Performs a broadcast inner join between this genomic dataset and another genomic dataset.
In a broadcast join, the left genomic dataset (this genomic dataset) is collected to the driver, and broadcast to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is an inner join, all values who do not overlap a value from the other genomic dataset are dropped.
- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space.
- Definition Classes
- GenomicDataset
-
def
broadcastRegionJoinAgainst[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](broadcast: GenomicBroadcast[X, Y, Z])(implicit tTag: ClassTag[Alignment], xTag: ClassTag[X], uyTag: scala.reflect.api.JavaUniverse.TypeTag[(Y, Alignment)]): GenericGenomicDataset[(X, Alignment), (Y, Alignment)]
Performs a broadcast inner join between this genomic dataset and data that has been broadcast.
Performs a broadcast inner join between this genomic dataset and data that has been broadcast.
In a broadcast join, the left side of the join (broadcastTree) is broadcast to to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is an inner join, all values who do not overlap a value from the other genomic dataset are dropped. As compared to broadcastRegionJoin, this function allows the broadcast object to be reused across multiple joins.
- broadcast
The data on the left side of the join.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space.
- Definition Classes
- GenomicDataset
- Note
This function differs from other region joins as it treats the calling genomic dataset as the right side of the join, and not the left.
- See also
broadcastRegionJoin
-
def
broadcastRegionJoinAgainstAndGroupByRight[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](broadcast: GenomicBroadcast[X, Y, Z])(implicit tTag: ClassTag[Alignment], xTag: ClassTag[X], syuTag: scala.reflect.api.JavaUniverse.TypeTag[(Seq[Y], Alignment)]): GenericGenomicDataset[(Iterable[X], Alignment), (Seq[Y], Alignment)]
Performs a broadcast inner join between this genomic dataset and another genomic dataset.
Performs a broadcast inner join between this genomic dataset and another genomic dataset.
In a broadcast join, the left side of the join (broadcastTree) is broadcast to to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is an inner join, all values who do not overlap a value from the other genomic dataset are dropped. As compared to broadcastRegionJoin, this function allows the broadcast object to be reused across multiple joins.
- broadcast
The data on the left side of the join.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space.
- Definition Classes
- GenomicDataset
- Note
This function differs from other region joins as it treats the calling genomic dataset as the right side of the join, and not the left.
- See also
broadcastRegionJoinAndGroupByRight
-
def
broadcastRegionJoinAndGroupByRight[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[Alignment], xTag: ClassTag[X], itxTag: ClassTag[(Iterable[Alignment], X)], iuyTag: scala.reflect.api.JavaUniverse.TypeTag[(Seq[Alignment], Y)]): GenericGenomicDataset[(Iterable[Alignment], X), (Seq[Alignment], Y)]
Performs a broadcast inner join between this genomic dataset and another genomic dataset.
Performs a broadcast inner join between this genomic dataset and another genomic dataset.
In a broadcast join, the left genomic dataset (this genomic dataset) is collected to the driver, and broadcast to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is an inner join, all values who do not overlap a value from the other genomic dataset are dropped.
- genomicDataset
The right genomic dataset in the join.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space.
- Definition Classes
- GenomicDataset
- See also
broadcastRegionJoinAgainstAndGroupByRight
-
def
broadcastRegionJoinAndGroupByRight[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[Alignment], xTag: ClassTag[X], itxTag: ClassTag[(Iterable[Alignment], X)], iuyTag: scala.reflect.api.JavaUniverse.TypeTag[(Seq[Alignment], Y)]): GenericGenomicDataset[(Iterable[Alignment], X), (Seq[Alignment], Y)]
Performs a broadcast inner join between this genomic dataset and another genomic dataset.
Performs a broadcast inner join between this genomic dataset and another genomic dataset.
In a broadcast join, the left genomic dataset (this genomic dataset) is collected to the driver, and broadcast to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is an inner join, all values who do not overlap a value from the other genomic dataset are dropped.
- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space.
- Definition Classes
- GenomicDataset
- See also
broadcastRegionJoinAgainstAndGroupByRight
-
def
broadcastRegionJoinAndGroupByRight[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Iterable[Alignment], X), (Seq[Alignment], Y)]
(Java-specific) Performs a broadcast inner join between this genomic dataset and another genomic dataset.
(Java-specific) Performs a broadcast inner join between this genomic dataset and another genomic dataset.
In a broadcast join, the left genomic dataset (this genomic dataset) is collected to the driver, and broadcast to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is an inner join, all values who do not overlap a value from the other genomic dataset are dropped.
- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space.
- Definition Classes
- GenomicDataset
- See also
broadcastRegionJoinAgainstAndGroupByRight
-
def
broadcastRegionJoinAndGroupByRight[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Iterable[Alignment], X), (Seq[Alignment], Y)]
(R-specific) Performs a broadcast inner join between this genomic dataset and another genomic dataset.
(R-specific) Performs a broadcast inner join between this genomic dataset and another genomic dataset.
In a broadcast join, the left genomic dataset (this genomic dataset) is collected to the driver, and broadcast to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is an inner join, all values who do not overlap a value from the other genomic dataset are dropped.
- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space.
- Definition Classes
- GenomicDataset
- See also
broadcastRegionJoinAgainstAndGroupByRight
-
def
buildTree(rdd: RDD[(ReferenceRegion, Alignment)])(implicit tTag: ClassTag[Alignment]): IntervalArray[ReferenceRegion, Alignment]
- Attributes
- protected
- Definition Classes
- AlignmentDataset → GenomicDataset
-
def
cache(): AlignmentDataset
Caches underlying RDD in memory.
Caches underlying RDD in memory.
- returns
Cached GenomicDataset.
- Definition Classes
- DatasetBoundGenomicDataset → GenomicDataset
-
def
clone(): AnyRef
- Attributes
- protected[java.lang]
- Definition Classes
- AnyRef
- Annotations
- @native() @throws( ... )
-
def
computeMismatchingPositions(referenceFile: ReferenceFile, overwriteExistingTags: Boolean = false, validationStringency: ValidationStringency = ValidationStringency.LENIENT): AlignmentDataset
(Scala-specific) Computes the mismatching positions field (SAM "MD" tag).
(Scala-specific) Computes the mismatching positions field (SAM "MD" tag).
- referenceFile
A reference file that can be broadcast to all nodes.
- overwriteExistingTags
If true, overwrites the MD tags on reads where it is already populated. If false, we only tag reads that are currently missing an MD tag. Default is false.
- validationStringency
If we are recalculating existing tags and we find that the MD tag that was previously on the read doesn't match our new tag, LENIENT will log a warning message, STRICT will throw an exception, and SILENT will ignore. Default is LENIENT.
- returns
Returns a new AlignmentDataset where all reads have the mismatchingPositions field populated.
- Definition Classes
- AlignmentDataset
-
def
computeMismatchingPositions(referenceFile: ReferenceFile, overwriteExistingTags: Boolean, validationStringency: ValidationStringency): AlignmentDataset
(Java-specific) Computes the mismatching positions field (SAM "MD" tag).
(Java-specific) Computes the mismatching positions field (SAM "MD" tag).
- referenceFile
A reference file that can be broadcast to all nodes.
- overwriteExistingTags
If true, overwrites the MD tags on reads where it is already populated. If false, we only tag reads that are currently missing an MD tag.
- validationStringency
If we are recalculating existing tags and we find that the MD tag that was previously on the read doesn't match our new tag, LENIENT will log a warning message, STRICT will throw an exception, and SILENT will ignore.
- returns
Returns a new AlignmentDataset where all reads have the mismatchingPositions field populated.
- Definition Classes
- AlignmentDataset
-
def
convertToSam(sortOrder: SortOrder): (SAMFileHeader, RDD[SAMRecordWritable])
Converts this genomic dataset of Alignments to HTSJDK SAMRecords.
Converts this genomic dataset of Alignments to HTSJDK SAMRecords.
- sortOrder
Sort order.
- returns
Return a tuple of SAMFileHeader and an RDD of HTSJDK SAMRecords.
- Definition Classes
- AlignmentDataset
-
def
convertToSam(isSorted: Boolean = false): (SAMFileHeader, RDD[SAMRecordWritable])
Converts this genomic dataset of Alignments to HTSJDK SAMRecords.
Converts this genomic dataset of Alignments to HTSJDK SAMRecords.
- isSorted
True if sorted.
- returns
Return a tuple of SAMFileHeader and an RDD of HTSJDK SAMRecords.
- Definition Classes
- AlignmentDataset
-
def
countKmers(kmerLength: Int): RDD[(String, Long)]
Cuts reads into _k_-mers, and then counts the number of occurrences of each _k_-mer.
Cuts reads into _k_-mers, and then counts the number of occurrences of each _k_-mer.
- kmerLength
The value of _k_ to use for cutting _k_-mers.
- returns
Returns an RDD containing k-mer/count pairs.
- Definition Classes
- AlignmentDataset
-
def
countKmersAsDataset(kmerLength: Int): Dataset[(String, Long)]
Cuts reads into _k_-mers, and then counts the number of occurrences of each _k_-mer.
Cuts reads into _k_-mers, and then counts the number of occurrences of each _k_-mer.
- kmerLength
The value of _k_ to use for cutting _k_-mers.
- returns
Returns a Dataset containing k-mer/count pairs.
- Definition Classes
- AlignmentDataset
-
val
dataset: Dataset[Alignment]
These data as a Spark SQL Dataset.
These data as a Spark SQL Dataset.
- Definition Classes
- DatasetBoundAlignmentDataset → GenomicDataset
-
def
debug(mkr: Marker, msg: ⇒ Any, t: ⇒ Throwable): Unit
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- protected
- Definition Classes
- Logging
-
def
debug(msg: ⇒ Any, t: ⇒ Throwable): Unit
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- protected
- Definition Classes
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def
debug(msg: ⇒ Any): Unit
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final
def
eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
-
def
error(mkr: Marker, msg: ⇒ Any, t: ⇒ Throwable): Unit
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- protected
- Definition Classes
- Logging
-
def
error(msg: ⇒ Any, t: ⇒ Throwable): Unit
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- protected
- Definition Classes
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def
error(msg: ⇒ Any): Unit
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- Definition Classes
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def
filterByMappingQuality(minimumMappingQuality: Int): AlignmentDataset
Filter this AlignmentDataset by mapping quality.
Filter this AlignmentDataset by mapping quality.
- minimumMappingQuality
Minimum mapping quality to filter by, inclusive.
- returns
AlignmentDataset filtered by mapping quality.
- Definition Classes
- DatasetBoundAlignmentDataset → AlignmentDataset
-
def
filterByOverlappingRegion(query: ReferenceRegion): AlignmentDataset
Runs a filter that selects data in the underlying RDD that overlaps a single genomic region.
Runs a filter that selects data in the underlying RDD that overlaps a single genomic region.
- query
The region to query for.
- returns
Returns a new GenomicDataset containing only data that overlaps the query region.
- Definition Classes
- GenomicDataset
-
def
filterByOverlappingRegions(querys: Iterable[ReferenceRegion]): AlignmentDataset
(Scala-specific) Runs a filter that selects data in the underlying RDD that overlaps several genomic regions.
(Scala-specific) Runs a filter that selects data in the underlying RDD that overlaps several genomic regions.
- querys
The regions to query for.
- returns
Returns a new GenomicDataset containing only data that overlaps the querys region.
