tecVarEstim {BALLI} | R Documentation |
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, ...)
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. |
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 |
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)