org.bdgenomics.adam.rdd

# ADAMContext

#### class ADAMContext extends Serializable with Logging

The ADAMContext provides functions on top of a SparkContext for loading genomic data.

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### Instance Constructors

1. #### new ADAMContext(sc: SparkContext)

   sc

     The SparkContext to wrap.

### Value Members

1. #### final def !=(arg0: AnyRef): Boolean

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2. #### final def !=(arg0: Any): Boolean

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

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     @throws( ... )

8. #### final def eq(arg0: AnyRef): Boolean

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

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

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      @throws( classOf[java.lang.Throwable] )

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

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12. #### def getFiles(path: Path, fs: FileSystem): Array[Path]

    Elaborates out a directory/glob/plain path.

    Elaborates out a directory/glob/plain path.

    path

      Path to elaborate.

    fs

      The underlying file system that this path is on.

    returns

      Returns an array of Paths to load.

    Attributes
      protected
    Exceptions thrown
      FileNotFoundException

      if the path does not match any files.

    See also

      getFsAndFiles

13. #### def getFsAndFiles(path: Path): Array[Path]

    Elaborates out a directory/glob/plain path.

    Elaborates out a directory/glob/plain path.

    path

      Path to elaborate.

    returns

      Returns an array of Paths to load.

    Attributes
      protected
    Exceptions thrown
      FileNotFoundException

      if the path does not match any files.

    See also

      getFiles

14. #### def getFsAndFilesWithFilter(pathName: String, filter: PathFilter): Array[Path]

    Elaborates out a directory/glob/plain path name.

    Elaborates out a directory/glob/plain path name.

    pathName

      Path name to elaborate.

    filter

      Filter to discard paths.

    returns

      Returns an array of Paths to load.

    Attributes
      protected
    Exceptions thrown
      FileNotFoundException

      if the path does not match any files.

    See also

      getFiles

15. #### def hashCode(): Int

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

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17. #### def isTraceEnabled(): Boolean

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18. #### def loadAlignments(pathName: String, optPathName2: Option[String] = None, optRecordGroup: Option[String] = None, optPredicate: Option[FilterPredicate] = None, optProjection: Option[Schema] = None, stringency: ValidationStringency = ValidationStringency.STRICT): AlignmentRecordRDD

    Load alignment records into an AlignmentRecordRDD.

    Load alignment records into an AlignmentRecordRDD.

    Loads path names ending in: * .bam/.cram/.sam as BAM/CRAM/SAM format, * .fa/.fasta as FASTA format, * .fq/.fastq as FASTQ format, and * .ifq as interleaved FASTQ format.

    If none of these match, fall back to Parquet + Avro.

    For FASTA, FASTQ, and interleaved FASTQ formats, compressed files are supported through compression codecs configured in Hadoop, which by default include .gz and .bz2, but can include more.

    pathName

      The path name to load alignment records from. Globs/directories are supported, although file extension must be present for BAM/CRAM/SAM, FASTA, and FASTQ formats.

    optPathName2

      The optional path name to load the second set of alignment records from, if loading paired FASTQ format. Globs/directories are supported, although file extension must be present. Defaults to None.

    optRecordGroup

      The optional record group name to associate to the alignment records. Defaults to None.

    optPredicate

      An optional pushdown predicate to use when reading Parquet + Avro. Defaults to None.

    optProjection

      An option projection schema to use when reading Parquet + Avro. Defaults to None.

    stringency

      The validation stringency to use when validating BAM/CRAM/SAM or FASTQ formats. Defaults to ValidationStringency.STRICT.

    returns

      Returns an AlignmentRecordRDD which wraps the RDD of alignment records, sequence dictionary representing contigs the alignment records may be aligned to, and the record group dictionary for the alignment records if one is available.

    See also

      loadParquetAlignments

      loadInterleavedFastq

      loadFasta

      loadFastq

      loadBam

19. #### def loadBam(pathName: String, stringency: ValidationStringency = ValidationStringency.STRICT): AlignmentRecordRDD

    Load alignment records from BAM/CRAM/SAM into an AlignmentRecordRDD.

    Load alignment records from BAM/CRAM/SAM into an AlignmentRecordRDD.