- Definition Classes
- DatasetBoundGenomicDataset → GenomicDataset
-
def
filterByOverlappingRegions(querys: Iterable[ReferenceRegion]): AlignmentDataset
(Java-specific) Runs a filter that selects data in the underlying RDD that overlaps several genomic regions.
(Java-specific) Runs a filter that selects data in the underlying RDD that overlaps several genomic regions.
- querys
The regions to query for.
- returns
Returns a new GenomicDataset containing only data that overlaps the querys region.
- Definition Classes
- GenomicDataset
-
def
filterDuplicateReads(): AlignmentDataset
Filter duplicate reads from this AlignmentDataset.
Filter duplicate reads from this AlignmentDataset.
- returns
AlignmentDataset filtered to remove duplicate reads.
- Definition Classes
- DatasetBoundAlignmentDataset → AlignmentDataset
-
def
filterToPrimaryAlignments(): AlignmentDataset
Filter this AlignmentDataset to include only primary alignments.
Filter this AlignmentDataset to include only primary alignments.
- returns
AlignmentDataset filtered to include only primary alignments.
- Definition Classes
- DatasetBoundAlignmentDataset → AlignmentDataset
-
def
filterToReadGroup(readGroupId: String): AlignmentDataset
Filter this AlignmentDataset by read group to those that match the specified read group.
Filter this AlignmentDataset by read group to those that match the specified read group.
- readGroupId
Read group to filter by.
- returns
AlignmentDataset filtered by read group.
- Definition Classes
- DatasetBoundAlignmentDataset → AlignmentDataset
-
def
filterToReadGroups(readGroupIds: Seq[String]): AlignmentDataset
(Scala-specific) Filter this AlignmentDataset by read group to those that match the specified read groups.
(Scala-specific) Filter this AlignmentDataset by read group to those that match the specified read groups.
- readGroupIds
Sequence of read groups to filter by.
- returns
AlignmentDataset filtered by one or more read groups.
- Definition Classes
- DatasetBoundAlignmentDataset → AlignmentDataset
-
def
filterToReadGroups(readGroupIds: List[String]): AlignmentDataset
(Java-specific) Filter this AlignmentDataset by read group to those that match the specified read groups.
(Java-specific) Filter this AlignmentDataset by read group to those that match the specified read groups.
- readGroupIds
List of read groups to filter by.
- returns
AlignmentDataset filtered by one or more read groups.
- Definition Classes
- AlignmentDataset
-
def
filterToSample(readGroupSampleId: String): AlignmentDataset
Filter this AlignmentDataset by sample to those that match the specified sample.
Filter this AlignmentDataset by sample to those that match the specified sample.
- readGroupSampleId
Sample to filter by.
- returns
AlignmentDataset filtered by the specified sample.
- Definition Classes
- DatasetBoundAlignmentDataset → AlignmentDataset
-
def
filterToSamples(readGroupSampleIds: Seq[String]): AlignmentDataset
(Scala-specific) Filter this AlignmentDataset by sample to those that match the specified samples.
(Scala-specific) Filter this AlignmentDataset by sample to those that match the specified samples.
- readGroupSampleIds
Sequence of samples to filter by.
- returns
AlignmentDataset filtered by the specified samples.
- Definition Classes
- DatasetBoundAlignmentDataset → AlignmentDataset
-
def
filterToSamples(readGroupSampleIds: List[String]): AlignmentDataset
(Java-specific) Filter this AlignmentDataset by sample to those that match the specified samples.
(Java-specific) Filter this AlignmentDataset by sample to those that match the specified samples.
- readGroupSampleIds
List of samples to filter by.
- returns
AlignmentDataset filtered by the specified samples.
- Definition Classes
- AlignmentDataset
-
def
filterUnalignedReads(): AlignmentDataset
Filter unaligned reads from this AlignmentDataset.
Filter unaligned reads from this AlignmentDataset.
- returns
AlignmentDataset filtered to remove unaligned reads.
- Definition Classes
- DatasetBoundAlignmentDataset → AlignmentDataset
-
def
filterUnpairedReads(): AlignmentDataset
Filter unpaired reads from this AlignmentDataset.
Filter unpaired reads from this AlignmentDataset.
- returns
AlignmentDataset filtered to remove unpaired reads.
- Definition Classes
- DatasetBoundAlignmentDataset → AlignmentDataset
-
def
finalize(): Unit
- Attributes
- protected[java.lang]
- Definition Classes
- AnyRef
- Annotations
- @throws( classOf[java.lang.Throwable] )
-
def
flagStat(): (FlagStatMetrics, FlagStatMetrics)
Runs a quality control pass akin to the Samtools FlagStat tool.
Runs a quality control pass akin to the Samtools FlagStat tool.
- returns
Returns a tuple of (failedQualityMetrics, passedQualityMetrics)
- Definition Classes
- AlignmentDataset
-
def
flattenRddByRegions(): RDD[(ReferenceRegion, Alignment)]
- Attributes
- protected
- Definition Classes
- GenomicDataset
-
def
fullOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[Alignment], xTag: ClassTag[X], otoxTag: ClassTag[(Option[Alignment], Option[X])], ouoyTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[Alignment], Option[Y])]): GenericGenomicDataset[(Option[Alignment], Option[X]), (Option[Alignment], Option[Y])]
Performs a sort-merge full outer join between this genomic dataset and another genomic dataset.
Performs a sort-merge full outer join between this genomic dataset and another genomic dataset.
In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is a full outer join, if a value from either genomic dataset does not overlap any values in the other genomic dataset, it will be paired with a
None
in the product of the join.- genomicDataset
The right genomic dataset in the join.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and values that did not overlap will be paired with a
None
.
- Definition Classes
- GenomicDataset
-
def
fullOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[Alignment], xTag: ClassTag[X], otoxTag: ClassTag[(Option[Alignment], Option[X])], ouoyTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[Alignment], Option[Y])]): GenericGenomicDataset[(Option[Alignment], Option[X]), (Option[Alignment], Option[Y])]
Performs a sort-merge full outer join between this genomic dataset and another genomic dataset.
Performs a sort-merge full outer join between this genomic dataset and another genomic dataset.
In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is a full outer join, if a value from either genomic dataset does not overlap any values in the other genomic dataset, it will be paired with a
None
in the product of the join.- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and values that did not overlap will be paired with a
None
.
- Definition Classes
- GenomicDataset
-
def
fullOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Option[Alignment], Option[X]), (Option[Alignment], Option[Y])]
(Python-specific) Performs a sort-merge full outer join between this genomic dataset and another genomic dataset.
(Python-specific) Performs a sort-merge full outer join between this genomic dataset and another genomic dataset.
In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is a full outer join, if a value from either genomic dataset does not overlap any values in the other genomic dataset, it will be paired with a
None
in the product of the join.- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and values that did not overlap will be paired with a
None
.
- Definition Classes
- GenomicDataset
-
def
fullOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Option[Alignment], Option[X]), (Option[Alignment], Option[Y])]
(R-specific) Performs a sort-merge full outer join between this genomic dataset and another genomic dataset.
(R-specific) Performs a sort-merge full outer join between this genomic dataset and another genomic dataset.
In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is a full outer join, if a value from either genomic dataset does not overlap any values in the other genomic dataset, it will be paired with a
None
in the product of the join.- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and values that did not overlap will be paired with a
None
.
- Definition Classes
- GenomicDataset
-
final
def
getClass(): Class[_]
- Definition Classes
- AnyRef → Any
- Annotations
- @native()
-
def
getReferenceRegions(elem: Alignment): Seq[ReferenceRegion]
Returns all reference regions that overlap this read.
Returns all reference regions that overlap this read.
If a read is unaligned, it covers no reference region. If a read is aligned we expect it to cover a single region. A chimeric read would cover multiple regions, but we store chimeric reads in a way similar to BAM, where the split alignments are stored in multiple separate reads.
- elem
Read to produce regions for.
- returns
The seq of reference regions this read covers.
- Attributes
- protected
- Definition Classes
- AlignmentDataset → GenomicDataset
-
def
info(mkr: Marker, msg: ⇒ Any, t: ⇒ Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
info(msg: ⇒ Any, t: ⇒ Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
info(msg: ⇒ Any): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
isDebugEnabled: Boolean
- Attributes
- protected
- Definition Classes
- Logging
-
def
isErrorEnabled: Boolean
- Attributes
- protected
- Definition Classes
- Logging
-
def
isInfoEnabled: Boolean
- Attributes
- protected
- Definition Classes
- Logging
-
final
def
isInstanceOf[T0]: Boolean
- Definition Classes
- Any
-
val
isPartitioned: Boolean
- Definition Classes
- DatasetBoundAlignmentDataset → DatasetBoundGenomicDataset
-
def
isSorted: Boolean
- Definition Classes
- GenomicDataset
-
def
isTraceEnabled: Boolean
- Attributes
- protected
- Definition Classes
- Logging
-
def
isWarnEnabled: Boolean
- Attributes
- protected
- Definition Classes
- Logging
-
lazy val
jrdd: JavaRDD[Alignment]
The underlying RDD of genomic data, as a JavaRDD.
The underlying RDD of genomic data, as a JavaRDD.
- Definition Classes
- GenomicDataset
-
def
leftNormalizeIndels(): AlignmentDataset
Left normalizes the INDELs in reads containing INDELs.
Left normalizes the INDELs in reads containing INDELs.
- returns
Returns a new genomic dataset where the reads that contained INDELs have their INDELs left normalized.
- Definition Classes
- AlignmentDataset
-
def
leftOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[Alignment], xTag: ClassTag[X], toxTag: ClassTag[(Alignment, Option[X])], uoyTag: scala.reflect.api.JavaUniverse.TypeTag[(Alignment, Option[Y])]): GenericGenomicDataset[(Alignment, Option[X]), (Alignment, Option[Y])]
Performs a sort-merge left outer join between this genomic dataset and another genomic dataset.
Performs a sort-merge left outer join between this genomic dataset and another genomic dataset.
In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is a left outer join, all values in the right genomic dataset that do not overlap a value from the left genomic dataset are dropped. If a value from the left genomic dataset does not overlap any values in the right genomic dataset, it will be paired with a
None
in the product of the join.- genomicDataset
The right genomic dataset in the join.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the left genomic dataset that did not overlap a key in the right genomic dataset.
- Definition Classes
- GenomicDataset
-
def
leftOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[Alignment], xTag: ClassTag[X], toxTag: ClassTag[(Alignment, Option[X])], uoyTag: scala.reflect.api.JavaUniverse.TypeTag[(Alignment, Option[Y])]): GenericGenomicDataset[(Alignment, Option[X]), (Alignment, Option[Y])]
Performs a sort-merge left outer join between this genomic dataset and another genomic dataset.
Performs a sort-merge left outer join between this genomic dataset and another genomic dataset.
In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is a left outer join, all values in the right genomic dataset that do not overlap a value from the left genomic dataset are dropped. If a value from the left genomic dataset does not overlap any values in the right genomic dataset, it will be paired with a
None
in the product of the join.- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the left genomic dataset that did not overlap a key in the right genomic dataset.
- Definition Classes
- GenomicDataset
-
def
leftOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Alignment, Option[X]), (Alignment, Option[Y])]
(Java-specific) Performs a sort-merge left outer join between this genomic dataset and another genomic dataset.
(Java-specific) Performs a sort-merge left outer join between this genomic dataset and another genomic dataset.
