org.bdgenomics.adam.rdd

# ADAMContext

#### class ADAMContext extends Serializable with Logging

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### Instance Constructors

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

### Value Members

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

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2. #### final def ##(): Int

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3. #### final def ==(arg0: Any): Boolean

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4. #### def adamDictionaryLoad[T](filePath: String)(implicit ev1: (T) ⇒ SpecificRecord, ev2: Manifest[T]): SequenceDictionary

   This method should create a new SequenceDictionary from any parquet file which contains records that have the requisite reference{Name,Id,Length,Url} fields.

   This method should create a new SequenceDictionary from any parquet file which contains records that have the requisite reference{Name,Id,Length,Url} fields.

   (If the path is a BAM or SAM file, and the implicit type is an Read, then it just defaults to reading the SequenceDictionary out of the BAM header in the normal way.)

   T

     The type of records to return

   filePath

     The path to the input data

   returns

     A sequenceDictionary containing the names and indices of all the sequences to which the records in the corresponding file are aligned.

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

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

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

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

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

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10. #### def findFiles(path: Path, regex: String): Seq[Path]

    Searches a path recursively, returning the names of all directories in the tree whose name matches the given regex.

    Searches a path recursively, returning the names of all directories in the tree whose name matches the given regex.

    path

      The path to begin the search at

    regex

      A regular expression

    returns

      A sequence of Path objects corresponding to the identified directories.

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

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

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

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

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15. #### def loadAlignments(filePath: String, projection: Option[Schema] = None, filePath2Opt: Option[String] = None, recordGroupOpt: Option[String] = None, stringency: ValidationStringency = ValidationStringency.STRICT): AlignmentRecordRDD

    Loads alignments from a given path, and infers the input type.

    Loads alignments from a given path, and infers the input type.

    This method can load:

    * AlignmentRecords via Parquet (default) * SAM/BAM (.sam, .bam) * FASTQ (interleaved, single end, paired end) (.ifq, .fq/.fastq) * FASTA (.fa, .fasta) * NucleotideContigFragments via Parquet (.contig.adam)

    As hinted above, the input type is inferred from the file path extension.

    filePath

      Path to load data from.

    projection

      The fields to project; ignored if not Parquet.

    filePath2Opt

      The path to load a second end of FASTQ data from. Ignored if not FASTQ.

    recordGroupOpt

      Optional record group name to set if loading FASTQ.

    stringency

      Validation stringency used on FASTQ import/merging.

    returns

      Returns an AlignmentRecordRDD which wraps the RDD of reads, sequence dictionary representing the contigs these reads are aligned to if the reads are aligned, and the record group dictionary for the reads if one is available.

    See also

      loadFasta

      loadFastq

      loadInterleavedFastq

      loadParquetAlignments

      loadBam

16. #### def loadAlignmentsFromPaths(paths: Seq[Path]): AlignmentRecordRDD

    Takes a sequence of Path objects and loads alignments using that path.

    Takes a sequence of Path objects and loads alignments using that path.

    This infers the type of each path, and thus can be used to load a mixture of different files from disk. I.e., if you want to load 2 BAM files and 3 Parquet files, this is the method you are looking for!

    The RDDs obtained from loading each file are simply unioned together, while the record group dictionaries are naively merged. The sequence dictionaries are merged in a way that dedupes the sequence records in each dictionary.

    paths

      The locations of the files to load.

    returns

      Returns an AlignmentRecordRDD which wraps the RDD of reads, sequence dictionary representing the contigs these reads are aligned to if the reads are aligned, and the record group dictionary for the reads if one is available.

    See also

      loadAlignments

17. #### def loadBED(filePath: String): RDD[Feature]

18. #### def loadBam(filePath: String): AlignmentRecordRDD

    Loads a SAM/BAM file.

    Loads a SAM/BAM file.

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

    filePath

      Path to the file on disk.

    returns

      Returns an AlignmentRecordRDD which wraps the RDD of reads, sequence dictionary representing the contigs these reads are aligned to if the reads are aligned, and the record group dictionary for the reads if one is available.