    This reads the sequence and record group dictionaries from the BAM/CRAM/SAM file header. SAMRecords are read from the file and converted to the AlignmentRecord schema.

    pathName

      The path name to load BAM/CRAM/SAM formatted alignment records from. Globs/directories are supported.

    stringency

      The validation stringency to use when validating the BAM/CRAM/SAM format header. Defaults to ValidationStringency.STRICT.

    returns

      Returns an AlignmentRecordRDD which wraps the RDD of alignment records, sequence dictionary representing contigs the alignment records may be aligned to, and the record group dictionary for the alignment records if one is available.

20. #### def loadBed(pathName: String, optSequenceDictionary: Option[SequenceDictionary] = None, optMinPartitions: Option[Int] = None, stringency: ValidationStringency = ValidationStringency.STRICT): FeatureRDD

    Load a path name in BED6/12 format into a FeatureRDD.

    Load a path name in BED6/12 format into a FeatureRDD.

    pathName

      The path name to load features in BED6/12 format from. Globs/directories are supported.

    optSequenceDictionary

      Optional sequence dictionary. Defaults to None.

    optMinPartitions

      An optional minimum number of partitions to load. If not set, falls back to the configured Spark default parallelism. Defaults to None.

    stringency

      The validation stringency to use when validating BED6/12 format. Defaults to ValidationStringency.STRICT.

    returns

      Returns a FeatureRDD.

21. #### def loadContigFragments(pathName: String, maximumLength: Long = 10000L, optPredicate: Option[FilterPredicate] = None, optProjection: Option[Schema] = None): NucleotideContigFragmentRDD

    Load nucleotide contig fragments into a NucleotideContigFragmentRDD.

    Load nucleotide contig fragments into a NucleotideContigFragmentRDD.

    If the path name has a .fa/.fasta extension, load as FASTA format. Else, fall back to Parquet + Avro.

    For FASTA format, compressed files are supported through compression codecs configured in Hadoop, which by default include .gz and .bz2, but can include more.

    pathName

      The path name to load nucleotide contig fragments from. Globs/directories are supported, although file extension must be present for FASTA format.

    maximumLength

      Maximum fragment length. Defaults to 10000L. Values greater than 1e9 should be avoided.

    optPredicate

      An optional pushdown predicate to use when reading Parquet + Avro. Defaults to None.

    optProjection

      An option projection schema to use when reading Parquet + Avro. Defaults to None.

    returns

      Returns a NucleotideContigFragmentRDD.

    See also

      loadParquetContigFragments

      loadFasta

22. #### def loadCoverage(pathName: String, optSequenceDictionary: Option[SequenceDictionary] = None, optMinPartitions: Option[Int] = None, optPredicate: Option[FilterPredicate] = None, optProjection: Option[Schema] = None, stringency: ValidationStringency = ValidationStringency.STRICT): CoverageRDD

    Load features into a FeatureRDD and convert to a CoverageRDD.

    Load features into a FeatureRDD and convert to a CoverageRDD. Coverage is stored in the score field of Feature.

    Loads path names ending in: * .bed as BED6/12 format, * .gff3 as GFF3 format, * .gtf/.gff as GTF/GFF2 format, * .narrow[pP]eak as NarrowPeak format, and * .interval_list as IntervalList format.

    If none of these match, fall back to Parquet + Avro.

    For BED6/12, GFF3, GTF/GFF2, NarrowPeak, and IntervalList formats, compressed files are supported through compression codecs configured in Hadoop, which by default include .gz and .bz2, but can include more.

    pathName

      The path name to load features from. Globs/directories are supported, although file extension must be present for BED6/12, GFF3, GTF/GFF2, NarrowPeak, or IntervalList formats.

    optSequenceDictionary

      Optional sequence dictionary. Defaults to None.

    optMinPartitions

      An optional minimum number of partitions to use. For textual formats, if this is None, fall back to the Spark default parallelism. Defaults to None.

    optPredicate

      An optional pushdown predicate to use when reading Parquet + Avro. Defaults to None.

    optProjection

      An option projection schema to use when reading Parquet + Avro. Defaults to None.

    stringency

      The validation stringency to use when validating BED6/12, GFF3, GTF/GFF2, NarrowPeak, or IntervalList formats. Defaults to ValidationStringency.STRICT.

    returns

      Returns a FeatureRDD converted to a CoverageRDD.

