InPAS (version 1.4.4)

limmaAnalyze: use limma to analyze the PDUI

Description

use limma to analyze the PDUI

Usage

limmaAnalyze(UTR3eset, design, contrast.matrix, coef=1, robust=FALSE, ...)

Arguments

UTR3eset

an UTR3eSet object

design

the design matrix of the experiment, with rows corresponding to arrays and columns to coefficients to be estimated. Defaults to the unit vector meaning that the arrays are treated as replicates. see model.matrix

contrast.matrix

numeric matrix with rows corresponding to coefficients in fit and columns containing contrasts. May be a vector if there is only one contrast. see makeContrasts

coef

column number or column name specifying which coefficient or contrast of the linear model is of interest. see more topTable. default value: 1

robust

logical, should the estimation of the empirical Bayes prior parameters be robustified against outlier sample variances?

...

other arguments are passed to lmFit.

Value

fit results of eBayes by limma. It is an object of class MArrayLM containing everything found in fit. see eBayes

See Also

singleSampleAnalyze,singleGroupAnalyze, fisher.exact.test

Examples

    library(limma)
    path <- file.path(find.package("InPAS"), "extdata")
    load(file.path(path, "eset.MAQC.rda"))
    tags <- colnames(eset$PDUI.log2)
    g <- factor(gsub("\\..*$", "", tags))
    design <- model.matrix(~-1+g)
    colnames(design) <- c("Brain", "UHR")
    contrast.matrix <- makeContrasts(contrasts="Brain-UHR",levels=design)
    res <- limmaAnalyze(eset, design, contrast.matrix)
    head(res)