Object

io.projectglow.sql.expressions

LinearRegressionGwas

Related Doc: package expressions

Permalink

object LinearRegressionGwas extends GlowLogging

Linear Supertypes
GlowLogging, LazyLogging, LazyLogging, Logging, AnyRef, Any
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. LinearRegressionGwas
  2. GlowLogging
  3. LazyLogging
  4. LazyLogging
  5. Logging
  6. AnyRef
  7. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

Value Members

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

    Permalink
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int

    Permalink
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean

    Permalink
    Definition Classes
    AnyRef → Any
  4. final def asInstanceOf[T0]: T0

    Permalink
    Definition Classes
    Any
  5. def clone(): AnyRef

    Permalink
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  6. final def eq(arg0: AnyRef): Boolean

    Permalink
    Definition Classes
    AnyRef
  7. def equals(arg0: Any): Boolean

    Permalink
    Definition Classes
    AnyRef → Any
  8. def finalize(): Unit

    Permalink
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  9. final def getClass(): Class[_]

    Permalink
    Definition Classes
    AnyRef → Any
  10. def hashCode(): Int

    Permalink
    Definition Classes
    AnyRef → Any
  11. final def isInstanceOf[T0]: Boolean

    Permalink
    Definition Classes
    Any
  12. def linearRegressionGwas(genotypes: DenseVector[Double], phenotypes: DenseVector[Double], covariateQR: CovariateQRContext): InternalRow

    Permalink
  13. lazy val logger: Logger

    Permalink
    Attributes
    protected
    Definition Classes
    LazyLogging → Logging
  14. final def ne(arg0: AnyRef): Boolean

    Permalink
    Definition Classes
    AnyRef
  15. final def notify(): Unit

    Permalink
    Definition Classes
    AnyRef
  16. final def notifyAll(): Unit

    Permalink
    Definition Classes
    AnyRef
  17. def runRegression(genotypes: DenseVector[Double], phenotypes: DenseVector[Double], covariateQRContext: CovariateQRContext): RegressionStats

    Permalink

    Fits a linear regression model to a single variant.

    Fits a linear regression model to a single variant.

    The algorithm here is based off the linear regression algorithm used in Hail, as described in https://arxiv.org/pdf/1901.09531.pdf.

    At a high level, we compute the QR decomposition once per covariate matrix, and use Q to project the genotypes into the orthogonal complement of the column space of the covariate matrix. Then we use a simple algorithm for linear regression with one independent variable to solve for relevant output (https://en.wikipedia.org/wiki/Simple_linear_regression#Numerical_example).

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

    Permalink
    Definition Classes
    AnyRef
  19. def toString(): String

    Permalink
    Definition Classes
    AnyRef → Any
  20. final def wait(): Unit

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  21. final def wait(arg0: Long, arg1: Int): Unit

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  22. final def wait(arg0: Long): Unit

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from GlowLogging

Inherited from LazyLogging

Inherited from LazyLogging

Inherited from Logging

Inherited from AnyRef

Inherited from Any

Ungrouped