In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is a left outer join, all values in the right genomic dataset that do not overlap a value from the left genomic dataset are dropped. If a value from the left genomic dataset does not overlap any values in the right genomic dataset, it will be paired with a
None
in the product of the join.- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the left genomic dataset that did not overlap a key in the right genomic dataset.
- Definition Classes
- GenomicDataset
-
def
leftOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Alignment, Option[X]), (Alignment, Option[Y])]
(R-specific) Performs a sort-merge left outer join between this genomic dataset and another genomic dataset.
(R-specific) Performs a sort-merge left outer join between this genomic dataset and another genomic dataset.
In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is a left outer join, all values in the right genomic dataset that do not overlap a value from the left genomic dataset are dropped. If a value from the left genomic dataset does not overlap any values in the right genomic dataset, it will be paired with a
None
in the product of the join.- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the left genomic dataset that did not overlap a key in the right genomic dataset.
- Definition Classes
- GenomicDataset
-
def
leftOuterShuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[Alignment], xTag: ClassTag[X], toxTag: ClassTag[(Alignment, Iterable[X])], uiyTag: scala.reflect.api.JavaUniverse.TypeTag[(Alignment, Seq[Y])]): GenericGenomicDataset[(Alignment, Iterable[X]), (Alignment, Seq[Y])]
Performs a sort-merge left outer join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value.
Performs a sort-merge left outer join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value.
In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is a left outer join, all values in the right genomic dataset that do not overlap a value from the left genomic dataset are dropped. If a value from the left genomic dataset does not overlap any values in the right genomic dataset, it will be paired with an empty Iterable in the product of the join.
- genomicDataset
The right genomic dataset in the join.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the left genomic dataset that did not overlap a key in the right genomic dataset.
- Definition Classes
- GenomicDataset
-
def
leftOuterShuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[Alignment], xTag: ClassTag[X], toxTag: ClassTag[(Alignment, Iterable[X])], uiyTag: scala.reflect.api.JavaUniverse.TypeTag[(Alignment, Seq[Y])]): GenericGenomicDataset[(Alignment, Iterable[X]), (Alignment, Seq[Y])]
Performs a sort-merge left outer join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value.
Performs a sort-merge left outer join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value.
In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is a left outer join, all values in the right genomic dataset that do not overlap a value from the left genomic dataset are dropped. If a value from the left genomic dataset does not overlap any values in the right genomic dataset, it will be paired with an empty Iterable in the product of the join.
- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the left genomic dataset that did not overlap a key in the right genomic dataset.
- Definition Classes
- GenomicDataset
-
def
leftOuterShuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Alignment, Iterable[X]), (Alignment, Seq[Y])]
(Java-specific) Performs a sort-merge left outer join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value.
(Java-specific) Performs a sort-merge left outer join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value.
In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is a left outer join, all values in the right genomic dataset that do not overlap a value from the left genomic dataset are dropped. If a value from the left genomic dataset does not overlap any values in the right genomic dataset, it will be paired with an empty Iterable in the product of the join.
- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the left genomic dataset that did not overlap a key in the right genomic dataset.
- Definition Classes
- GenomicDataset
-
def
leftOuterShuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Alignment, Iterable[X]), (Alignment, Seq[Y])]
(R-specific) Performs a sort-merge left outer join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value.
(R-specific) Performs a sort-merge left outer join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value.
In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is a left outer join, all values in the right genomic dataset that do not overlap a value from the left genomic dataset are dropped. If a value from the left genomic dataset does not overlap any values in the right genomic dataset, it will be paired with an empty Iterable in the product of the join.
- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the left genomic dataset that did not overlap a key in the right genomic dataset.
- Definition Classes
- GenomicDataset
-
def
logger: Logger
- Attributes
- protected
- Definition Classes
- Logging
-
def
loggerName: String
- Attributes
- protected
- Definition Classes
- Logging
-
def
markDuplicates(): AlignmentDataset
Marks reads as possible fragment duplicates.
Marks reads as possible fragment duplicates.
- returns
A new genomic dataset where reads have the duplicate read flag set. Duplicate reads are NOT filtered out.
- Definition Classes
- AlignmentDataset
-
final
def
ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
-
final
def
notify(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native()
-
final
def
notifyAll(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native()
-
val
optLookbackPartitions: Option[Int]
- Definition Classes
- DatasetBoundAlignmentDataset → DatasetBoundGenomicDataset
-
val
optPartitionBinSize: Option[Int]
- Definition Classes
- DatasetBoundAlignmentDataset → DatasetBoundGenomicDataset
-
lazy val
optPartitionMap: None.type
- Attributes
- protected
- Definition Classes
- DatasetBoundAlignmentDataset → GenomicDataset
-
def
persist(sl: StorageLevel): AlignmentDataset
Persists underlying RDD in memory or disk.
Persists underlying RDD in memory or disk.
- sl
new StorageLevel
- returns
Persisted GenomicDataset.
- Definition Classes
- DatasetBoundGenomicDataset → GenomicDataset
-
def
pipe[X, Y <: Product, Z <: GenomicDataset[X, Y, Z], W <: InFormatter[Alignment, Alignment, AlignmentDataset, W]](cmd: List[String], files: List[String], environment: Map[String, String], flankSize: Integer, tFormatter: Class[W], xFormatter: OutFormatter[X], convFn: Function2[AlignmentDataset, RDD[X], Z]): Z
(Java/Python-specific) Pipes genomic data to a subprocess that runs in parallel using Spark.
(Java/Python-specific) Pipes genomic data to a subprocess that runs in parallel using Spark.
- X
The type of the record created by the piped command.
- Y
A GenomicDataset containing X's.
- cmd
Command to run.
- files
Files to make locally available to the commands being run. Default is empty.
- environment
A map containing environment variable/value pairs to set in the environment for the newly created process. Default is empty.
- flankSize
Number of bases to flank each command invocation by.
- tFormatter
Class of formatter for data going into pipe command.
- xFormatter
Formatter for data coming out of the pipe command.
- convFn
The conversion function used to build the final genomic dataset.
- returns
Returns a new GenomicDataset of type Y.
- Definition Classes
- GenomicDataset
-
def
pipe[X, Y <: Product, Z <: GenomicDataset[X, Y, Z], W <: InFormatter[Alignment, Alignment, AlignmentDataset, W]](cmd: Seq[Any], files: Seq[Any], environment: Map[Any, Any], flankSize: Double, tFormatter: Class[W], xFormatter: OutFormatter[X], convFn: Function2[AlignmentDataset, RDD[X], Z]): Z
(R-specific) Pipes genomic data to a subprocess that runs in parallel using Spark.
(R-specific) Pipes genomic data to a subprocess that runs in parallel using Spark.
- X
The type of the record created by the piped command.
- Y
A GenomicDataset containing X's.
- cmd
Command to run.
- files
Files to make locally available to the commands being run. Default is empty.
- environment
A map containing environment variable/value pairs to set in the environment for the newly created process. Default is empty.
- flankSize
Number of bases to flank each command invocation by.
- tFormatter
Class of formatter for data going into pipe command.
- xFormatter
Formatter for data coming out of the pipe command.
- convFn
The conversion function used to build the final genomic dataset.
- returns
Returns a new GenomicDataset of type Y.
- Definition Classes
- GenomicDataset
-
def
pipe[X, Y <: Product, Z <: GenomicDataset[X, Y, Z], W <: InFormatter[Alignment, Alignment, AlignmentDataset, 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[Alignment, Alignment, AlignmentDataset, W], xFormatter: OutFormatter[X], convFn: (AlignmentDataset, RDD[X]) ⇒ Z, tManifest: ClassTag[Alignment], xManifest: ClassTag[X]): Z
(Scala-specific) Pipes genomic data to a subprocess that runs in parallel using Spark.
(Scala-specific) Pipes genomic data to a subprocess that runs in parallel using Spark.
Files are substituted in to the command with a $x syntax. E.g., to invoke a command that uses the first file from the files Seq, use $0. To access the path to the directory where the files are copied, use $root.
Pipes require the presence of an InFormatterCompanion and an OutFormatter as implicit values. The InFormatterCompanion should be a singleton whose apply method builds an InFormatter given a specific type of GenomicDataset. The implicit InFormatterCompanion yields an InFormatter which is used to format the input to the pipe, and the implicit OutFormatter is used to parse the output from the pipe.
- X
The type of the record created by the piped command.
- Y
A GenomicDataset containing X's.
- cmd
Command to run.
- files
Files to make locally available to the commands being run. Default is empty.
- environment
A map containing environment variable/value pairs to set in the environment for the newly created process. Default is empty.
- flankSize
Number of bases to flank each command invocation by.
- optTimeout
An optional parameter specifying how long to let a single partition run for, in seconds. If the partition times out, the partial results will be returned, and no exception will be logged. The partition will log that the command timed out.
- returns
Returns a new GenomicDataset of type Y.
- Definition Classes
- GenomicDataset
-
val
processingSteps: Seq[ProcessingStep]
The processing steps that have been applied to this GenomicDataset.
The processing steps that have been applied to this GenomicDataset.
- Definition Classes
- DatasetBoundAlignmentDataset → GenomicDatasetWithLineage
-
val
productFn: (Alignment) ⇒ Alignment
- Attributes
- protected
- Definition Classes
- AlignmentDataset → GenomicDataset
-
lazy val
rdd: RDD[Alignment]
The RDD of genomic data that we are wrapping.
The RDD of genomic data that we are wrapping.
- Definition Classes
- DatasetBoundAlignmentDataset → GenomicDataset
-
val
readGroups: ReadGroupDictionary
A dictionary describing the read groups attached to this GenomicDataset.
A dictionary describing the read groups attached to this GenomicDataset.
- Definition Classes
- DatasetBoundAlignmentDataset → AvroReadGroupGenomicDataset
-
def
realignIndels(consensusModel: ConsensusGenerator = new ConsensusGeneratorFromReads, isSorted: Boolean = false, maxIndelSize: Int = 500, maxConsensusNumber: Int = 30, lodThreshold: Double = 5.0, maxTargetSize: Int = 3000, maxReadsPerTarget: Int = 20000, unclipReads: Boolean = false, optReferenceFile: Option[ReferenceFile] = None): AlignmentDataset
(Scala-specific) Realigns indels using a consensus-based heuristic.
(Scala-specific) Realigns indels using a consensus-based heuristic.
- consensusModel
The model to use for generating consensus sequences to realign against.
- isSorted
If the input data is sorted, setting this parameter to true avoids a second sort. Defaults to false.
- maxIndelSize
The size of the largest indel to use for realignment. Defaults to 500.
- maxConsensusNumber
The maximum number of consensus sequences to realign against per target region. Defaults to 30.
- lodThreshold
Log-odds threshold to use when realigning; realignments are only finalized if the log-odds threshold is exceeded. Defaults to 5.0.
- maxTargetSize
The maximum width of a single target region for realignment. Defaults to 3000.
- maxReadsPerTarget
Maximum number of reads per target. Defaults to 20000.
- unclipReads
If true, unclips reads prior to realignment. Else, omits clipped bases during realignment. Defaults to false.
- optReferenceFile
An optional reference. If not provided, reference will be inferred from MD tags. Defaults to None.
- returns
Returns a genomic dataset of mapped reads which have been realigned.
- Definition Classes
- AlignmentDataset
-
def
realignIndels(consensusModel: ConsensusGenerator, isSorted: Boolean, maxIndelSize: Integer, maxConsensusNumber: Integer, lodThreshold: Double, maxTargetSize: Integer, maxReadsPerTarget: Integer, unclipReads: Boolean, referenceFile: ReferenceFile): AlignmentDataset
(Java-specific) Realigns indels using a consensus-based heuristic with the specified reference.
