tecVarEstim function

Technical Variance Estimation

Estimate technical variance by using voom-trend. The code is derived from voom function in limma package

tecVarEstim(counts, design = NULL, lib.size = NULL, span = 0.5, ...)

Arguments

• counts: a DGEList object
• design: design matrix with samples in row and coefficient(s) to be estimated in column
• lib.size: numeric vector containing total library sizes for each sample
• span: width of the lowess smoothing window as a proportion
• ...: other arguments are passed to lmFit.

Returns

an TecVarList object with the following components: - targets: matrix containing covariables, library sizes and normalization foctors of each sample

• design: design matrix with samples in row and covariable(s) to be estimated in column

• logcpm: logcpm values of each gene and each sample

• tecVar: estimated techical variance of each gene and each sample

Examples

expr <- data.frame(t(sapply(1:1000,function(x)rnbinom(20,mu=500,size=50))))
group <- c(rep("A",10),rep("B",10))
design <- model.matrix(~group, data = expr)
dge <- DGEList(counts=expr, group=group)
dge <- calcNormFactors(dge)
tecVarEstim(dge,design)