Covariate Residualization Settings

What is regressed out of the phenotype and genotype before fitting. Shared by fineMappingPipeline and twasWeightsPipeline, which hold the same four settings.

fineMappingPipeline's usePCA / nPCs are not here. They do not residualize anything: they PCA-reduce a multi-trait context's phenotype matrix and fine-map each top principal component as a trait. That is an analysis mode, a sibling of the univariate and multivariate dispatch paths, not a covariate setting.

Usage

ResidualizationParam(
  phenotypeCovariates = NULL,
  genotypeCovariates = NULL,
  residualizePhenotype = NULL,
  residualizeGenotype = NULL,
  scaleResiduals = NULL,
  covariateNaAction = NULL
)

Arguments

phenotypeCovariates

Covariates to residualize the phenotype on, or NULL (default) for the dataset's own.

genotypeCovariates

Covariates to residualize the genotype on, or NULL (default) for the dataset's own.

residualizePhenotype

Logical. Residualize on the phenotype covariates. NULL (default) means unset, which the accessors read as TRUE.

residualizeGenotype

Logical. Residualize on the genotype covariates. NULL (default) means unset, read as TRUE.

scaleResiduals

Logical. Scale each residual column to unit variance, which is what puts a fitted effect on the standardized genotype scale. NULL (default) means unset, and the accessors fall back to the dataset's own scaleResiduals slot (itself TRUE by default) — so this is the per-call override of a per-object default, and the only knob the pipelines need: it reaches residualizedGenotypes already, which is the one point every individual-level fit draws its genotypes through.

covariateNaAction

How missing covariate values are handled when the design is assembled: "impute" or "drop". NULL (default) leaves the accessor's own default in place.

Value

A ResidualizationParam object, a MethodParam.

Summary-statistics inputs

A QtlSumStats / GwasSumStats input carries no genotypes or covariates, so nothing here applies and the whole bundle is ignored — not refused.

That is the opposite of CrossValidationParam, which is refused on those inputs (fineMappingPipeline(QtlSumStats, crossValidation = ...) errors). The difference is the default: CV is off unless asked for (folds = 0), so a non-default value on a summary-statistics run is an explicit request for something impossible. Residualization is on by default (residualizePhenotype and residualizeGenotype are both TRUE), so refusing a non-default would reject the default bundle and force every sumstats caller to unset it.

One bundle therefore travels to either input kind unchanged, the same way CrossValidationParam's weightMethods / maxVariants are carried but ignored by fineMappingPipeline.

Examples

ResidualizationParam(residualizeGenotype = FALSE)
#> <ResidualizationParam>
#>   residualizeGenotype      FALSE
#>   unset: phenotypeCovariates, genotypeCovariates, residualizePhenotype, scaleResiduals, covariateNaAction