Batch effects are removed using a two-stage regression approach.
Usage
ber(Y, b, covariates = NULL, stage2=FALSE)
Arguments
Y
A matrix with $n$ rows and $g$ columns, where $n$ is the number of objects and $g$
is the number of variables. In the case of gene expression data, columns correspond
to genes (probe sets) and rows to samples.
b
A vector of class factor with the element in position $i$ ($i=1,\ldots,n$) representing
the batch from which observation $i$ belongs to.
covariates
An object of class data.frame where each column corresponds to a quantitative
variable (of class numeric) or a qualitative variable (of class factor).
stage2
A logical value indicating if the covariates have to be considered only in handling the
location effects (stage2 = F) or also for the scale effects (stage2 = T).
Value
A matrix of adjusted data with $n$ rows and $g$ columns.
Details
In this implementation NA values are not allowed.
References
M. Giordan. A two-stage procedure for the removal of batch effects in microarray studies