(Java-specific) Realigns indels using a consensus-based heuristic with the specified reference.
- consensusModel
The model to use for generating consensus sequences to realign against.
- isSorted
If the input data is sorted, setting this parameter to true avoids a second sort.
- maxIndelSize
The size of the largest indel to use for realignment.
- maxConsensusNumber
The maximum number of consensus sequences to realign against per target region.
- lodThreshold
Log-odds threshold to use when realigning; realignments are only finalized if the log-odds threshold is exceeded.
- maxTargetSize
The maximum width of a single target region for realignment.
- maxReadsPerTarget
Maximum number of reads per target.
- unclipReads
If true, unclips reads prior to realignment. Else, omits clipped bases during realignment.
- referenceFile
Reference file.
- returns
Returns a genomic dataset of mapped reads which have been realigned.
- Definition Classes
- AlignmentDataset
-
def
realignIndels(consensusModel: ConsensusGenerator, isSorted: Boolean, maxIndelSize: Integer, maxConsensusNumber: Integer, lodThreshold: Double, maxTargetSize: Integer, maxReadsPerTarget: Integer, unclipReads: Boolean): AlignmentDataset
(Java-specific) Realigns indels using a consensus-based heuristic.
(Java-specific) Realigns indels using a consensus-based heuristic.
- consensusModel
The model to use for generating consensus sequences to realign against.
- isSorted
If the input data is sorted, setting this parameter to true avoids a second sort.
- maxIndelSize
The size of the largest indel to use for realignment.
- maxConsensusNumber
The maximum number of consensus sequences to realign against per target region.
- lodThreshold
Log-odds threshold to use when realigning; realignments are only finalized if the log-odds threshold is exceeded.
- maxTargetSize
The maximum width of a single target region for realignment.
- maxReadsPerTarget
Maximum number of reads per target.
- unclipReads
If true, unclips reads prior to realignment. Else, omits clipped bases during realignment.
- returns
Returns a genomic dataset of mapped reads which have been realigned.
- Definition Classes
- AlignmentDataset
-
def
realignIndels(referenceFile: ReferenceFile): AlignmentDataset
(Java-specific) Realigns indels using a consensus-based heuristic with the specified reference and default parameters.
(Java-specific) Realigns indels using a consensus-based heuristic with the specified reference and default parameters.
- referenceFile
Reference file.
- returns
Returns a genomic dataset of mapped reads which have been realigned.
- Definition Classes
- AlignmentDataset
-
def
realignIndels(): AlignmentDataset
(Java-specific) Realigns indels using a consensus-based heuristic with default parameters.
(Java-specific) Realigns indels using a consensus-based heuristic with default parameters.
- returns
Returns a genomic dataset of mapped reads which have been realigned.
- Definition Classes
- AlignmentDataset
-
def
reassembleReadPairs(secondPairRdd: RDD[Alignment], validationStringency: ValidationStringency = ValidationStringency.LENIENT): AlignmentDataset
(Scala-specific) Reassembles read pairs from two sets of unpaired reads.
(Scala-specific) Reassembles read pairs from two sets of unpaired reads. The assumption is that the two sets were _originally_ paired together.
- secondPairRdd
The rdd containing the second read from the pairs.
- validationStringency
How stringently to validate the reads.
- returns
Returns a genomic dataset with the pair information recomputed.
- Definition Classes
- AlignmentDataset
- Note
The RDD that this is called on should be the RDD with the first read from the pair.
-
def
reassembleReadPairs(secondPairRdd: JavaRDD[Alignment], validationStringency: ValidationStringency): AlignmentDataset
(Java-specific) Reassembles read pairs from two sets of unpaired reads.
(Java-specific) Reassembles read pairs from two sets of unpaired reads. The assumption is that the two sets were _originally_ paired together.
- secondPairRdd
The rdd containing the second read from the pairs.
- validationStringency
How stringently to validate the reads.
- returns
Returns a genomic dataset with the pair information recomputed.
- Definition Classes
- AlignmentDataset
- Note
The RDD that this is called on should be the RDD with the first read from the pair.
-
def
recalibrateBaseQualities(knownSnps: Broadcast[SnpTable], minAcceptableQuality: Int = 5, optStorageLevel: Option[StorageLevel] = Some(StorageLevel.MEMORY_ONLY), optSamplingFraction: Option[Double] = None, optSamplingSeed: Option[Long] = None): AlignmentDataset
(Scala-specific) Runs base quality score recalibration on a set of reads.
(Scala-specific) Runs base quality score recalibration on a set of reads. Uses a table of known SNPs to mask true variation during the recalibration process.
- knownSnps
A table of known SNPs to mask valid variants.
- minAcceptableQuality
The minimum quality score to recalibrate.
- optStorageLevel
An optional storage level to set for the output of the first stage of BQSR. Defaults to StorageLevel.MEMORY_ONLY.
- optSamplingFraction
An optional fraction of reads to sample when generating the covariate table.
- optSamplingSeed
An optional seed to provide if downsampling reads.
- returns
Returns a genomic dataset of recalibrated reads.
- Definition Classes
- AlignmentDataset
-
def
recalibrateBaseQualities(knownSnps: VariantDataset, minAcceptableQuality: Integer, storageLevel: StorageLevel, samplingFraction: Double, samplingSeed: Long): AlignmentDataset
(Java-specific) Runs base quality score recalibration on a set of reads.
(Java-specific) Runs base quality score recalibration on a set of reads. Uses a table of known SNPs to mask true variation during the recalibration process.
- knownSnps
A table of known SNPs to mask valid variants.
- minAcceptableQuality
The minimum quality score to recalibrate.
- storageLevel
Storage level to set for the output of the first stage of BQSR. Set to null to omit.
- samplingFraction
Fraction of reads to sample when generating the covariate table.
- samplingSeed
Seed to provide if downsampling reads.
- returns
Returns a genomic dataset of recalibrated reads.
- Definition Classes
- AlignmentDataset
-
def
recalibrateBaseQualities(knownSnps: VariantDataset, minAcceptableQuality: Integer, storageLevel: StorageLevel): AlignmentDataset
(Java-specific) Runs base quality score recalibration on a set of reads.
(Java-specific) Runs base quality score recalibration on a set of reads. Uses a table of known SNPs to mask true variation during the recalibration process.
- knownSnps
A table of known SNPs to mask valid variants.
- minAcceptableQuality
The minimum quality score to recalibrate.
- storageLevel
An optional storage level to set for the output of the first stage of BQSR. Set to null to omit.
- returns
Returns a genomic dataset of recalibrated reads.
- Definition Classes
- AlignmentDataset
-
def
replaceProcessingSteps(newProcessingSteps: Seq[ProcessingStep]): AlignmentDataset
Replaces the processing steps attached to this genomic dataset.
Replaces the processing steps attached to this genomic dataset.
- newProcessingSteps
The new processing steps to attach to this genomic dataset.
- returns
Returns a new GenomicDataset with new processing lineage attached.
- Definition Classes
- DatasetBoundAlignmentDataset → GenomicDatasetWithLineage
-
def
replaceRdd(newRdd: RDD[Alignment], newPartitionMap: Option[Array[Option[(ReferenceRegion, ReferenceRegion)]]] = None): AlignmentDataset
- Attributes
- protected
- Definition Classes
- AlignmentDataset → GenomicDataset
-
def
replaceRddAndSequences(newRdd: RDD[Alignment], newSequences: SequenceDictionary, partitionMap: Option[Array[Option[(ReferenceRegion, ReferenceRegion)]]] = None): AlignmentDataset
Replaces the underlying RDD and SequenceDictionary and emits a new object.
Replaces the underlying RDD and SequenceDictionary and emits a new object.
- newRdd
New RDD to replace current RDD.
- newSequences
New sequence dictionary to replace current dictionary.
- returns
Returns a new AlignmentDataset.
- Attributes
- protected
- Definition Classes
- AlignmentDataset
-
def
replaceReadGroups(newReadGroups: ReadGroupDictionary): AlignmentDataset
Replaces the read groups attached to this genomic dataset.
Replaces the read groups attached to this genomic dataset.
- newReadGroups
The new read group dictionary to attach.
- returns
Returns a new GenomicDataset with new read groups attached.
- Definition Classes
- DatasetBoundAlignmentDataset → AvroReadGroupGenomicDataset
-
def
replaceSequences(newSequences: SequenceDictionary): AlignmentDataset
Replaces the sequence dictionary attached to a GenomicDataset.
Replaces the sequence dictionary attached to a GenomicDataset.
- newSequences
The new sequence dictionary to attach.
- returns
Returns a new GenomicDataset with the sequences replaced.
- Definition Classes
- DatasetBoundAlignmentDataset → GenomicDataset
-
def
rightOuterBroadcastRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[Alignment], xTag: ClassTag[X], otxTag: ClassTag[(Option[Alignment], X)], ouyTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[Alignment], Y)]): GenericGenomicDataset[(Option[Alignment], X), (Option[Alignment], Y)]
Performs a broadcast right outer join between this genomic dataset and another genomic dataset.
Performs a broadcast right outer join between this genomic dataset and another genomic dataset.
In a broadcast join, the left genomic dataset (this genomic dataset) is collected to the driver, and broadcast to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is a right outer join, all values in the left genomic dataset that do not overlap a value from the right genomic dataset are dropped. If a value from the right genomic dataset does not overlap any values in the left genomic dataset, it will be paired with a
None
in the product of the join.- genomicDataset
The right genomic dataset in the join.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the right genomic dataset that did not overlap a key in the left genomic dataset.
- Definition Classes
- GenomicDataset
- See also
rightOuterBroadcastRegionJoin
-
def
rightOuterBroadcastRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[Alignment], xTag: ClassTag[X], otxTag: ClassTag[(Option[Alignment], X)], ouyTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[Alignment], Y)]): GenericGenomicDataset[(Option[Alignment], X), (Option[Alignment], Y)]
Performs a broadcast right outer join between this genomic dataset and another genomic dataset.
Performs a broadcast right outer join between this genomic dataset and another genomic dataset.
In a broadcast join, the left genomic dataset (this genomic dataset) is collected to the driver, and broadcast to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is a right outer join, all values in the left genomic dataset that do not overlap a value from the right genomic dataset are dropped. If a value from the right genomic dataset does not overlap any values in the left genomic dataset, it will be paired with a
None
in the product of the join.- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the right genomic dataset that did not overlap a key in the left genomic dataset.
- Definition Classes
- GenomicDataset
- See also
rightOuterBroadcastRegionJoin
-
def
rightOuterBroadcastRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Option[Alignment], X), (Option[Alignment], Y)]
(Java-specific) Performs a broadcast right outer join between this genomic dataset and another genomic dataset.
(Java-specific) Performs a broadcast right outer join between this genomic dataset and another genomic dataset.
In a broadcast join, the left genomic dataset (this genomic dataset) is collected to the driver, and broadcast to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is a right outer join, all values in the left genomic dataset that do not overlap a value from the right genomic dataset are dropped. If a value from the right genomic dataset does not overlap any values in the left genomic dataset, it will be paired with a
None
in the product of the join.- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the right genomic dataset that did not overlap a key in the left genomic dataset.