    See also

      loadAlignments

19. #### def loadFasta(filePath: String, fragmentLength: Long): RDD[NucleotideContigFragment]

20. #### def loadFastq(filePath1: String, filePath2Opt: Option[String], recordGroupOpt: Option[String] = None, stringency: ValidationStringency = ValidationStringency.STRICT): AlignmentRecordRDD

21. #### def loadFeatures(filePath: String, projection: Option[Schema] = None): RDD[Feature]

22. #### def loadFragments(filePath: String): RDD[Fragment]

23. #### def loadGTF(filePath: String): RDD[Feature]

24. #### def loadGenes(filePath: String, projection: Option[Schema] = None): RDD[Gene]

25. #### def loadGenotypes(filePath: String, projection: Option[Schema] = None, sd: Option[SequenceDictionary] = None): RDD[Genotype]

26. #### def loadIndexedBam(filePath: String, viewRegion: ReferenceRegion): RDD[AlignmentRecord]

    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.

    filePath

      The path to the input data. Currently this path must correspond to a single Bam file. The bam index file associated needs to have the same name.

    viewRegion

      The ReferenceRegion we are filtering on

27. #### def loadInterleavedFastq(filePath: String): AlignmentRecordRDD

28. #### def loadInterleavedFastqAsFragments(filePath: String): RDD[Fragment]

29. #### def loadIntervalList(filePath: String): RDD[Feature]

30. #### def loadNarrowPeak(filePath: String): RDD[Feature]

31. #### def loadPairedFastq(filePath1: String, filePath2: String, recordGroupOpt: Option[String], stringency: ValidationStringency): AlignmentRecordRDD

32. #### def loadParquet[T](filePath: String, predicate: Option[FilterPredicate] = None, projection: Option[Schema] = None)(implicit ev1: (T) ⇒ SpecificRecord, ev2: Manifest[T]): RDD[T]

    This method will create a new RDD.

    This method will create a new RDD.

    T

      The type of records to return

    filePath

      The path to the input data

    predicate

      An optional pushdown predicate to use when reading the data

    projection

      An option projection schema to use when reading the data

    returns

      An RDD with records of the specified type

33. #### def loadParquetAlignments(filePath: String, predicate: Option[FilterPredicate] = None, projection: Option[Schema] = None): AlignmentRecordRDD

    Loads alignment data from a Parquet file.

    Loads alignment data from a Parquet file.

    filePath

      The path of the file to load.

    predicate

      An optional predicate to push down into the file.

    projection

      An optional schema designating the fields to project.

    returns

      Returns an AlignmentRecordRDD which wraps the RDD of reads, sequence dictionary representing the contigs these reads are aligned to if the reads are aligned, and the record group dictionary for the reads if one is available.

    Note

      The sequence dictionary is read from an avro file stored at filePath.seqdict and the record group dictionary is read from an avro file stored at filePath.rgdict. These files are pure avro, not Parquet.

    See also

      loadAlignments

34. #### def loadParquetContigFragments(filePath: String, predicate: Option[FilterPredicate] = None, projection: Option[Schema] = None): RDD[NucleotideContigFragment]

35. #### def loadParquetFeatures(filePath: String, predicate: Option[FilterPredicate] = None, projection: Option[Schema] = None): RDD[Feature]

36. #### def loadParquetFragments(filePath: String, predicate: Option[FilterPredicate] = None, projection: Option[Schema] = None): RDD[Fragment]

37. #### def loadParquetGenotypes(filePath: String, predicate: Option[FilterPredicate] = None, projection: Option[Schema] = None): RDD[Genotype]

38. #### def loadParquetVariantAnnotations(filePath: String, predicate: Option[FilterPredicate] = None, projection: Option[Schema] = None): RDD[DatabaseVariantAnnotation]

39. #### def loadParquetVariants(filePath: String, predicate: Option[FilterPredicate] = None, projection: Option[Schema] = None): RDD[Variant]

40. #### def loadReferenceFile(filePath: String, fragmentLength: Long): ReferenceFile

41. #### def loadSequence(filePath: String, projection: Option[Schema] = None, fragmentLength: Long = 10000): RDD[NucleotideContigFragment]

42. #### def loadUnpairedFastq(filePath: String, recordGroupOpt: Option[String] = None, setFirstOfPair: Boolean = false, setSecondOfPair: Boolean = false, stringency: ValidationStringency = ValidationStringency.STRICT): AlignmentRecordRDD

43. #### def loadVariantAnnotations(filePath: String, projection: Option[Schema] = None, sd: Option[SequenceDictionary] = None): RDD[DatabaseVariantAnnotation]

44. #### def loadVariants(filePath: String, projection: Option[Schema] = None, sd: Option[SequenceDictionary] = None): RDD[Variant]

45. #### def loadVcf(filePath: String, sd: Option[SequenceDictionary]): RDD[VariantContext]

46. #### def loadVcfAnnotations(filePath: String, sd: Option[SequenceDictionary] = None): RDD[DatabaseVariantAnnotation]

47. #### def log: Logger

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

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

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

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

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

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

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54. #### def logName: String

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

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

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

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

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

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

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

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62. #### val sc: SparkContext

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

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

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

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

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

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