    See also

      loadParquetFeatures

      loadIntervalList

      loadNarrowPeak

      loadGff3

      loadGtf

      loadBed

23. #### def loadFasta(pathName: String, maximumLength: Long = 10000L): NucleotideContigFragmentRDD

    Load nucleotide contig fragments from FASTA into a NucleotideContigFragmentRDD.

    Load nucleotide contig fragments from FASTA into a NucleotideContigFragmentRDD.

    pathName

      The path name to load nucleotide contig fragments from. Globs/directories are supported.

    maximumLength

      Maximum fragment length. Defaults to 10000L. Values greater than 1e9 should be avoided.

    returns

      Returns a NucleotideContigFragmentRDD.

24. #### def loadFastq(pathName1: String, optPathName2: Option[String], optRecordGroup: Option[String] = None, stringency: ValidationStringency = ValidationStringency.STRICT): AlignmentRecordRDD

    Load unaligned alignment records from (possibly paired) FASTQ into an AlignmentRecordRDD.

    Load unaligned alignment records from (possibly paired) FASTQ into an AlignmentRecordRDD.

    pathName1

      The path name to load the first set of unaligned alignment records from. Globs/directories are supported.

    optPathName2

      The path name to load the second set of unaligned alignment records from, if provided. Globs/directories are supported.

    optRecordGroup

      The optional record group name to associate to the unaligned alignment records. Defaults to None.

    stringency

      The validation stringency to use when validating (possibly paired) FASTQ format. Defaults to ValidationStringency.STRICT.

    returns

      Returns an unaligned AlignmentRecordRDD.

    See also

      loadUnpairedFastq

      loadPairedFastq

25. #### def loadFeatures(pathName: String, optSequenceDictionary: Option[SequenceDictionary] = None, optMinPartitions: Option[Int] = None, optPredicate: Option[FilterPredicate] = None, optProjection: Option[Schema] = None, stringency: ValidationStringency = ValidationStringency.STRICT): FeatureRDD

    Load features into a FeatureRDD.

    Load features into a FeatureRDD.

    Loads path names ending in: * .bed as BED6/12 format, * .gff3 as GFF3 format, * .gtf/.gff as GTF/GFF2 format, * .narrow[pP]eak as NarrowPeak format, and * .interval_list as IntervalList format.

    If none of these match, fall back to Parquet + Avro.

    For BED6/12, GFF3, GTF/GFF2, NarrowPeak, and IntervalList formats, compressed files are supported through compression codecs configured in Hadoop, which by default include .gz and .bz2, but can include more.

    pathName

      The path name to load features from. Globs/directories are supported, although file extension must be present for BED6/12, GFF3, GTF/GFF2, NarrowPeak, or IntervalList formats.

    optSequenceDictionary

      Optional sequence dictionary. Defaults to None.

    optMinPartitions

      An optional minimum number of partitions to use. For textual formats, if this is None, fall back to the Spark default parallelism. Defaults to None.

    optPredicate

      An optional pushdown predicate to use when reading Parquet + Avro. Defaults to None.

    optProjection

      An option projection schema to use when reading Parquet + Avro. Defaults to None.

    stringency

      The validation stringency to use when validating BED6/12, GFF3, GTF/GFF2, NarrowPeak, or IntervalList formats. Defaults to ValidationStringency.STRICT.

    returns

      Returns a FeatureRDD.

    See also

      loadParquetFeatures

      loadIntervalList

      loadNarrowPeak

      loadGff3

      loadGtf

      loadBed

26. #### def loadFragments(pathName: String, optPredicate: Option[FilterPredicate] = None, optProjection: Option[Schema] = None, stringency: ValidationStringency = ValidationStringency.STRICT): FragmentRDD

    Load fragments into a FragmentRDD.

    Load fragments into a FragmentRDD.

    Loads path names ending in: * .bam/.cram/.sam as BAM/CRAM/SAM format and * .ifq as interleaved FASTQ format.

    If none of these match, fall back to Parquet + Avro.

    For interleaved FASTQ format, compressed files are supported through compression codecs configured in Hadoop, which by default include .gz and .bz2, but can include more.

    pathName

      The path name to load fragments from. Globs/directories are supported, although file extension must be present for BAM/CRAM/SAM and FASTQ formats.

    optPredicate

      An optional pushdown predicate to use when reading Parquet + Avro. Defaults to None.

    optProjection

      An option projection schema to use when reading Parquet + Avro. Defaults to None.

    stringency

      The validation stringency to use when validating BAM/CRAM/SAM or FASTQ formats. Defaults to ValidationStringency.STRICT.

    returns

      Returns a FragmentRDD.