- Definition Classes
- GenomicDataset
-
def
rightOuterBroadcastRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Option[Alignment], X), (Option[Alignment], Y)]
(R-specific) Performs a broadcast right outer join between this genomic dataset and another genomic dataset.
(R-specific) Performs a broadcast right outer join between this genomic dataset and another genomic dataset.
In a broadcast join, the left genomic dataset (this genomic dataset) is collected to the driver, and broadcast to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is a right outer join, all values in the left genomic dataset that do not overlap a value from the right genomic dataset are dropped. If a value from the right genomic dataset does not overlap any values in the left genomic dataset, it will be paired with a
None
in the product of the join.- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the right genomic dataset that did not overlap a key in the left genomic dataset.
- Definition Classes
- GenomicDataset
-
def
rightOuterBroadcastRegionJoinAgainst[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](broadcast: GenomicBroadcast[X, Y, Z])(implicit tTag: ClassTag[Alignment], xTag: ClassTag[X], oyuTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[Y], Alignment)]): GenericGenomicDataset[(Option[X], Alignment), (Option[Y], Alignment)]
Performs a broadcast right outer join between this genomic dataset and data that has been broadcast.
Performs a broadcast right outer join between this genomic dataset and data that has been broadcast.
In a broadcast join, the left side of the join (broadcastTree) is broadcast to to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is a right outer join, all values in the left table that do not overlap a value from the right genomic dataset are dropped. If a value from the right genomic dataset does not overlap any values in the left table, it will be paired with a
None
in the product of the join. As compared to broadcastRegionJoin, this function allows the broadcast object to be reused across multiple joins.- broadcast
The data on the left side of the join.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space.
- Definition Classes
- GenomicDataset
- Note
This function differs from other region joins as it treats the calling genomic dataset as the right side of the join, and not the left.
- See also
rightOuterBroadcastRegionJoin
-
def
rightOuterBroadcastRegionJoinAgainstAndGroupByRight[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](broadcast: GenomicBroadcast[X, Y, Z])(implicit tTag: ClassTag[Alignment], xTag: ClassTag[X], syuTag: scala.reflect.api.JavaUniverse.TypeTag[(Seq[Y], Alignment)]): GenericGenomicDataset[(Iterable[X], Alignment), (Seq[Y], Alignment)]
Performs a broadcast right outer join between this genomic dataset and another genomic dataset.
Performs a broadcast right outer join between this genomic dataset and another genomic dataset.
In a broadcast join, the left side of the join (broadcastTree) is broadcast to to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is a right outer join, all values in the left table that do not overlap a value from the right genomic dataset are dropped. If a value from the right genomic dataset does not overlap any values in the left table, it will be paired with a
None
in the product of the join. As compared to broadcastRegionJoin, this function allows the broadcast object to be reused across multiple joins.- broadcast
The data on the left side of the join.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space.
- Definition Classes
- GenomicDataset
- Note
This function differs from other region joins as it treats the calling genomic dataset as the right side of the join, and not the left.
- See also
rightOuterBroadcastRegionJoinAndGroupByRight
-
def
rightOuterBroadcastRegionJoinAndGroupByRight[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[Alignment], xTag: ClassTag[X], itxTag: ClassTag[(Iterable[Alignment], X)], iuyTag: scala.reflect.api.JavaUniverse.TypeTag[(Seq[Alignment], Y)]): GenericGenomicDataset[(Iterable[Alignment], X), (Seq[Alignment], Y)]
Performs a broadcast right outer join between this genomic dataset and another genomic dataset.
Performs a broadcast right outer join between this genomic dataset and another genomic dataset.
In a broadcast join, the left side of the join (broadcastTree) is broadcast to to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is a right outer join, all values in the left genomic dataset that do not overlap a value from the right genomic dataset are dropped. If a value from the right genomic dataset does not overlap any values in the left genomic dataset, it will be paired with a
None
in the product of the join.- genomicDataset
The right genomic dataset in the join.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the right genomic dataset that did not overlap a key in the left genomic dataset.
- Definition Classes
- GenomicDataset
- See also
rightOuterBroadcastRegionJoinAgainstAndGroupByRight
-
def
rightOuterBroadcastRegionJoinAndGroupByRight[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[Alignment], xTag: ClassTag[X], itxTag: ClassTag[(Iterable[Alignment], X)], iuyTag: scala.reflect.api.JavaUniverse.TypeTag[(Seq[Alignment], Y)]): GenericGenomicDataset[(Iterable[Alignment], X), (Seq[Alignment], Y)]
Performs a broadcast right outer join between this genomic dataset and another genomic dataset.
Performs a broadcast right outer join between this genomic dataset and another genomic dataset.
In a broadcast join, the left side of the join (broadcastTree) is broadcast to to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is a right outer join, all values in the left genomic dataset that do not overlap a value from the right genomic dataset are dropped. If a value from the right genomic dataset does not overlap any values in the left genomic dataset, it will be paired with a
None
in the product of the join.- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the right genomic dataset that did not overlap a key in the left genomic dataset.
- Definition Classes
- GenomicDataset
- See also
rightOuterBroadcastRegionJoinAgainstAndGroupByRight
-
def
rightOuterBroadcastRegionJoinAndGroupByRight[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Iterable[Alignment], X), (Seq[Alignment], Y)]
(Java-specific) Performs a broadcast right outer join between this genomic dataset and another genomic dataset.
(Java-specific) Performs a broadcast right outer join between this genomic dataset and another genomic dataset.
In a broadcast join, the left side of the join (broadcastTree) is broadcast to to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is a right outer join, all values in the left genomic dataset that do not overlap a value from the right genomic dataset are dropped. If a value from the right genomic dataset does not overlap any values in the left genomic dataset, it will be paired with a
None
in the product of the join.- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the right genomic dataset that did not overlap a key in the left genomic dataset.
- Definition Classes
- GenomicDataset
- See also
rightOuterBroadcastRegionJoinAgainstAndGroupByRight
-
def
rightOuterBroadcastRegionJoinAndGroupByRight[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Iterable[Alignment], X), (Seq[Alignment], Y)]
(R-specific) Performs a broadcast right outer join between this genomic dataset and another genomic dataset.
(R-specific) Performs a broadcast right outer join between this genomic dataset and another genomic dataset.
In a broadcast join, the left side of the join (broadcastTree) is broadcast to to all the nodes in the cluster. The key equality function used for this join is the reference region overlap function. Since this is a right outer join, all values in the left genomic dataset that do not overlap a value from the right genomic dataset are dropped. If a value from the right genomic dataset does not overlap any values in the left genomic dataset, it will be paired with a
None
in the product of the join.- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the right genomic dataset that did not overlap a key in the left genomic dataset.
- Definition Classes
- GenomicDataset
- See also
rightOuterBroadcastRegionJoinAgainstAndGroupByRight
-
def
rightOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[Alignment], xTag: ClassTag[X], otxTag: ClassTag[(Option[Alignment], X)], ouyTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[Alignment], Y)]): GenericGenomicDataset[(Option[Alignment], X), (Option[Alignment], Y)]
Performs a sort-merge right outer join between this genomic dataset and another genomic dataset.
Performs a sort-merge right outer join between this genomic dataset and another genomic dataset.
In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is a right outer join, all values in the left genomic dataset that do not overlap a value from the right genomic dataset are dropped. If a value from the right genomic dataset does not overlap any values in the left genomic dataset, it will be paired with a
None
in the product of the join.- genomicDataset
The right genomic dataset in the join.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the right genomic dataset that did not overlap a key in the left genomic dataset.
- Definition Classes
- GenomicDataset
-
def
rightOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[Alignment], xTag: ClassTag[X], otxTag: ClassTag[(Option[Alignment], X)], ouyTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[Alignment], Y)]): GenericGenomicDataset[(Option[Alignment], X), (Option[Alignment], Y)]
Performs a sort-merge right outer join between this genomic dataset and another genomic dataset.
Performs a sort-merge right outer join between this genomic dataset and another genomic dataset.
In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is a right outer join, all values in the left genomic dataset that do not overlap a value from the right genomic dataset are dropped. If a value from the right genomic dataset does not overlap any values in the left genomic dataset, it will be paired with a
None
in the product of the join.- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the right genomic dataset that did not overlap a key in the left genomic dataset.
- Definition Classes
- GenomicDataset
-
def
rightOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Option[Alignment], X), (Option[Alignment], Y)]
(Java-specific) Performs a sort-merge right outer join between this genomic dataset and another genomic dataset.
(Java-specific) Performs a sort-merge right outer join between this genomic dataset and another genomic dataset.
In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is a right outer join, all values in the left genomic dataset that do not overlap a value from the right genomic dataset are dropped. If a value from the right genomic dataset does not overlap any values in the left genomic dataset, it will be paired with a
None
in the product of the join.- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the right genomic dataset that did not overlap a key in the left genomic dataset.
- Definition Classes
- GenomicDataset
-
def
rightOuterShuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Option[Alignment], X), (Option[Alignment], Y)]
(R-specific) Performs a sort-merge right outer join between this genomic dataset and another genomic dataset.
(R-specific) Performs a sort-merge right outer join between this genomic dataset and another genomic dataset.
In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is a right outer join, all values in the left genomic dataset that do not overlap a value from the right genomic dataset are dropped. If a value from the right genomic dataset does not overlap any values in the left genomic dataset, it will be paired with a
None
in the product of the join.- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, and all keys from the right genomic dataset that did not overlap a key in the left genomic dataset.
- Definition Classes
- GenomicDataset
-
def
rightOuterShuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[Alignment], xTag: ClassTag[X], otixTag: ClassTag[(Option[Alignment], Iterable[X])], otsyTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[Alignment], Seq[Y])]): GenericGenomicDataset[(Option[Alignment], Iterable[X]), (Option[Alignment], Seq[Y])]
Performs a sort-merge right outer join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value, if not null.
Performs a sort-merge right outer join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value, if not null.
In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. In the same operation, we group all values by the left item in the genomic dataset. Since this is a right outer join, all values from the right genomic dataset who did not overlap a value from the left genomic dataset are placed into a length-1 Iterable with a
None
key.- genomicDataset
The right genomic dataset in the join.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, grouped together by the value they overlapped in the left genomic dataset, and all values from the right genomic dataset that did not overlap an item in the left genomic dataset.
- Definition Classes
- GenomicDataset
-
def
rightOuterShuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[Alignment], xTag: ClassTag[X], otixTag: ClassTag[(Option[Alignment], Iterable[X])], ousyTag: scala.reflect.api.JavaUniverse.TypeTag[(Option[Alignment], Seq[Y])]): GenericGenomicDataset[(Option[Alignment], Iterable[X]), (Option[Alignment], Seq[Y])]
Performs a sort-merge right outer join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value, if not null.
Performs a sort-merge right outer join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value, if not null.
In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. In the same operation, we group all values by the left item in the genomic dataset. Since this is a right outer join, all values from the right genomic dataset who did not overlap a value from the left genomic dataset are placed into a length-1 Iterable with a
None
key.- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, grouped together by the value they overlapped in the left genomic dataset, and all values from the right genomic dataset that did not overlap an item in the left genomic dataset.
- Definition Classes
- GenomicDataset
-
def
rightOuterShuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Option[Alignment], Iterable[X]), (Option[Alignment], Seq[Y])]
(Java-specific) Performs a sort-merge right outer join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value, if not null.
(Java-specific) Performs a sort-merge right outer join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value, if not null.
