class ADAMContext extends Serializable with Logging
The ADAMContext provides functions on top of a SparkContext for loading genomic data.
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new
ADAMContext(sc: SparkContext)
- sc
The SparkContext to wrap.
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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.
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FileNotFoundException
if the path does not match any files.- See also
getFsAndFiles
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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.
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FileNotFoundException
if the path does not match any files.- See also
getFiles
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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.
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FileNotFoundException
if the path does not match any files.- See also
getFiles
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def
isPartitioned(pathName: String): Boolean
Return true if the specified path of Parquet + Avro files is partitioned.
Return true if the specified path of Parquet + Avro files is partitioned.
- pathName
Path in which to look for partitioned flag.
- returns
Return true if the specified path of Parquet + Avro files is partitioned. Behavior is undefined if some paths in glob contain _partitionedByStartPos flag file and some do not.
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def
loadAlignments(pathName: String, optPathName2: Option[String] = None, optReadGroup: Option[String] = None, optPredicate: Option[FilterPredicate] = None, optProjection: Option[Schema] = None, stringency: ValidationStringency = ValidationStringency.STRICT): AlignmentRecordDataset
Load alignment records into an AlignmentRecordDataset.
Load alignment records into an AlignmentRecordDataset.
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.
- optReadGroup
The optional read group identifier 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 AlignmentRecordDataset which wraps the genomic dataset of alignment records, sequence dictionary representing reference sequences the alignment records may be aligned to, and the read group dictionary for the alignment records if one is available.
- See also
loadBam
loadFastq
loadFasta
loadInterleavedFastq
loadParquetAlignments
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def
loadBam(pathName: String, stringency: ValidationStringency = ValidationStringency.STRICT): AlignmentRecordDataset
Load alignment records from BAM/CRAM/SAM into an AlignmentRecordDataset.
Load alignment records from BAM/CRAM/SAM into an AlignmentRecordDataset.
This reads the sequence and read 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 AlignmentRecordDataset which wraps the genomic dataset of alignment records, sequence dictionary representing reference sequences the alignment records may be aligned to, and the read group dictionary for the alignment records if one is available.
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def
loadBed(pathName: String, optSequenceDictionary: Option[SequenceDictionary] = None, optMinPartitions: Option[Int] = None, stringency: ValidationStringency = ValidationStringency.STRICT): FeatureDataset
Load a path name in BED6/12 format into a FeatureDataset.
Load a path name in BED6/12 format into a FeatureDataset.
- 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 FeatureDataset.
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def
loadContigFragments(pathName: String, maximumLength: Long = 10000L, optPredicate: Option[FilterPredicate] = None, optProjection: Option[Schema] = None): NucleotideContigFragmentDataset
Load nucleotide contig fragments into a NucleotideContigFragmentDataset.
Load nucleotide contig fragments into a NucleotideContigFragmentDataset.
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 NucleotideContigFragmentDataset.
- See also
loadFasta
loadParquetContigFragments
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def
loadCoverage(pathName: String, optSequenceDictionary: Option[SequenceDictionary] = None, optMinPartitions: Option[Int] = None, optPredicate: Option[FilterPredicate] = None, optProjection: Option[Schema] = None, stringency: ValidationStringency = ValidationStringency.STRICT): CoverageDataset
Load features into a FeatureDataset and convert to a CoverageDataset.
Load features into a FeatureDataset and convert to a CoverageDataset. 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 FeatureDataset converted to a CoverageDataset.
- See also
loadBed
loadGtf
loadGff3
loadNarrowPeak
loadIntervalList
loadParquetFeatures
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def
loadFasta(pathName: String, maximumLength: Long = 10000L): NucleotideContigFragmentDataset
Load nucleotide contig fragments from FASTA into a NucleotideContigFragmentDataset.
Load nucleotide contig fragments from FASTA into a NucleotideContigFragmentDataset.
- 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 NucleotideContigFragmentDataset.
-
def
loadFastq(pathName1: String, optPathName2: Option[String], optReadGroup: Option[String] = None, stringency: ValidationStringency = ValidationStringency.STRICT): AlignmentRecordDataset
Load unaligned alignment records from (possibly paired) FASTQ into an AlignmentRecordDataset.