    See also

      loadParquetFragments

      loadInterleavedFastqAsFragments

      loadAlignments

      loadBam

27. #### def loadGenotypes(pathName: String, optPredicate: Option[FilterPredicate] = None, optProjection: Option[Schema] = None, stringency: ValidationStringency = ValidationStringency.STRICT): GenotypeRDD

    Load genotypes into a GenotypeRDD.

    Load genotypes into a GenotypeRDD.

    If the path name has a .vcf/.vcf.gz/.vcf.bgz extension, load as VCF format. Else, fall back to Parquet + Avro.

    pathName

      The path name to load genotypes from. Globs/directories are supported, although file extension must be present for VCF format.

    optPredicate

      An optional pushdown predicate to use when reading Parquet + Avro. Defaults to None.

    optProjection

      An option projection schema to use when reading Parquet + Avro. Defaults to None.

    stringency

      The validation stringency to use when validating VCF format. Defaults to ValidationStringency.STRICT.

    returns

      Returns a GenotypeRDD.

    See also

      loadParquetGenotypes

      loadVcf

28. #### def loadGff3(pathName: String, optSequenceDictionary: Option[SequenceDictionary] = None, optMinPartitions: Option[Int] = None, stringency: ValidationStringency = ValidationStringency.STRICT): FeatureRDD

    Load a path name in GFF3 format into a FeatureRDD.

    Load a path name in GFF3 format into a FeatureRDD.

    pathName

      The path name to load features in GFF3 format from. Globs/directories are supported.

    optSequenceDictionary

      Optional sequence dictionary. Defaults to None.

    optMinPartitions

      An optional minimum number of partitions to load. If not set, falls back to the configured Spark default parallelism. Defaults to None.

    stringency

      The validation stringency to use when validating GFF3 format. Defaults to ValidationStringency.STRICT.

    returns

      Returns a FeatureRDD.

29. #### def loadGtf(pathName: String, optSequenceDictionary: Option[SequenceDictionary] = None, optMinPartitions: Option[Int] = None, stringency: ValidationStringency = ValidationStringency.STRICT): FeatureRDD

    Load a path name in GTF/GFF2 format into a FeatureRDD.

    Load a path name in GTF/GFF2 format into a FeatureRDD.

    pathName

      The path name to load features in GTF/GFF2 format from. Globs/directories are supported.

    optSequenceDictionary

      Optional sequence dictionary. Defaults to None.

    optMinPartitions

      An optional minimum number of partitions to load. If not set, falls back to the configured Spark default parallelism. Defaults to None.

    stringency

      The validation stringency to use when validating GTF/GFF2 format. Defaults to ValidationStringency.STRICT.

    returns

      Returns a FeatureRDD.

30. #### def loadIndexedBam(pathName: String, viewRegions: Iterable[ReferenceRegion], stringency: ValidationStringency = ValidationStringency.STRICT)(implicit s: DummyImplicit): AlignmentRecordRDD

    Functions like loadBam, but uses BAM index files to look at fewer blocks, and only returns records within the specified ReferenceRegions.

    Functions like loadBam, but uses BAM index files to look at fewer blocks, and only returns records within the specified ReferenceRegions. BAM index file required.

    pathName

      The path name to load indexed BAM formatted alignment records from. Globs/directories are supported.

    viewRegions

      Iterable of ReferenceRegion we are filtering on.

    stringency

      The validation stringency to use when validating the BAM/CRAM/SAM format header. Defaults to ValidationStringency.STRICT.

    returns

      Returns an AlignmentRecordRDD which wraps the RDD of alignment records, sequence dictionary representing contigs the alignment records may be aligned to, and the record group dictionary for the alignment records if one is available.

31. #### def loadIndexedBam(pathName: String, viewRegion: ReferenceRegion): AlignmentRecordRDD

    Functions like loadBam, but uses BAM index files to look at fewer blocks, and only returns records within a specified ReferenceRegion.

