affiXcanBs: Fit linear models and compute ANOVA p-values

Description Usage Arguments Value Examples

View source: R/AffiXcan.R

Description

Fit linear models and compute ANOVA p-values

Usage

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affiXcanBs(
  exprMatrix,
  assay,
  regionAssoc,
  pca,
  cov = NULL,
  BPPARAM = bpparam(),
  trainingSamples
)

Arguments

exprMatrix

A SummarizedExperiment object containing expression data

assay

A string with the name of the object in SummarizedExperiment::assays(exprMatrix) that contains expression values

regionAssoc

A data.frame with the associations between regulatory regions and expressed genes, and with colnames = c("REGULATORY_REGION", "EXPRESSED_REGION")

pca

A list, which is the returningObject$pca from affiXcanPca()

cov

Optional; a data.frame with covariates values for the population structure where the columns are the PCs and the rows are the individual IDs; default is NULL

BPPARAM

A BiocParallelParam object. Default is bpparam(). For details on BiocParallelParam virtual base class see browseVignettes("BiocParallel")

trainingSamples

A vector of strings. The identifiers (e.g. row names of MultiAssayExperiment objects from tbaPaths) of the samples that have to be considered in the training phase, and not used for the cross-validation

Value

A list containing lists named as the EXPRESSED_REGIONS found in the param regionAssoc. Each of these lists contain three objects:

Examples

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if (interactive()) {
data(exprMatrix)
data(trainingCovariates)
data(regionAssoc)

tbaPaths <- system.file("extdata","training.tba.toydata.rds",
package="AffiXcan")
regionsCount <- overlookRegions(tbaPaths)
assay <- "values"

sampleNames <- colnames(exprMatrix)
nSamples <- length(sampleNames)
sampGroups <- subsetKFold(k=5, n=nSamples)
for (i in seq(length(sampGroups))) {
     sampGroups[[i]] <- colnames(exprMatrix)[sampGroups[[i]]]
}

testingSamples <- sampGroups[[1]]
trainingSamples <- sampleNames[!sampleNames %in% testingSamples]

pca <- affiXcanPca(tbaPaths=tbaPaths, varExplained=80, scale=TRUE,
regionsCount=regionsCount, trainingSamples=trainingSamples)

bs <- affiXcanBs(exprMatrix=exprMatrix, assay=assay, regionAssoc=regionAssoc,
pca=pca, cov=trainingCovariates, trainingSamples=trainingSamples)
}

AffiXcan documentation built on Nov. 8, 2020, 8:07 p.m.