diffExpR: Function for RNASeq Differential Expression
In HTDA: HTDA (High Throughput Data Analysis)

Description Usage Arguments Details Value Examples

Identified differentially expressed genes from two different condition

1	diffExpR(object, comparison = comparison, ...)

`object`	Quantified data obtained from rnaseqProcess function
`comparison`	name of comparing conditions, currently working is "Control-Treated"
`...`

The function based on the following flow

1. First extrcat the quantified data from PreProcessData S4 class objec t. 2. Extract the corresponding phenodata information. 3. Use the Limma functionality for creating design and contrast matrix 4. calculate differential expression

Return an object of S4 class PreProcessData.

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (object, comparison = comparison, ...) 
{
    state <- object@phenoData$condition
    f <- factor(state)
    design <- model.matrix(~0 + f)
    colnames(design) <- levels(f)
    pdf("Mean-varianceTrend.pdf")
    linmod <- limma::voom(object@qData, design, plot = TRUE)
    dev.off()
    fit <- limma::lmFit(linmod, design)
    contrast.matrix <- limma::makeContrasts(comparison, levels = design)
    fit <- limma::contrasts.fit(fit, contrast.matrix)
    ebayes <- limma::eBayes(fit)
    object@diffExp <- limma::topTable(ebayes, number = Inf)
    object@DFsummary <- data.frame(summary(limma::decideTests(fit)))
    new("PreProcessData", object)
  }