    Functions like loadBam, but uses BAM index files to look at fewer blocks, and only returns records within a specified ReferenceRegion. BAM index file required.

    pathName

      The path name to load indexed BAM formatted alignment records from. Globs/directories are supported.

    viewRegion

      The ReferenceRegion we are filtering on.

    returns

      Returns an AlignmentRecordRDD which wraps the RDD of alignment records, sequence dictionary representing contigs the alignment records may be aligned to, and the record group dictionary for the alignment records if one is available.

32. #### def loadIndexedVcf(pathName: String, viewRegions: Iterable[ReferenceRegion], stringency: ValidationStringency = ValidationStringency.STRICT)(implicit s: DummyImplicit): VariantContextRDD

    Load variant context records from VCF indexed by tabix (tbi) into a VariantContextRDD.

    Load variant context records from VCF indexed by tabix (tbi) into a VariantContextRDD.

    pathName

      The path name to load VCF variant context records from. Globs/directories are supported.

    viewRegions

      Iterator of ReferenceRegions we are filtering on.

    stringency

      The validation stringency to use when validating VCF format. Defaults to ValidationStringency.STRICT.

    returns

      Returns a VariantContextRDD.

33. #### def loadIndexedVcf(pathName: String, viewRegion: ReferenceRegion): VariantContextRDD

    Load variant context records from VCF indexed by tabix (tbi) into a VariantContextRDD.

    Load variant context records from VCF indexed by tabix (tbi) into a VariantContextRDD.

    pathName

      The path name to load VCF variant context records from. Globs/directories are supported.

    viewRegion

      ReferenceRegion we are filtering on.

    returns

      Returns a VariantContextRDD.

34. #### def loadInterleavedFastq(pathName: String): AlignmentRecordRDD

    Load unaligned alignment records from interleaved FASTQ into an AlignmentRecordRDD.

    Load unaligned alignment records from interleaved FASTQ into an AlignmentRecordRDD.

    In interleaved FASTQ, the two reads from a paired sequencing protocol are interleaved in a single file. This is a zipped representation of the typical paired FASTQ.

    pathName

      The path name to load unaligned alignment records from. Globs/directories are supported.

    returns

      Returns an unaligned AlignmentRecordRDD.

35. #### def loadInterleavedFastqAsFragments(pathName: String): FragmentRDD

    Load paired unaligned alignment records grouped by sequencing fragment from interleaved FASTQ into an FragmentRDD.

    Load paired unaligned alignment records grouped by sequencing fragment from interleaved FASTQ into an FragmentRDD.

    In interleaved FASTQ, the two reads from a paired sequencing protocol are interleaved in a single file. This is a zipped representation of the typical paired FASTQ.

    Fragments represent all of the reads from a single sequenced fragment as a single object, which is a useful representation for some tasks.

    pathName

      The path name to load unaligned alignment records from. Globs/directories are supported.

    returns

      Returns a FragmentRDD containing the paired reads grouped by sequencing fragment.

36. #### def loadIntervalList(pathName: String, optMinPartitions: Option[Int] = None, stringency: ValidationStringency = ValidationStringency.STRICT): FeatureRDD

    Load a path name in IntervalList format into a FeatureRDD.

    Load a path name in IntervalList format into a FeatureRDD.

    pathName

      The path name to load features in IntervalList format from. Globs/directories are supported.

    optMinPartitions

      An optional minimum number of partitions to load. If not set, falls back to the configured Spark default parallelism. Defaults to None.

    stringency

      The validation stringency to use when validating IntervalList format. Defaults to ValidationStringency.STRICT.

    returns

      Returns a FeatureRDD.

37. #### def loadNarrowPeak(pathName: String, optSequenceDictionary: Option[SequenceDictionary] = None, optMinPartitions: Option[Int] = None, stringency: ValidationStringency = ValidationStringency.STRICT): FeatureRDD

    Load a path name in NarrowPeak format into a FeatureRDD.

    Load a path name in NarrowPeak format into a FeatureRDD.

    pathName

      The path name to load features in NarrowPeak format from. Globs/directories are supported.

    optSequenceDictionary

      Optional sequence dictionary. Defaults to None.

    optMinPartitions

      An optional minimum number of partitions to load. If not set, falls back to the configured Spark default parallelism. Defaults to None.

    stringency

      The validation stringency to use when validating NarrowPeak format. Defaults to ValidationStringency.STRICT.

    returns

      Returns a FeatureRDD.