In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. In the same operation, we group all values by the left item in the genomic dataset. Since this is a right outer join, all values from the right genomic dataset who did not overlap a value from the left genomic dataset are placed into a length-1 Iterable with a
None
key.- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, grouped together by the value they overlapped in the left genomic dataset, and all values from the right genomic dataset that did not overlap an item in the left genomic dataset.
- Definition Classes
- GenomicDataset
-
def
rightOuterShuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Option[Alignment], Iterable[X]), (Option[Alignment], Seq[Y])]
(R-specific) Performs a sort-merge right outer join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value, if not null.
(R-specific) Performs a sort-merge right outer join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value, if not null.
In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. In the same operation, we group all values by the left item in the genomic dataset. Since this is a right outer join, all values from the right genomic dataset who did not overlap a value from the left genomic dataset are placed into a length-1 Iterable with a
None
key.- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, grouped together by the value they overlapped in the left genomic dataset, and all values from the right genomic dataset that did not overlap an item in the left genomic dataset.
- Definition Classes
- GenomicDataset
-
def
save(filePath: String, isSorted: Boolean): Boolean
Saves this genomic dataset to disk, with the type identified by the extension.
Saves this genomic dataset to disk, with the type identified by the extension.
- filePath
Path to save the file at.
- isSorted
Whether the file is sorted or not.
- returns
Returns true if saving succeeded.
- Definition Classes
- AlignmentDataset
-
def
save(args: ADAMSaveAnyArgs, isSorted: Boolean = false): Boolean
Saves Alignments as a directory of Parquet files or as SAM/BAM.
Saves Alignments as a directory of Parquet files or as SAM/BAM.
This method infers the output format from the file extension. Filenames ending in .sam/.bam are saved as SAM/BAM, and all other files are saved as Parquet.
- args
Save configuration arguments.
- isSorted
If the output is sorted, this will modify the SAM/BAM header.
- returns
Returns true if saving succeeded.
- Definition Classes
- AlignmentDataset
-
def
saveAsFastq(fileName: String, fileName2Opt: Option[String] = None, writeOriginalQualityScores: Boolean = false, sort: Boolean = false, asSingleFile: Boolean = false, disableFastConcat: Boolean = false, validationStringency: ValidationStringency = ValidationStringency.LENIENT, persistLevel: Option[StorageLevel] = None): Unit
Saves reads in FASTQ format.
Saves reads in FASTQ format.
- fileName
Path to save files at.
- fileName2Opt
Optional second path for saving files. If set, two files will be saved.
- writeOriginalQualityScores
If true, writes out reads with the base quality scores from the original quality scores (SAM "OQ") field. If false, writes out reads with the quality scores from the qualityScores field. Default is false.
- sort
Whether to sort the FASTQ files by read name or not. Defaults to false. Sorting the output will recover pair order, if desired.
- asSingleFile
By default (false), writes file to disk as shards with one shard per partition. If true, we save the file to disk as a single file by merging the shards.
- disableFastConcat
If asSingleFile is true, disables the use of the parallel file merging engine.
- validationStringency
Iff strict, throw an exception if any read in this genomic dataset is not accompanied by its mate.
- persistLevel
An optional persistance level to set. If this level is set, then reads will be cached (at the given persistance) level between passes.
- Definition Classes
- AlignmentDataset
-
def
saveAsFastq(fileName: String, writeOriginalQualityScores: Boolean, sort: Boolean, asSingleFile: Boolean, disableFastConcat: Boolean, validationStringency: ValidationStringency): Unit
(Java-specific) Saves reads in FASTQ format.
(Java-specific) Saves reads in FASTQ format.
- fileName
Path to save files at.
- writeOriginalQualityScores
If true, writes out reads with the base quality scores from the original quality scores (SAM "OQ") field. If false, writes out reads with the quality scores from the qualityScores field. Default is false.
- sort
Whether to sort the FASTQ files by read name or not. Defaults to false. Sorting the output will recover pair order, if desired.
- asSingleFile
If false, writes file to disk as shards with one shard per partition. If true, we save the file to disk as a single file by merging the shards.
- disableFastConcat
If asSingleFile is true, disables the use of the parallel file merging engine.
- validationStringency
Iff strict, throw an exception if any read in this genomic dataset is not accompanied by its mate.
- Definition Classes
- AlignmentDataset
-
def
saveAsPairedFastq(fileName1: String, fileName2: String, writeOriginalQualityScores: Boolean = false, asSingleFile: Boolean = false, disableFastConcat: Boolean = false, validationStringency: ValidationStringency = ValidationStringency.LENIENT, persistLevel: Option[StorageLevel] = None): Unit
Saves these Alignments to two FASTQ files.
Saves these Alignments to two FASTQ files.
The files are one for the first mate in each pair, and the other for the second mate in the pair.
- fileName1
Path at which to save a FASTQ file containing the first mate of each pair.
- fileName2
Path at which to save a FASTQ file containing the second mate of each pair.
- writeOriginalQualityScores
If true, writes out reads with the base quality scores from the original quality scores (SAM "OQ") field. If false, writes out reads with the quality scores from the qualityScores field. Default is false.
- asSingleFile
By default (false), writes file to disk as shards with one shard per partition. If true, we save the file to disk as a single file by merging the shards.
- disableFastConcat
If asSingleFile is true, disables the use of the parallel file merging engine.
- validationStringency
Iff strict, throw an exception if any read in this genomic dataset is not accompanied by its mate.
- persistLevel
An optional persistance level to set. If this level is set, then reads will be cached (at the given persistance) level between passes.
- Definition Classes
- AlignmentDataset
-
def
saveAsPairedFastq(fileName1: String, fileName2: String, writeOriginalQualityScores: Boolean, asSingleFile: Boolean, disableFastConcat: Boolean, validationStringency: ValidationStringency, persistLevel: StorageLevel): Unit
(Java-specific) Saves these Alignments to two FASTQ files.
(Java-specific) Saves these Alignments to two FASTQ files.
The files are one for the first mate in each pair, and the other for the second mate in the pair.
- fileName1
Path at which to save a FASTQ file containing the first mate of each pair.
- fileName2
Path at which to save a FASTQ file containing the second mate of each pair.
- writeOriginalQualityScores
If true, writes out reads with the base quality scores from the original quality scores (SAM "OQ") field. If false, writes out reads with the quality scores from the qualityScores field. Default is false.
- asSingleFile
If false, writes file to disk as shards with one shard per partition. If true, we save the file to disk as a single file by merging the shards.
- disableFastConcat
If asSingleFile is true, disables the use of the parallel file merging engine.
- validationStringency
Iff strict, throw an exception if any read in this genomic dataset is not accompanied by its mate.
- persistLevel
The persistence level to cache reads at between passes.
- Definition Classes
- AlignmentDataset
-
def
saveAsParquet(filePath: String, blockSize: Int = 128 * 1024 * 1024, pageSize: Int = 1 * 1024 * 1024, compressionCodec: CompressionCodecName = CompressionCodecName.GZIP, disableDictionaryEncoding: Boolean = false): Unit
Saves this genomic dataset to disk as a Parquet file.
Saves this genomic dataset to disk as a Parquet file.
- blockSize
Size per block.
- pageSize
Size per page.
- compressionCodec
Name of the compression codec to use.
- disableDictionaryEncoding
Whether or not to disable bit-packing. Default is false.
- Definition Classes
- DatasetBoundAlignmentDataset → AvroGenomicDataset → GenomicDataset
-
def
saveAsParquet(pathName: String): Unit
Saves this genomic dataset to disk as a Parquet file.
Saves this genomic dataset to disk as a Parquet file.
- pathName
Path to save the file at.
- Definition Classes
- AvroGenomicDataset
-
def
saveAsParquet(pathName: String, blockSize: Integer, pageSize: Integer, compressionCodec: CompressionCodecName, disableDictionaryEncoding: Boolean): Unit
(Java-specific) Saves this genomic dataset to disk as a Parquet file.
(Java-specific) Saves this genomic dataset to disk as a Parquet file.
- pathName
Path to save the file at.
- blockSize
The size in bytes of blocks to write.
- pageSize
The size in bytes of pages to write.
- compressionCodec
The compression codec to apply to pages.
- disableDictionaryEncoding
If false, dictionary encoding is used. If true, delta encoding is used.
- Definition Classes
- AvroGenomicDataset
-
def
saveAsParquet(args: SaveArgs): Unit
Saves a genomic dataset to Parquet.
Saves a genomic dataset to Parquet.
- args
The output format configuration to use when saving the data.
- Definition Classes
- GenomicDataset
-
def
saveAsPartitionedParquet(pathName: String, compressionCodec: CompressionCodecName = CompressionCodecName.GZIP, partitionSize: Int = 1000000): Unit
Saves this RDD to disk in range binned partitioned Parquet format.
Saves this RDD to disk in range binned partitioned Parquet format.
- pathName
The path to save the partitioned Parquet file to.
- compressionCodec
Name of the compression codec to use.
- partitionSize
Size of partitions used when writing Parquet, in base pairs (bp). Defaults to 1,000,000 bp.
- Definition Classes
- GenomicDataset
-
def
saveAsSam(filePath: String, asType: SAMFormat, asSingleFile: Boolean, isSorted: Boolean): Unit
Saves this genomic dataset to disk as a SAM/BAM/CRAM file.
Saves this genomic dataset to disk as a SAM/BAM/CRAM file.
- filePath
Path to save the file at.
- asType
The SAMFormat to save as. If left null, we will infer the format from the file extension.
- asSingleFile
If true, saves output as a single file.
- isSorted
If the output is sorted, this will modify the header.
- Definition Classes
- AlignmentDataset
-
def
saveAsSam(filePath: String, asType: Option[SAMFormat], asSingleFile: Boolean, sortOrder: SortOrder, deferMerging: Boolean, disableFastConcat: Boolean): Unit
- Definition Classes
- AlignmentDataset
-
def
saveAsSam(filePath: String, asType: Option[SAMFormat] = None, asSingleFile: Boolean = false, isSorted: Boolean = false, deferMerging: Boolean = false, disableFastConcat: Boolean = false): Unit
Saves this genomic dataset of ADAM read data into the SAM/BAM format.
Saves this genomic dataset of ADAM read data into the SAM/BAM format.
- filePath
Path to save files to.
- asType
Selects whether to save as SAM, BAM, or CRAM. The default value is None, which means the file type is inferred from the extension.
- asSingleFile
If true, saves output as a single file.
- isSorted
If the output is sorted, this will modify the header.
- deferMerging
If true and asSingleFile is true, we will save the output shards as a headerless file, but we will not merge the shards.
- disableFastConcat
If asSingleFile is true and deferMerging is false, disables the use of the parallel file merging engine.
- Definition Classes
- AlignmentDataset
-
def
saveAsSamString(): String
Converts this genomic dataset into the SAM spec string it represents.
Converts this genomic dataset into the SAM spec string it represents.
This method converts a genomic dataset of Alignments back to an RDD of SAMRecordWritables and a SAMFileHeader, and then maps this RDD into a string on the driver that represents this file in SAM.
- returns
A string on the driver representing this genomic dataset of reads in SAM format.
- Definition Classes
- AlignmentDataset
-
def
saveAvro[U <: SpecificRecordBase](pathName: String, sc: SparkContext, schema: Schema, avro: Seq[U])(implicit tUag: ClassTag[U]): Unit
Saves Avro data to a Hadoop file system.
Saves Avro data to a Hadoop file system.
This method uses a SparkContext to identify our underlying file system, which we then save to.