Load unaligned alignment records from (possibly paired) FASTQ into an AlignmentRecordDataset.
- 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.
- optReadGroup
The optional read group identifier 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 AlignmentRecordDataset.
- See also
loadPairedFastq
loadUnpairedFastq
-
def
loadFeatures(pathName: String, optSequenceDictionary: Option[SequenceDictionary] = None, optMinPartitions: Option[Int] = None, optPredicate: Option[FilterPredicate] = None, optProjection: Option[Schema] = None, stringency: ValidationStringency = ValidationStringency.STRICT): FeatureDataset
Load features into a FeatureDataset.
Load features into a FeatureDataset.
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 FeatureDataset.
- See also
loadBed
loadGtf
loadGff3
loadNarrowPeak
loadIntervalList
loadParquetFeatures
-
def
loadFragments(pathName: String, optPredicate: Option[FilterPredicate] = None, optProjection: Option[Schema] = None, stringency: ValidationStringency = ValidationStringency.STRICT): FragmentDataset
Load fragments into a FragmentDataset.
Load fragments into a FragmentDataset.
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 FragmentDataset.
- See also
loadBam
loadAlignments
loadInterleavedFastqAsFragments
loadParquetFragments
-
def
loadGenotypes(pathName: String, optPredicate: Option[FilterPredicate] = None, optProjection: Option[Schema] = None, stringency: ValidationStringency = ValidationStringency.STRICT): GenotypeDataset
Load genotypes into a GenotypeDataset.
Load genotypes into a GenotypeDataset.
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 GenotypeDataset.
- See also
loadVcf
loadParquetGenotypes
-
def
loadGff3(pathName: String, optSequenceDictionary: Option[SequenceDictionary] = None, optMinPartitions: Option[Int] = None, stringency: ValidationStringency = ValidationStringency.STRICT): FeatureDataset
Load a path name in GFF3 format into a FeatureDataset.
Load a path name in GFF3 format into a FeatureDataset.
- 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 FeatureDataset.
-
def
loadGtf(pathName: String, optSequenceDictionary: Option[SequenceDictionary] = None, optMinPartitions: Option[Int] = None, stringency: ValidationStringency = ValidationStringency.STRICT): FeatureDataset
Load a path name in GTF/GFF2 format into a FeatureDataset.
Load a path name in GTF/GFF2 format into a FeatureDataset.
- 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 FeatureDataset.
-
def
loadIndexedBam(pathName: String, viewRegions: Iterable[ReferenceRegion], stringency: ValidationStringency = ValidationStringency.STRICT)(implicit s: DummyImplicit): AlignmentRecordDataset
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 AlignmentRecordDataset which wraps the genomic dataset of alignment records, sequence dictionary representing reference sequences the alignment records may be aligned to, and the read group dictionary for the alignment records if one is available.
-
def
loadIndexedBam(pathName: String, viewRegion: ReferenceRegion): AlignmentRecordDataset
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 AlignmentRecordDataset which wraps the genomic dataset of alignment records, sequence dictionary representing reference sequences the alignment records may be aligned to, and the read group dictionary for the alignment records if one is available.
-
def
loadIndexedVcf(pathName: String, viewRegions: Iterable[ReferenceRegion], stringency: ValidationStringency = ValidationStringency.STRICT)(implicit s: DummyImplicit): VariantContextDataset
Load variant context records from VCF indexed by tabix (tbi) into a VariantContextDataset.
Load variant context records from VCF indexed by tabix (tbi) into a VariantContextDataset.
- 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 VariantContextDataset.
-
def
loadIndexedVcf(pathName: String, viewRegion: ReferenceRegion): VariantContextDataset
Load variant context records from VCF indexed by tabix (tbi) into a VariantContextDataset.
Load variant context records from VCF indexed by tabix (tbi) into a VariantContextDataset.
- pathName
The path name to load VCF variant context records from. Globs/directories are supported.
- viewRegion
ReferenceRegion we are filtering on.
- returns
Returns a VariantContextDataset.
-
def
loadInterleavedFastq(pathName: String): AlignmentRecordDataset
Load unaligned alignment records from interleaved FASTQ into an AlignmentRecordDataset.
