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Arguments For The QTL Enrichment Estimator

Source: R/qtlEnrichmentPipeline.R
QtlEnrichmentParam.Rd

The algorithmic settings qtlEnrichment takes, as one checked bundle. Everything else that function accepts — the two data arguments, numThreads, seed, verbose, and the alignNames switch — is the pipeline's own business and is not settable here.

Usage

QtlEnrichmentParam(
  numGwas = NULL,
  piQtl = NULL,
  lambda = 1,
  impN = 25,
  doubleShrinkage = FALSE,
  besselCorrection = TRUE
)

Arguments

numGwas

Number of GWAS variants used to estimate piGwas. NULL (default) estimates it from the data, which is biased unless the outcome PIP vector really is genome-wide.

piQtl

Per-variant prior of being a causal QTL variant. NULL (default) estimates it from the data.

lambda

Shrinkage parameter, shrinking the enrichment estimate towards zero as in ridge regression. 0 applies no shrinkage. Default 1.0.

impN

Rounds of multiple imputation to draw QTL from. Default 25.

doubleShrinkage

Logical. Apply the double-shrinkage correction to the enrichment estimate. Default FALSE.

besselCorrection

Logical. Apply Bessel's correction when estimating the sampling variance. Default TRUE.

Value

A QtlEnrichmentParam object, a MethodParam.

Examples

QtlEnrichmentParam(lambda = 0, impN = 50)
#> <QtlEnrichmentParam>
#>   lambda                   0
#>   impN                     50
#>   doubleShrinkage          FALSE
#>   besselCorrection         TRUE
#>   unset: numGwas, piQtl