limmaAnalyze {InPAS} | R Documentation

## 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

### Author(s)

Jianhong Ou

### 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)

[Package InPAS version 1.18.0 Index]