Load unaligned alignment records from interleaved FASTQ into an AlignmentRecordDataset.
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 AlignmentRecordDataset.
-
def
loadInterleavedFastqAsFragments(pathName: String): FragmentDataset
Load paired unaligned alignment records grouped by sequencing fragment from interleaved FASTQ into an FragmentDataset.
Load paired unaligned alignment records grouped by sequencing fragment from interleaved FASTQ into an FragmentDataset.
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 FragmentDataset containing the paired reads grouped by sequencing fragment.
-
def
loadIntervalList(pathName: String, optMinPartitions: Option[Int] = None, stringency: ValidationStringency = ValidationStringency.STRICT): FeatureDataset
Load a path name in IntervalList format into a FeatureDataset.
Load a path name in IntervalList format into a FeatureDataset.
- 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 FeatureDataset.
-
def
loadNarrowPeak(pathName: String, optSequenceDictionary: Option[SequenceDictionary] = None, optMinPartitions: Option[Int] = None, stringency: ValidationStringency = ValidationStringency.STRICT): FeatureDataset
Load a path name in NarrowPeak format into a FeatureDataset.
Load a path name in NarrowPeak format into a FeatureDataset.
- 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 FeatureDataset.
-
def
loadPairedFastq(pathName1: String, pathName2: String, optReadGroup: Option[String] = None, persistLevel: Option[StorageLevel] = Some(StorageLevel.MEMORY_ONLY), stringency: ValidationStringency = ValidationStringency.STRICT): AlignmentRecordDataset
Load unaligned alignment records from paired FASTQ into an AlignmentRecordDataset.
Load unaligned alignment records from paired FASTQ into an AlignmentRecordDataset.
- 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.
- optReadGroup
The optional read group identifier to associate to the unaligned alignment records. Defaults to None.
- persistLevel
An optional persistance level to set. If this level is set, then reads will be cached (at the given persistance) level as part of validation. Defaults to StorageLevel.MEMORY_ONLY.
- stringency
The validation stringency to use when validating paired FASTQ format. Defaults to ValidationStringency.STRICT.
- returns
Returns an unaligned AlignmentRecordDataset.
-
def
loadPairedFastqAsFragments(pathName1: String, pathName2: String, optReadGroup: Option[String] = None, persistLevel: Option[StorageLevel] = Some(StorageLevel.MEMORY_ONLY), stringency: ValidationStringency = ValidationStringency.STRICT): FragmentDataset
Load paired unaligned alignment records grouped by sequencing fragment from paired FASTQ files into an FragmentDataset.
Load paired unaligned alignment records grouped by sequencing fragment from paired FASTQ files into an FragmentDataset.
Fragments represent all of the reads from a single sequenced fragment as a single object, which is a useful representation for some tasks.
- 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.
- optReadGroup
The optional read group identifier to associate to the unaligned alignment records. Defaults to None.
- persistLevel
An optional persistance level to set. If this level is set, then reads will be cached (at the given persistance) level as part of validation. Defaults to StorageLevel.MEMORY_ONLY.
- stringency
The validation stringency to use when validating paired FASTQ format. Defaults to ValidationStringency.STRICT.
- returns
Returns a FragmentDataset containing the paired reads grouped by sequencing fragment.
-
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.
-
def
loadParquetAlignments(pathName: String, optPredicate: Option[FilterPredicate] = None, optProjection: Option[Schema] = None): AlignmentRecordDataset
Load a path name in Parquet + Avro format into an AlignmentRecordDataset.
Load a path name in Parquet + Avro format into an AlignmentRecordDataset.
- 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 AlignmentRecordDataset which wraps the genomic dataset of alignment records, sequence dictionary representing reference sequences the alignment records may be aligned to, and the read group dictionary for the alignment records if one is available.
- Note
The sequence dictionary is read from an Avro file stored at pathName/_references.avro and the read group dictionary is read from an Avro file stored at pathName/_readGroups.avro. These files are pure Avro, not Parquet + Avro.
-
def
loadParquetContigFragments(pathName: String, optPredicate: Option[FilterPredicate] = None, optProjection: Option[Schema] = None): NucleotideContigFragmentDataset
Load a path name in Parquet + Avro format into a NucleotideContigFragmentDataset.