Frustratingly enough, although all records generated by the Avro IDL compiler have a static SCHEMA$ field, this field does not belong to the SpecificRecordBase abstract class, or the SpecificRecord interface. As such, we must force the user to pass in the schema.
- U
The type of the specific record we are saving.
- pathName
Path to save records to.
- sc
SparkContext used for identifying underlying file system.
- schema
Schema of records we are saving.
- avro
Seq of records we are saving.
- Attributes
- protected
- Definition Classes
- GenomicDataset
-
def
saveMetadata(pathName: String): Unit
Called in saveAsParquet after saving genomic dataset to Parquet to save metadata.
Called in saveAsParquet after saving genomic dataset to Parquet to save metadata.
Writes any necessary metadata to disk. If not overridden, writes the sequence dictionary to disk as Avro.
- pathName
The filepath to the file where we will save the Metadata.
- Attributes
- protected
- Definition Classes
- AvroReadGroupGenomicDataset → AvroGenomicDataset → GenomicDataset
-
def
savePartitionMap(pathName: String): Unit
Save the partition map to disk.
Save the partition map to disk. This is done by adding the partition map to the schema.
- pathName
The filepath where we will save the partition map.
- Attributes
- protected
- Definition Classes
- AvroGenomicDataset
-
def
saveProcessingSteps(pathName: String): Unit
Save the processing steps to disk.
Save the processing steps to disk.
- pathName
The path to save processing steps to.
- Attributes
- protected
- Definition Classes
- AvroReadGroupGenomicDataset
-
def
saveRddAsParquet(pathName: String, blockSize: Int = 128 * 1024 * 1024, pageSize: Int = 1 * 1024 * 1024, compressionCodec: CompressionCodecName = CompressionCodecName.GZIP, disableDictionaryEncoding: Boolean = false, optSchema: Option[Schema] = None): Unit
Saves a genomic dataset of Avro data to Parquet.
Saves a genomic dataset of Avro data to Parquet.
- pathName
The path to save the file to.
- blockSize
The size in bytes of blocks to write. Defaults to 128 * 1024 * 1024.
- pageSize
The size in bytes of pages to write. Defaults to 1 * 1024 * 1024.
- compressionCodec
The compression codec to apply to pages. Defaults to CompressionCodecName.GZIP.
- disableDictionaryEncoding
If false, dictionary encoding is used. If true, delta encoding is used. Defaults to false.
- optSchema
The optional schema to set. Defaults to None.
- Attributes
- protected
- Definition Classes
- AvroGenomicDataset
-
def
saveRddAsParquet(args: SaveArgs): Unit
- Attributes
- protected
- Definition Classes
- AvroGenomicDataset
-
def
saveReadGroups(pathName: String): Unit
Save the read groups to disk.
Save the read groups to disk.
- pathName
The path to save read groups to.
- Attributes
- protected
- Definition Classes
- AvroReadGroupGenomicDataset
-
def
saveSequences(pathName: String): Unit
Save the sequence dictionary to disk.
Save the sequence dictionary to disk.
- pathName
The path to save the sequence dictionary to.
- Attributes
- protected
- Definition Classes
- GenomicDataset
-
val
sequences: SequenceDictionary
The sequence dictionary describing the reference assembly this dataset is aligned to.
The sequence dictionary describing the reference assembly this dataset is aligned to.
- Definition Classes
- DatasetBoundAlignmentDataset → GenomicDataset
-
def
shuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[Alignment], xTag: ClassTag[X], txTag: ClassTag[(Alignment, X)], uyTag: scala.reflect.api.JavaUniverse.TypeTag[(Alignment, Y)]): GenericGenomicDataset[(Alignment, X), (Alignment, Y)]
Performs a sort-merge inner join between this genomic dataset and another genomic dataset.
Performs a sort-merge inner join between this genomic dataset and another genomic dataset.
In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is an inner join, all values who do not overlap a value from the other genomic dataset are dropped.
- genomicDataset
The right genomic dataset in the join.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space.
- Definition Classes
- GenomicDataset
-
def
shuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[Alignment], xTag: ClassTag[X], txTag: ClassTag[(Alignment, X)], uyTag: scala.reflect.api.JavaUniverse.TypeTag[(Alignment, Y)]): GenericGenomicDataset[(Alignment, X), (Alignment, Y)]
Performs a sort-merge inner join between this genomic dataset and another genomic dataset.
Performs a sort-merge inner join between this genomic dataset and another genomic dataset.
In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is an inner join, all values who do not overlap a value from the other genomic dataset are dropped.
- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space.
- Definition Classes
- GenomicDataset
-
def
shuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Alignment, X), (Alignment, Y)]
(Java-specific) Performs a sort-merge inner join between this genomic dataset and another genomic dataset.
(Java-specific) Performs a sort-merge inner join between this genomic dataset and another genomic dataset.
In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is an inner join, all values who do not overlap a value from the other genomic dataset are dropped.
- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space.
- Definition Classes
- GenomicDataset
-
def
shuffleRegionJoin[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Alignment, X), (Alignment, Y)]
(R-specific) Performs a sort-merge inner join between this genomic dataset and another genomic dataset.
(R-specific) Performs a sort-merge inner join between this genomic dataset and another genomic dataset.
In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is an inner join, all values who do not overlap a value from the other genomic dataset are dropped.
- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space.
- Definition Classes
- GenomicDataset
-
def
shuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z])(implicit tTag: ClassTag[Alignment], xTag: ClassTag[X], tixTag: ClassTag[(Alignment, Iterable[X])], uiyTag: scala.reflect.api.JavaUniverse.TypeTag[(Alignment, Seq[Y])]): GenericGenomicDataset[(Alignment, Iterable[X]), (Alignment, Seq[Y])]
Performs a sort-merge inner join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value.
Performs a sort-merge inner join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value.
In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is an inner join, all values who do not overlap a value from the other genomic dataset are dropped. In the same operation, we group all values by the left item in the genomic dataset.
- genomicDataset
The right genomic dataset in the join.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, grouped together by the value they overlapped in the left genomic dataset.
- Definition Classes
- GenomicDataset
-
def
shuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Long)(implicit tTag: ClassTag[Alignment], xTag: ClassTag[X], tixTag: ClassTag[(Alignment, Iterable[X])], uiyTag: scala.reflect.api.JavaUniverse.TypeTag[(Alignment, Seq[Y])]): GenericGenomicDataset[(Alignment, Iterable[X]), (Alignment, Seq[Y])]
Performs a sort-merge inner join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value.
Performs a sort-merge inner join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value.
In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. Since this is an inner join, all values who do not overlap a value from the other genomic dataset are dropped. In the same operation, we group all values by the left item in the genomic dataset.
- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, grouped together by the value they overlapped in the left genomic dataset.
- Definition Classes
- GenomicDataset
-
def
shuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Integer): GenericGenomicDataset[(Alignment, Iterable[X]), (Alignment, Seq[Y])]
(Java-specific) Performs a sort-merge inner join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value.
(Java-specific) Performs a sort-merge inner join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value.
In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. In the same operation, we group all values by the left item in the genomic dataset.
- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, grouped together by the value they overlapped in the left genomic dataset.
- Definition Classes
- GenomicDataset
-
def
shuffleRegionJoinAndGroupByLeft[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](genomicDataset: GenomicDataset[X, Y, Z], flankSize: Double): GenericGenomicDataset[(Alignment, Iterable[X]), (Alignment, Seq[Y])]
(R-specific) Performs a sort-merge inner join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value.
(R-specific) Performs a sort-merge inner join between this genomic dataset and another genomic dataset, followed by a groupBy on the left value.
In a sort-merge join, both genomic datasets are co-partitioned and sorted. The partitions are then zipped, and we do a merge join on each partition. The key equality function used for this join is the reference region overlap function. In the same operation, we group all values by the left item in the genomic dataset.
- genomicDataset
The right genomic dataset in the join.
- flankSize
Sets a flankSize for the distance between elements to be joined. If set to 0, an overlap is required to join two elements.
- returns
Returns a new genomic dataset containing all pairs of keys that overlapped in the genomic coordinate space, grouped together by the value they overlapped in the left genomic dataset.
- Definition Classes
- GenomicDataset
-
def
sort(partitions: Int = rdd.partitions.length, stringency: ValidationStringency = ValidationStringency.STRICT)(implicit tTag: ClassTag[Alignment]): AlignmentDataset
Sorts our genome aligned data by reference positions, with references ordered by index.
Sorts our genome aligned data by reference positions, with references ordered by index.
- partitions
The number of partitions for the new genomic dataset.
- stringency
The level of ValidationStringency to enforce.
- returns
Returns a new genomic dataset containing sorted data.
- Definition Classes
- GenomicDataset
- Note
Uses ValidationStringency to handle unaligned or where objects align to multiple positions.
- See also
sortLexicographically
-
def
sort(): AlignmentDataset
Sorts our genome aligned data by reference positions, with references ordered by index.
Sorts our genome aligned data by reference positions, with references ordered by index.
- returns
Returns a new genomic dataset containing sorted data.
- Definition Classes
- GenomicDataset
- See also
sortLexicographically
-
def
sortByReadName(): AlignmentDataset
Sorts our alignments by read name.
Sorts our alignments by read name.
- returns
Returns a new genomic dataset containing sorted alignments.
- Definition Classes
- AlignmentDataset
-
def
sortByReferencePosition(): AlignmentDataset
Sorts our alignments by reference position, with references ordered by name.
Sorts our alignments by reference position, with references ordered by name.
Sorts alignments by the location where the reads are aligned. Unaligned reads are put at the end and sorted by read name. References are ordered lexicographically.
- returns
Returns a new genomic dataset containing sorted alignments.
- Definition Classes
- AlignmentDataset
- See also
sortByReferencePositionAndIndex
-
def
sortByReferencePositionAndIndex(): AlignmentDataset
Sorts our alignments by reference position, with references ordered by index.
Sorts our alignments by reference position, with references ordered by index.
Sorts alignments by the location where the reads are aligned. Unaligned reads are put at the end and sorted by read name. References are ordered by index that they are ordered in the SequenceDictionary.
- returns
Returns a new genomic dataset containing sorted alignments.
- Definition Classes
- AlignmentDataset
- See also
sortByReferencePosition
-
def
sortLexicographically(partitions: Int = rdd.partitions.length, storePartitionMap: Boolean = false, storageLevel: StorageLevel = StorageLevel.MEMORY_ONLY, stringency: ValidationStringency = ValidationStringency.STRICT)(implicit tTag: ClassTag[Alignment]): AlignmentDataset
Sorts our genome aligned data by reference positions, with references ordered lexicographically.
Sorts our genome aligned data by reference positions, with references ordered lexicographically.
- partitions
The number of partitions for the new genomic dataset.
- storePartitionMap
A Boolean flag to determine whether to store the partition bounds from the resulting genomic dataset.
- storageLevel
The level at which to persist the resulting genomic dataset.
- stringency
The level of ValidationStringency to enforce.
- returns
Returns a new genomic dataset containing sorted data.
- Definition Classes
- GenomicDataset
- Note
Uses ValidationStringency to handle data that is unaligned or where objects align to multiple positions.
- See also
sort
-
def
sortLexicographically(): AlignmentDataset
Sorts our genome aligned data by reference positions, with references ordered lexicographically.
Sorts our genome aligned data by reference positions, with references ordered lexicographically.
- returns
Returns a new genomic dataset containing sorted data.