38. #### def loadPairedFastq(pathName1: String, pathName2: String, optRecordGroup: Option[String] = None, stringency: ValidationStringency = ValidationStringency.STRICT): AlignmentRecordRDD

    Load unaligned alignment records from paired FASTQ into an AlignmentRecordRDD.

    Load unaligned alignment records from paired FASTQ into an AlignmentRecordRDD.

    pathName1

      The path name to load the first set of unaligned alignment records from. Globs/directories are supported.

    pathName2

      The path name to load the second set of unaligned alignment records from. Globs/directories are supported.

    optRecordGroup

      The optional record group name to associate to the unaligned alignment records. Defaults to None.

    stringency

      The validation stringency to use when validating paired FASTQ format. Defaults to ValidationStringency.STRICT.

    returns

      Returns an unaligned AlignmentRecordRDD.

39. #### def loadParquet[T](pathName: String, optPredicate: Option[FilterPredicate] = None, optProjection: Option[Schema] = None)(implicit ev1: (T) ⇒ SpecificRecord, ev2: Manifest[T]): RDD[T]

    Load a path name in Parquet + Avro format into an RDD.

    Load a path name in Parquet + Avro format into an RDD.

    T

      The type of records to return.

    pathName

      The path name to load Parquet + Avro formatted data from. Globs/directories are supported.

    optPredicate

      An optional pushdown predicate to use when reading Parquet + Avro. Defaults to None.

    optProjection

      An option projection schema to use when reading Parquet + Avro. Defaults to None.

    returns

      An RDD with records of the specified type.

40. #### def loadParquetAlignments(pathName: String, optPredicate: Option[FilterPredicate] = None, optProjection: Option[Schema] = None): AlignmentRecordRDD

    Load a path name in Parquet + Avro format into an AlignmentRecordRDD.

    Load a path name in Parquet + Avro format into an AlignmentRecordRDD.

    pathName

      The path name to load alignment records from. Globs/directories are supported.

    optPredicate

      An optional pushdown predicate to use when reading Parquet + Avro. Defaults to None.

    optProjection

      An option projection schema to use when reading Parquet + Avro. Defaults to None.

    returns

      Returns an AlignmentRecordRDD which wraps the RDD of alignment records, sequence dictionary representing contigs the alignment records may be aligned to, and the record group dictionary for the alignment records if one is available.

    Note

      The sequence dictionary is read from an Avro file stored at pathName/_seqdict.avro and the record group dictionary is read from an Avro file stored at pathName/_rgdict.avro. These files are pure Avro, not Parquet + Avro.

41. #### def loadParquetContigFragments(pathName: String, optPredicate: Option[FilterPredicate] = None, optProjection: Option[Schema] = None): NucleotideContigFragmentRDD

    Load a path name in Parquet + Avro format into a NucleotideContigFragmentRDD.

    Load a path name in Parquet + Avro format into a NucleotideContigFragmentRDD.

    pathName

      The path name to load nucleotide contig fragments from. Globs/directories are supported.

    optPredicate

      An optional pushdown predicate to use when reading Parquet + Avro. Defaults to None.

    optProjection

      An option projection schema to use when reading Parquet + Avro. Defaults to None.

    returns

      Returns a NucleotideContigFragmentRDD.

42. #### def loadParquetCoverage(pathName: String, optPredicate: Option[FilterPredicate] = None, forceRdd: Boolean = false): CoverageRDD

    Load a path name in Parquet + Avro format into a FeatureRDD and convert to a CoverageRDD.

    Load a path name in Parquet + Avro format into a FeatureRDD and convert to a CoverageRDD. Coverage is stored in the score field of Feature.

    pathName

      The path name to load features from. Globs/directories are supported.

    optPredicate

      An optional pushdown predicate to use when reading Parquet + Avro. Defaults to None.

    forceRdd

      Forces loading the RDD.

    returns

      Returns a FeatureRDD converted to a CoverageRDD.

43. #### def loadParquetFeatures(pathName: String, optPredicate: Option[FilterPredicate] = None, optProjection: Option[Schema] = None): FeatureRDD

    Load a path name in Parquet + Avro format into a FeatureRDD.

