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implicit class GenomicOperations extends AnyRef

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Instance Constructors

  1. new GenomicOperations(df: DataFrame)

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  1. final def !=(arg0: Any): Boolean
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  8. final def getClass(): Class[_]
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    @native() @HotSpotIntrinsicCandidate()
  9. def groupByLocus(): RelationalGroupedDataset
  10. def hashCode(): Int
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    @native() @HotSpotIntrinsicCandidate()
  11. val isHeterozygote: Column
  12. final def isInstanceOf[T0]: Boolean
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  13. val isSexualGenotype: Column
  14. def joinAndMerge(other: DataFrame, outputColumnName: String, joinType: String = "inner"): DataFrame
  15. def joinByLocus(other: DataFrame, joinType: String): DataFrame
  16. final def ne(arg0: AnyRef): Boolean
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  17. val normalizeCall: (Column) ⇒ Column
  18. final def notify(): Unit
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  19. final def notifyAll(): Unit
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    @native() @HotSpotIntrinsicCandidate()
  20. def selectLocus(cols: Column*): DataFrame
  21. val strictAutosomalTransmissions: List[(Array[Int], Array[Int], Array[Int], Boolean, Boolean, String)]
  22. val strictSexualTransmissions: List[(String, Array[Int], Array[Int], Array[Int], Boolean, Boolean, String)]
  23. final def synchronized[T0](arg0: ⇒ T0): T0
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  24. def toString(): String
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  25. final def wait(arg0: Long, arg1: Int): Unit
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  26. final def wait(arg0: Long): Unit
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  27. final def wait(): Unit
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  28. def withCombinedFrequencies(combined: String, prefix1: String, prefix2: String): DataFrame
  29. def withGenotypeTransmission(as: String, calls_name: String = "calls", gender_name: String = "gender", affected_status_name: String = "affected_status", father_calls_name: String = "father_calls", father_affected_status_name: String = "father_affected_status", mother_calls_name: String = "mother_calls", mother_affected_status_name: String = "mother_affected_status"): DataFrame
  30. def withNormalizedVariants(referenceGenomePath: String = ...): DataFrame
  31. def withParentalOrigin(as: String, fth_calls: Column, mth_calls: Column, MTH: String = "mother", FTH: String = "father"): DataFrame
  32. def withSplitMultiAllelic: DataFrame
  33. def withTransmissionPerLocus(locusColumnNames: Seq[String], transmissionColumnName: String, resultColumnName: String): DataFrame

    Compute transmission per locus given an existing column containing the transmission for this particular occurrence.

    Compute transmission per locus given an existing column containing the transmission for this particular occurrence.

    locusColumnNames

    list of locus columns

    transmissionColumnName

    name of the transmission column

    resultColumnName

    name of the resulting computation

    returns

    a dataframe with a new column containing the number of transmission per locus as a Map of transmission type -> count per type.

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  1. def finalize(): Unit
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