- Definition Classes
- GenomicDataset
- See also
sort
-
lazy val
spark: SparkSession
- Definition Classes
- GenomicDataset
- Annotations
- @transient()
-
final
def
synchronized[T0](arg0: ⇒ T0): T0
- Definition Classes
- AnyRef
-
def
toCoverage(): CoverageDataset
Converts this dataset of alignments into a corresponding CoverageDataset.
Converts this dataset of alignments into a corresponding CoverageDataset.
- returns
CoverageDataset containing mapped genomic dataset of Coverage.
- Definition Classes
- AlignmentDataset
-
def
toDF(): DataFrame
- returns
These data as a Spark SQL DataFrame.
- Definition Classes
- GenomicDataset
-
def
toFragments(): FragmentDataset
Convert this set of reads into fragments.
Convert this set of reads into fragments.
- returns
Returns a FragmentDataset where all reads have been grouped together by the original sequence fragment they come from.
- Definition Classes
- AlignmentDataset
-
def
toReads(): ReadDataset
Convert this genomic dataset of alignments to reads.
Convert this genomic dataset of alignments to reads.
- returns
Return this genomic dataset of alignments converted to a ReadDataset.
- Definition Classes
- AlignmentDataset
-
def
toString(): String
- Definition Classes
- AvroReadGroupGenomicDataset → GenomicDataset → AnyRef → Any
-
def
trace(mkr: Marker, msg: ⇒ Any, t: ⇒ Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
trace(msg: ⇒ Any, t: ⇒ Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
trace(msg: ⇒ Any): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
transform(tFn: Function[JavaRDD[Alignment], JavaRDD[Alignment]]): AlignmentDataset
(Java-specific) Applies a function that transforms the underlying RDD into a new RDD.
(Java-specific) Applies a function that transforms the underlying RDD into a new RDD.
- tFn
A function that transforms the underlying RDD.
- returns
A new genomic dataset where the RDD of genomic data has been replaced, but the metadata (sequence dictionary, and etc) are copied without modification.
- Definition Classes
- GenomicDataset
-
def
transform(tFn: (RDD[Alignment]) ⇒ RDD[Alignment]): AlignmentDataset
(Scala-specific) Applies a function that transforms the underlying RDD into a new RDD.
(Scala-specific) Applies a function that transforms the underlying RDD into a new RDD.
- tFn
A function that transforms the underlying RDD.
- returns
A new genomic dataset where the RDD of genomic data has been replaced, but the metadata (sequence dictionary, and etc) are copied without modification.
- Definition Classes
- GenomicDataset
-
def
transformDataFrame(tFn: Function[DataFrame, DataFrame]): AlignmentDataset
(Java-specific) Applies a function that transforms the underlying DataFrame into a new DataFrame using the Spark SQL API.
(Java-specific) Applies a function that transforms the underlying DataFrame into a new DataFrame using the Spark SQL API.
- tFn
A function that transforms the underlying DataFrame as a DataFrame.
- returns
A new genomic dataset where the DataFrame of genomic data has been replaced, but the metadata (sequence dictionary, and etc) are copied without modification.
- Definition Classes
- GenomicDataset
-
def
transformDataFrame(tFn: (DataFrame) ⇒ DataFrame)(implicit uTag: scala.reflect.api.JavaUniverse.TypeTag[Alignment]): AlignmentDataset
(Scala-specific) Applies a function that transforms the underlying DataFrame into a new DataFrame using the Spark SQL API.
(Scala-specific) Applies a function that transforms the underlying DataFrame into a new DataFrame using the Spark SQL API.
- tFn
A function that transforms the underlying data as a DataFrame.
- returns
A new genomic dataset where the DataFrame of genomic data has been replaced, but the metadata (sequence dictionary, and etc) are copied without modification.
- Definition Classes
- GenomicDataset
-
def
transformDataset(tFn: Function[Dataset[Alignment], Dataset[Alignment]]): AlignmentDataset
(Java-specific) Applies a function that transforms the underlying Dataset into a new Dataset using the Spark SQL API.
(Java-specific) Applies a function that transforms the underlying Dataset into a new Dataset using the Spark SQL API.
- tFn
A function that transforms the underlying Dataset as a Dataset.
- returns
A new genomic dataset where the Dataset of genomic data has been replaced, but the metadata (sequence dictionary, and etc) are copied without modification.
- Definition Classes
- DatasetBoundAlignmentDataset → AlignmentDataset → GenomicDataset
-
def
transformDataset(tFn: (Dataset[Alignment]) ⇒ Dataset[Alignment]): AlignmentDataset
(Scala-specific) Applies a function that transforms the underlying Dataset into a new Dataset using the Spark SQL API.
(Scala-specific) Applies a function that transforms the underlying Dataset into a new Dataset using the Spark SQL API.
- tFn
A function that transforms the underlying Dataset as a Dataset.
- returns
A new genomic dataset where the Dataset of genomic data has been replaced, but the metadata (sequence dictionary, and etc) are copied without modification.
- Definition Classes
- DatasetBoundAlignmentDataset → AlignmentDataset → GenomicDataset
-
def
transmute[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](tFn: Function[JavaRDD[Alignment], JavaRDD[X]], convFn: Function2[AlignmentDataset, RDD[X], Z]): Z
(Java-specific) Applies a function that transmutes the underlying RDD into a new RDD of a different type.
(Java-specific) Applies a function that transmutes the underlying RDD into a new RDD of a different type.
- tFn
A function that transforms the underlying RDD.
- convFn
The conversion function used to build the final RDD.
- returns
A new genomid dataset where the RDD of genomic data has been replaced, but the metadata (sequence dictionary, and etc) are copied without modification.
- Definition Classes
- GenomicDataset
-
def
transmute[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](tFn: (RDD[Alignment]) ⇒ RDD[X])(implicit convFn: (AlignmentDataset, RDD[X]) ⇒ Z): Z
(Scala-specific) Applies a function that transmutes the underlying RDD into a new RDD of a different type.
(Scala-specific) Applies a function that transmutes the underlying RDD into a new RDD of a different type.
- tFn
A function that transforms the underlying RDD.
- returns
A new genomic dataset where the RDD of genomic data has been replaced, but the metadata (sequence dictionary, and etc) are copied without modification.
- Definition Classes
- GenomicDataset
-
def
transmuteDataFrame[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](tFn: Function[DataFrame, DataFrame], convFn: GenomicDatasetConversion[Alignment, Alignment, AlignmentDataset, X, Y, Z]): Z
(Java-specific) Applies a function that transmutes the underlying DataFrame into a new DataFrame of a different type.
(Java-specific) Applies a function that transmutes the underlying DataFrame into a new DataFrame of a different type.
- tFn
A function that transforms the underlying DataFrame.
- returns
A new genomic dataset where the DataFrame of genomic data has been replaced, but the metadata (sequence dictionary, and etc) are copied without modification.
- Definition Classes
- GenomicDataset
-
def
transmuteDataFrame[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](tFn: (DataFrame) ⇒ DataFrame)(implicit yTag: scala.reflect.api.JavaUniverse.TypeTag[Y], convFn: (AlignmentDataset, Dataset[Y]) ⇒ Z): Z
(Java-specific) Applies a function that transmutes the underlying DataFrame into a new DataFrame of a different type.
(Java-specific) Applies a function that transmutes the underlying DataFrame into a new DataFrame of a different type.
- tFn
A function that transforms the underlying DataFrame.
- returns
A new genomic dataset where the DataFrame of genomic data has been replaced, but the metadata (sequence dictionary, and etc) are copied without modification.
- Definition Classes
- GenomicDataset
-
def
transmuteDataset[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](tFn: Function[Dataset[Alignment], Dataset[Y]], convFn: GenomicDatasetConversion[Alignment, Alignment, AlignmentDataset, X, Y, Z]): Z
(Java-specific) Applies a function that transmutes the underlying Dataset into a new Dataset of a different type.
(Java-specific) Applies a function that transmutes the underlying Dataset into a new Dataset of a different type.
- tFn
A function that transforms the underlying Dataset.
- returns
A new genomic dataset where the Dataset of genomic data has been replaced, but the metadata (sequence dictionary, and etc) are copied without modification.
- Definition Classes
- GenomicDataset
-
def
transmuteDataset[X, Y <: Product, Z <: GenomicDataset[X, Y, Z]](tFn: (Dataset[Alignment]) ⇒ Dataset[Y])(implicit yTag: scala.reflect.api.JavaUniverse.TypeTag[Y], convFn: (AlignmentDataset, Dataset[Y]) ⇒ Z): Z
(Scala-specific) Applies a function that transmutes the underlying Dataset into a new Dataset of a different type.
(Scala-specific) Applies a function that transmutes the underlying Dataset into a new Dataset of a different type.
- tFn
A function that transforms the underlying Dataset.
- returns
A new genomic dataset where the Dataset of genomic data has been replaced, but the metadata (sequence dictionary, and etc) are copied without modification.
- Definition Classes
- GenomicDataset
-
val
uTag: scala.reflect.api.JavaUniverse.TypeTag[Alignment]
- Definition Classes
- AlignmentDataset → GenomicDataset
-
def
union(datasets: AlignmentDataset*): AlignmentDataset
(Scala-specific) Unions together multiple genomic datasets.
(Scala-specific) Unions together multiple genomic datasets.
- datasets
Genomic datasets to union with this genomic dataset.
- Definition Classes
- AlignmentDataset → GenomicDataset
-
def
union(datasets: List[AlignmentDataset]): AlignmentDataset
(Java-specific) Unions together multiple genomic datasets.
(Java-specific) Unions together multiple genomic datasets.
- datasets
Genomic datasets to union with this genomic dataset.
- Definition Classes
- GenomicDataset
-
def
unpersist(): AlignmentDataset
Unpersists underlying RDD from memory or disk.
Unpersists underlying RDD from memory or disk.
- returns
Uncached GenomicDataset.
- Definition Classes
- DatasetBoundGenomicDataset → GenomicDataset
-
val
unproductFn: (Alignment) ⇒ Alignment
- Attributes
- protected
- Definition Classes
- AlignmentDataset → GenomicDataset
-
final
def
wait(): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... )
-
final
def
wait(arg0: Long, arg1: Int): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... )
-
final
def
wait(arg0: Long): Unit
- Definition Classes
- AnyRef
- Annotations
- @native() @throws( ... )
-
def
warn(mkr: Marker, msg: ⇒ Any, t: ⇒ Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
warn(msg: ⇒ Any, t: ⇒ Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
warn(msg: ⇒ Any): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
writePartitionedParquetFlag(pathName: String, partitionSize: Int): Unit
Save partition size into the partitioned Parquet flag file.
Save partition size into the partitioned Parquet flag file.
- pathName
Path to save the file at.
- partitionSize
Partition bin size, in base pairs, used in Hive-style partitioning.
- Definition Classes
- AvroGenomicDataset → GenomicDataset
-
def
writeTextRdd[T](rdd: RDD[T], outputPath: String, asSingleFile: Boolean, disableFastConcat: Boolean, optHeaderPath: Option[String] = None): Unit
Writes an RDD to disk as text and optionally merges.
Writes an RDD to disk as text and optionally merges.
- rdd
RDD to save.
- outputPath
Output path to save text files to.
- asSingleFile
If true, combines all partition shards.
- disableFastConcat
If asSingleFile is true, disables the use of the parallel file merging engine.
- optHeaderPath
If provided, the header file to include.
- Attributes
- protected
- Definition Classes
- GenomicDataset