    Load a path name in Parquet + Avro format into a FeatureRDD.

    pathName

      The path name to load features from. Globs/directories are supported.

    optPredicate

      An optional pushdown predicate to use when reading Parquet + Avro. Defaults to None.

    optProjection

      An option projection schema to use when reading Parquet + Avro. Defaults to None.

    returns

      Returns a FeatureRDD.

44. #### def loadParquetFragments(pathName: String, optPredicate: Option[FilterPredicate] = None, optProjection: Option[Schema] = None): FragmentRDD

    Load a path name in Parquet + Avro format into a FragmentRDD.

    Load a path name in Parquet + Avro format into a FragmentRDD.

    pathName

      The path name to load fragments from. Globs/directories are supported.

    optPredicate

      An optional pushdown predicate to use when reading Parquet + Avro. Defaults to None.

    optProjection

      An option projection schema to use when reading Parquet + Avro. Defaults to None.

    returns

      Returns a FragmentRDD.

45. #### def loadParquetGenotypes(pathName: String, optPredicate: Option[FilterPredicate] = None, optProjection: Option[Schema] = None): GenotypeRDD

    Load a path name in Parquet + Avro format into a GenotypeRDD.

    Load a path name in Parquet + Avro format into a GenotypeRDD.

    pathName

      The path name to load genotypes from. Globs/directories are supported.

    optPredicate

      An optional pushdown predicate to use when reading Parquet + Avro. Defaults to None.

    optProjection

      An option projection schema to use when reading Parquet + Avro. Defaults to None.

    returns

      Returns a GenotypeRDD.

46. #### def loadParquetVariants(pathName: String, optPredicate: Option[FilterPredicate] = None, optProjection: Option[Schema] = None): VariantRDD

    Load a path name in Parquet + Avro format into a VariantRDD.

    Load a path name in Parquet + Avro format into a VariantRDD.

    pathName

      The path name to load variants from. Globs/directories are supported.

    optPredicate

      An optional pushdown predicate to use when reading Parquet + Avro. Defaults to None.

    optProjection

      An option projection schema to use when reading Parquet + Avro. Defaults to None.

    returns

      Returns a VariantRDD.

47. #### def loadReferenceFile(pathName: String, maximumLength: Long): ReferenceFile

    Load reference sequences into a broadcastable ReferenceFile.

    Load reference sequences into a broadcastable ReferenceFile.

    If the path name has a .2bit extension, loads a 2bit file. Else, uses loadContigFragments to load the reference as an RDD, which is then collected to the driver.

    pathName

      The path name to load reference sequences from. Globs/directories for 2bit format are not supported.

    maximumLength

      Maximum fragment length. Defaults to 10000L. Values greater than 1e9 should be avoided.

    returns

      Returns a broadcastable ReferenceFile.

    See also

      loadContigFragments

48. #### def loadSequenceDictionary(pathName: String): SequenceDictionary

    Load a sequence dictionary.

    Load a sequence dictionary.

    Loads path names ending in: * .dict as HTSJDK sequence dictionary format, * .genome as Bedtools genome file format, * .txt as UCSC Genome Browser chromInfo files.

    Compressed files are supported through compression codecs configured in Hadoop, which by default include .gz and .bz2, but can include more.

    pathName

      The path name to load a sequence dictionary from.

    returns

      Returns a sequence dictionary.

    Exceptions thrown
      IllegalArgumentException

      if pathName file extension not one of .dict, .genome, or .txt

49. #### def loadUnpairedFastq(pathName: String, setFirstOfPair: Boolean = false, setSecondOfPair: Boolean = false, optRecordGroup: Option[String] = None, stringency: ValidationStringency = ValidationStringency.STRICT): AlignmentRecordRDD

    Load unaligned alignment records from unpaired FASTQ into an AlignmentRecordRDD.

    Load unaligned alignment records from unpaired FASTQ into an AlignmentRecordRDD.

    pathName

      The path name to load unaligned alignment records from. Globs/directories are supported.

    setFirstOfPair

      If true, sets the unaligned alignment record as first from the fragment. Defaults to false.

    setSecondOfPair

      If true, sets the unaligned alignment record as second from the fragment. Defaults to false.

    optRecordGroup

      The optional record group name to associate to the unaligned alignment records. Defaults to None.

    stringency

      The validation stringency to use when validating unpaired FASTQ format. Defaults to ValidationStringency.STRICT.

    returns

      Returns an unaligned AlignmentRecordRDD.