Load a path name in Parquet + Avro format into a NucleotideContigFragmentDataset.
- 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 NucleotideContigFragmentDataset.
-
def
loadParquetCoverage(pathName: String, optPredicate: Option[FilterPredicate] = None, forceRdd: Boolean = false): CoverageDataset
Load a path name in Parquet + Avro format into a FeatureDataset and convert to a CoverageDataset.
Load a path name in Parquet + Avro format into a FeatureDataset and convert to a CoverageDataset. 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 FeatureDataset converted to a CoverageDataset.
-
def
loadParquetFeatures(pathName: String, optPredicate: Option[FilterPredicate] = None, optProjection: Option[Schema] = None): FeatureDataset
Load a path name in Parquet + Avro format into a FeatureDataset.
Load a path name in Parquet + Avro format into a FeatureDataset.
- 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 FeatureDataset.
-
def
loadParquetFragments(pathName: String, optPredicate: Option[FilterPredicate] = None, optProjection: Option[Schema] = None): FragmentDataset
Load a path name in Parquet + Avro format into a FragmentDataset.
Load a path name in Parquet + Avro format into a FragmentDataset.
- 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 FragmentDataset.
-
def
loadParquetGenotypes(pathName: String, optPredicate: Option[FilterPredicate] = None, optProjection: Option[Schema] = None): GenotypeDataset
Load a path name in Parquet + Avro format into a GenotypeDataset.
Load a path name in Parquet + Avro format into a GenotypeDataset.
- 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 GenotypeDataset.
-
def
loadParquetVariantContexts(pathName: String): VariantContextDataset
Load a path name in Parquet + Avro format into a VariantContextDataset.
Load a path name in Parquet + Avro format into a VariantContextDataset.
- pathName
The path name to load variant context records from. Globs/directories are supported.
- returns
Returns a VariantContextDataset.
-
def
loadParquetVariants(pathName: String, optPredicate: Option[FilterPredicate] = None, optProjection: Option[Schema] = None): VariantDataset
Load a path name in Parquet format into a VariantDataset.
Load a path name in Parquet format into a VariantDataset.
- 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 VariantDataset.
-
def
loadPartitionedParquetAlignments(pathName: String, regions: Iterable[ReferenceRegion] = Iterable.empty, optLookbackPartitions: Option[Int] = Some(1)): AlignmentRecordDataset
Load a path name with range binned partitioned Parquet format into an AlignmentRecordDataset.
Load a path name with range binned partitioned Parquet format into an AlignmentRecordDataset.
- pathName
The path name to load alignment records from. Globs/directories are supported.
- regions
Optional list of genomic regions to load.
- optLookbackPartitions
Number of partitions to lookback to find beginning of an overlapping region when using the filterByOverlappingRegions function on the returned dataset. Defaults to one partition.
- returns
Returns an AlignmentRecordDataset.
- Note
The sequence dictionary is read from an Avro file stored at pathName/_references.avro and the read group dictionary is read from an Avro file stored at pathName/_readGroups.avro. These files are pure Avro, not Parquet + Avro.
-
def
loadPartitionedParquetContigFragments(pathName: String, regions: Iterable[ReferenceRegion] = Iterable.empty, optLookbackPartitions: Option[Int] = Some(1)): NucleotideContigFragmentDataset
Load a path name with range binned partitioned Parquet format into a NucleotideContigFragmentDataset.
Load a path name with range binned partitioned Parquet format into a NucleotideContigFragmentDataset.
- pathName
The path name to load alignment records from. Globs/directories are supported.
- regions
Optional list of genomic regions to load.
- optLookbackPartitions
Number of partitions to lookback to find beginning of an overlapping region when using the filterByOverlappingRegions function on the returned dataset. Defaults to one partition.
- returns
Returns a NucleotideContigFragmentDataset.
-
def
loadPartitionedParquetFeatures(pathName: String, regions: Iterable[ReferenceRegion] = Iterable.empty, optLookbackPartitions: Option[Int] = Some(1)): FeatureDataset
Load a path name with range binned partitioned Parquet format into a FeatureDataset.
Load a path name with range binned partitioned Parquet format into a FeatureDataset.
