Packages

case class Variants(rc: RuntimeETLContext, participantId: Column = col("participant_id"), affectedStatus: Column = col("affected_status"), filterSnv: Option[Column] = Some(col("has_alt")), snvDatasetId: String, splits: Seq[OccurrenceSplit], extraAggregations: Seq[Column] = Nil, checkpoint: Boolean = false, spliceAi: Boolean = true, destinationDataSetId: String = "enriched_variants") extends SimpleSingleETL with Product with Serializable

This ETL create an aggregated table on occurrences of SNV variants. Occurrences are aggregated by calculating the frequencies specified in parameter frequencies. The table is enriched with information from other datasets such as genes, dbsnp, clinvar, 1000 genomes, topmed_bravo, gnomad_genomes_v2, gnomad_exomes_v2, gnomad_genomes_v3.

rc

the etl context

participantId

column used to distinct participants in order to calculate total number of participants (pn) and total allele number (an)

affectedStatus

column used to calculate frequencies for affected / unaffected participants

snvDatasetId

the id of the dataset containing the SNV variants

extraAggregations

extra aggregations to be computed when grouping occurrences by locus. Will be added to the root of the data

spliceAi

bool indicating whether or not to join variants with SpliceAI. Defaults to true.

Linear Supertypes
Serializable, Serializable, Product, Equals, SingleETL[LocalDateTime, SimpleConfiguration], ETL[LocalDateTime, SimpleConfiguration], AnyRef, Any
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Inherited
  1. Variants
  2. Serializable
  3. Serializable
  4. Product
  5. Equals
  6. SingleETL
  7. ETL
  8. AnyRef
  9. Any
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Visibility
  1. Public
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Instance Constructors

  1. new Variants(rc: RuntimeETLContext, participantId: Column = col("participant_id"), affectedStatus: Column = col("affected_status"), filterSnv: Option[Column] = Some(col("has_alt")), snvDatasetId: String, splits: Seq[OccurrenceSplit], extraAggregations: Seq[Column] = Nil, checkpoint: Boolean = false, spliceAi: Boolean = true, destinationDataSetId: String = "enriched_variants")

    rc

    the etl context

    participantId

    column used to distinct participants in order to calculate total number of participants (pn) and total allele number (an)

    affectedStatus

    column used to calculate frequencies for affected / unaffected participants

    snvDatasetId

    the id of the dataset containing the SNV variants

    extraAggregations

    extra aggregations to be computed when grouping occurrences by locus. Will be added to the root of the data

    spliceAi

    bool indicating whether or not to join variants with SpliceAI. Defaults to true.

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. val affectedStatus: Column
  5. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  6. val checkpoint: Boolean
  7. val clinvar: DatasetConf
    Attributes
    protected
  8. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native() @HotSpotIntrinsicCandidate()
  9. implicit val conf: Configuration
    Definition Classes
    ETL
  10. val cosmic: DatasetConf
    Attributes
    protected
  11. val dbsnp: DatasetConf
    Attributes
    protected
  12. val defaultCurrentValue: LocalDateTime
    Definition Classes
    ETL
  13. def defaultRepartition: (DataFrame) ⇒ DataFrame
    Definition Classes
    ETL
  14. def defaultSampling: PartialFunction[String, (DataFrame) ⇒ DataFrame]
    Definition Classes
    ETL
  15. val destinationDataSetId: String
  16. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  17. val extraAggregations: Seq[Column]
  18. def extract(lastRunValue: LocalDateTime = minValue, currentRunValue: LocalDateTime = LocalDateTime.now()): Map[String, DataFrame]

    Reads data from a file system and produces a Map[DatasetConf, DataFrame].

    Reads data from a file system and produces a Map[DatasetConf, DataFrame]. This method should avoid transformation and joins but can implement filters in order to make the ETL more efficient.

    returns

    all the data needed to pass to the transform method and produce the desired output.

    Definition Classes
    Variants → ETL
  19. val filterSnv: Option[Column]
  20. val genes: DatasetConf
    Attributes
    protected
  21. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  22. def getLastRunValue(ds: DatasetConf): LocalDateTime

    If possible, fetch the last run value from the dataset passed in argument.