50. #### def loadVariants(pathName: String, optPredicate: Option[FilterPredicate] = None, optProjection: Option[Schema] = None, stringency: ValidationStringency = ValidationStringency.STRICT): VariantRDD

    Load variants into a VariantRDD.

    Load variants into a VariantRDD.

    If the path name has a .vcf/.vcf.gz/.vcf.bgz extension, load as VCF format. Else, fall back to Parquet + Avro.

    pathName

      The path name to load variants from. Globs/directories are supported, although file extension must be present for VCF format.

    optPredicate

      An optional pushdown predicate to use when reading Parquet + Avro. Defaults to None.

    optProjection

      An option projection schema to use when reading Parquet + Avro. Defaults to None.

    stringency

      The validation stringency to use when validating VCF format. Defaults to ValidationStringency.STRICT.

    returns

      Returns a VariantRDD.

    See also

      loadParquetVariants

      loadVcf

51. #### def loadVcf(pathName: String, stringency: ValidationStringency = ValidationStringency.STRICT): VariantContextRDD

    Load variant context records from VCF into a VariantContextRDD.

    Load variant context records from VCF into a VariantContextRDD.

    pathName

      The path name to load VCF variant context records from. Globs/directories are supported.

    stringency

      The validation stringency to use when validating VCF format. Defaults to ValidationStringency.STRICT.

    returns

      Returns a VariantContextRDD.

52. #### def loadVcfWithProjection(pathName: String, infoFields: Set[String], formatFields: Set[String], stringency: ValidationStringency = ValidationStringency.STRICT): VariantContextRDD

    Load variant context records from VCF into a VariantContextRDD.

    Load variant context records from VCF into a VariantContextRDD.

    Only converts the core Genotype/Variant fields, and the fields set in the requested projection. Core variant fields include:

    * Names (ID) * Filters (FILTER)

    Core genotype fields include:

    * Allelic depth (AD) * Read depth (DP) * Min read depth (MIN_DP) * Genotype quality (GQ) * Genotype likelihoods (GL/PL) * Strand bias components (SB) * Phase info (PS,PQ)

    pathName

      The path name to load VCF variant context records from. Globs/directories are supported.

    infoFields

      The info fields to include, in addition to the ID and FILTER attributes.

    formatFields

      The format fields to include, in addition to the core fields listed above.

    stringency

      The validation stringency to use when validating VCF format. Defaults to ValidationStringency.STRICT.

    returns

      Returns a VariantContextRDD.

53. #### def log: Logger

    Attributes
      protected
    Definition Classes
      Logging

54. #### def logDebug(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
      protected
    Definition Classes
      Logging

55. #### def logDebug(msg: ⇒ String): Unit

    Attributes
      protected
    Definition Classes
      Logging

56. #### def logError(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
      protected
    Definition Classes
      Logging

57. #### def logError(msg: ⇒ String): Unit

    Attributes
      protected
    Definition Classes
      Logging

58. #### def logInfo(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
      protected
    Definition Classes
      Logging

59. #### def logInfo(msg: ⇒ String): Unit

    Attributes
      protected
    Definition Classes
      Logging

60. #### def logName: String

    Attributes
      protected
    Definition Classes
      Logging

61. #### def logTrace(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
      protected
    Definition Classes
      Logging

62. #### def logTrace(msg: ⇒ String): Unit

    Attributes
      protected
    Definition Classes
      Logging

63. #### def logWarning(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
      protected
    Definition Classes
      Logging

64. #### def logWarning(msg: ⇒ String): Unit

    Attributes
      protected
    Definition Classes
      Logging

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

    Definition Classes
      AnyRef

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

    Definition Classes
      AnyRef

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

    Definition Classes
      AnyRef

68. #### val sc: SparkContext

    The SparkContext to wrap.

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

    Definition Classes
      AnyRef

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

    Definition Classes
      AnyRef → Any

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

    Definition Classes
      AnyRef
    Annotations
      @throws( ... )

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

    Definition Classes
      AnyRef
    Annotations
      @throws( ... )

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

    Definition Classes
      AnyRef
    Annotations
      @throws( ... )

### Inherited from Logging

### Inherited from Serializable

### Inherited from AnyRef

### Inherited from Any

### Ungrouped