- pathName
The path name to load alignment records from. Globs/directories are supported.
- regions
Optional list of genomic regions to load.
- optLookbackPartitions
Number of partitions to lookback to find beginning of an overlapping region when using the filterByOverlappingRegions function on the returned dataset. Defaults to one partition.
- returns
Returns a FeatureDataset.
-
def
loadPartitionedParquetGenotypes(pathName: String, regions: Iterable[ReferenceRegion] = Iterable.empty, optLookbackPartitions: Option[Int] = Some(1)): GenotypeDataset
Load a path name with range binned partitioned Parquet format into a GenotypeDataset.
Load a path name with range binned partitioned Parquet format into a GenotypeDataset.
- pathName
The path name to load alignment records from. Globs/directories are supported.
- regions
Optional list of genomic regions to load.
- optLookbackPartitions
Number of partitions to lookback to find beginning of an overlapping region when using the filterByOverlappingRegions function on the returned dataset. Defaults to one partition.
- returns
Returns a GenotypeDataset.
-
def
loadPartitionedParquetVariantContexts(pathName: String, regions: Iterable[ReferenceRegion] = Iterable.empty, optLookbackPartitions: Option[Int] = Some(1)): VariantContextDataset
Load a path name with range binned partitioned Parquet format into a VariantContextDataset.
Load a path name with range binned partitioned Parquet format into a VariantContextDataset.
- pathName
The path name to load variant context records from. Globs/directories are supported.
- regions
Optional list of genomic regions to load.
- optLookbackPartitions
Number of partitions to lookback to find beginning of an overlapping region when using the filterByOverlappingRegions function on the returned dataset. Defaults to one partition.
- returns
Returns a VariantContextDataset.
-
def
loadPartitionedParquetVariants(pathName: String, regions: Iterable[ReferenceRegion] = Iterable.empty, optLookbackPartitions: Option[Int] = Some(1)): VariantDataset
Load a path name with range binned partitioned Parquet format into a VariantDataset.
Load a path name with range binned partitioned Parquet format into a VariantDataset.
- pathName
The path name to load alignment records from. Globs/directories are supported.
- regions
Optional list of genomic regions to load.
- optLookbackPartitions
Number of partitions to lookback to find beginning of an overlapping region when using the filterByOverlappingRegions function on the returned dataset. Defaults to one partition.
- returns
Returns a VariantDataset.
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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
-
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
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def
loadUnpairedFastq(pathName: String, setFirstOfPair: Boolean = false, setSecondOfPair: Boolean = false, optReadGroup: Option[String] = None, stringency: ValidationStringency = ValidationStringency.STRICT): AlignmentRecordDataset
Load unaligned alignment records from unpaired FASTQ into an AlignmentRecordDataset.
Load unaligned alignment records from unpaired FASTQ into an AlignmentRecordDataset.
- 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.
- optReadGroup
The optional read group identifier 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 AlignmentRecordDataset.
-
def
loadVariantContexts(pathName: String): VariantContextDataset
Load a path name in VCF or Parquet format into a VariantContextDataset.
Load a path name in VCF or Parquet format into a VariantContextDataset.
- pathName
The path name to load variant context records from. Globs/directories are supported.
- returns
Returns a VariantContextDataset.
-
def
loadVariants(pathName: String, optPredicate: Option[FilterPredicate] = None, optProjection: Option[Schema] = None, stringency: ValidationStringency = ValidationStringency.STRICT): VariantDataset
Load variants into a VariantDataset.
Load variants into a VariantDataset.
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 VariantDataset.
- See also
loadVcf
loadParquetVariants
-
def
loadVcf(pathName: String, stringency: ValidationStringency = ValidationStringency.STRICT): VariantContextDataset
Load variant context records from VCF into a VariantContextDataset.
Load variant context records from VCF into a VariantContextDataset.
- 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 VariantContextDataset.
-
def
loadVcfWithProjection(pathName: String, infoFields: Set[String], formatFields: Set[String], stringency: ValidationStringency = ValidationStringency.STRICT): VariantContextDataset
Load variant context records from VCF into a VariantContextDataset.
Load variant context records from VCF into a VariantContextDataset.
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 VariantContextDataset.
-
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