affiXcanBs {AffiXcan} | R Documentation |
Fit a linear model and compute ANOVA p value
affiXcanBs(exprMatrix, assay, regionAssoc, pca, cov, BPPARAM = bpparam())
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$pca from affiXcanPca() |
cov |
A data.frame with covariates values for the population structure |
BPPARAM |
A BiocParallelParam object. Default is bpparam(). For details on BiocParallelParam virtual base class see browseVignettes("BiocParallel") |
A list containing lists named as the REGULATORY_REGIONS found in the param regionAssoc that have a correspondent name in the param pca. Each of these lists contains three objects:
coefficients: An object containing the coefficients of the principal components used in the model, completely similar to the "coefficients" from the results of lm()
pval: The uncorrected anova pvalue of the model, retrieved from anova(model, modelReduced, test="F")$'Pr(>F)'[2]
r.sq: The coefficient of determination between the real total expression values and the imputed GReX, retrived from summary(model)$r.squared
correctedP: The p value after the benjamini-hochberg correction for multiple testing, retrived using p.adjust(pvalues, method="BH")
if (interactive()) { trainingTbaPaths <- system.file("extdata","training.tba.toydata.rds", package="AffiXcan") data(exprMatrix) data(regionAssoc) data(trainingCovariates) assay <- "values" training <- affiXcanTrain(exprMatrix=exprMatrix, assay=assay, tbaPaths=trainingTbaPaths, regionAssoc=regionAssoc, cov=trainingCovariates, varExplained=80, scale=TRUE) pca <- training$pca bs <- affiXcanBs(exprMatrix=exprMatrix, assay=assay, regionAssoc=regionAssoc, pca=pca, cov=trainingCovariates) }