    If possible, fetch the last run value from the dataset passed in argument. Usually a date or an id.

    ds

    dataset

    returns

    the last run value or the minValue

    Definition Classes
    ETL
  23. val gnomad_exomes_v2: DatasetConf
    Attributes
    protected
  24. val gnomad_genomes_v2: DatasetConf
    Attributes
    protected
  25. val gnomad_genomes_v3: DatasetConf
    Attributes
    protected
  26. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  27. final def load(data: Map[String, DataFrame], lastRunValue: LocalDateTime, currentRunValue: LocalDateTime): Map[String, DataFrame]

    Loads the output data into a persistent storage.

    Loads the output data into a persistent storage. The output destination can be any of: object store, database or flat files...

    data

    output data produced by the transform method.

    Definition Classes
    SingleETL → ETL
  28. def loadDataset(df: DataFrame, ds: DatasetConf): DataFrame
    Definition Classes
    ETL
  29. def loadSingle(data: DataFrame, lastRunValue: LocalDateTime = minValue, currentRunValue: LocalDateTime = defaultCurrentValue): DataFrame
    Definition Classes
    SingleETL
  30. val log: Logger
    Definition Classes
    ETL
  31. val mainDestination: DatasetConf
    Definition Classes
    Variants → ETL
  32. val minValue: LocalDateTime
    Definition Classes
    ETL
  33. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  34. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  35. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  36. val participantId: Column
  37. def publish(): Unit

    OPTIONAL - Contains all actions needed to be done in order to make the data available to users like creating a view with the data.

    OPTIONAL - Contains all actions needed to be done in order to make the data available to users like creating a view with the data.

    Definition Classes
    ETL
  38. val rc: RuntimeETLContext
  39. def replaceWhere: Option[String]

    replaceWhere is used in for OverWriteStaticPartition load.

    replaceWhere is used in for OverWriteStaticPartition load. It avoids to compute dataframe to infer which partitions to replace. Most of the time, these partitions can be inferred statically. Always prefer that to dynamically overwrite partitions.

    Definition Classes
    ETL
  40. def reset(): Unit

    Reset the ETL by removing the destination dataset.

    Reset the ETL by removing the destination dataset.

    Definition Classes
    ETL
  41. def run(lastRunValue: Option[LocalDateTime] = None, currentRunValue: Option[LocalDateTime] = None): Map[String, DataFrame]

    Entry point of the etl - execute this method in order to run the whole ETL

    Entry point of the etl - execute this method in order to run the whole ETL

    Definition Classes
    ETL
  42. def sampling: PartialFunction[String, (DataFrame) ⇒ DataFrame]

    Logic used when the ETL is run as a RunStep.sample step.

    Logic used when the ETL is run as a RunStep.sample step.

    Definition Classes
    ETL
  43. val snvDatasetId: String
  44. implicit val spark: SparkSession
    Definition Classes
    ETL
  45. val spliceAi: Boolean
  46. val spliceai_indel: DatasetConf
    Attributes
    protected
  47. val spliceai_snv: DatasetConf
    Attributes
    protected
  48. val splits: Seq[OccurrenceSplit]
  49. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  50. val thousand_genomes: DatasetConf
    Attributes
    protected
  51. def toMain(df: ⇒ DataFrame): Map[String, DataFrame]
    Definition Classes
    ETL
  52. val topmed_bravo: DatasetConf
    Attributes
    protected
  53. final def transform(data: Map[String, DataFrame], lastRunValue: LocalDateTime = minValue, currentRunValue: LocalDateTime = defaultCurrentValue): Map[String, DataFrame]

    Takes a Map[DatasetConf, DataFrame] as input and applies a set of transformations to it to produce the ETL output.

    Takes a Map[DatasetConf, DataFrame] as input and applies a set of transformations to it to produce the ETL output. It is recommended to not read any additional data but to use the extract() method instead to inject input data.

    data

    input data

    Definition Classes
    SingleETL → ETL
  54. def transformSingle(data: Map[String, DataFrame], lastRunValue: LocalDateTime = minValue, currentRunValue: LocalDateTime = LocalDateTime.now()): DataFrame

    Takes a DataFrame as input and applies a set of transformations to it to produce the ETL output.

    Takes a DataFrame as input and applies a set of transformations to it to produce the ETL output. It is recommended to not read any additional data but to use the extract() method instead to inject input data.

    data

    input data

    Definition Classes
    Variants → SingleETL
  55. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  56. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  57. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Deprecated Value Members

  1. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] ) @Deprecated
    Deprecated

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from SingleETL[LocalDateTime, SimpleConfiguration]

Inherited from ETL[LocalDateTime, SimpleConfiguration]

Inherited from AnyRef

Inherited from Any

Ungrouped