Usage
normalize.quantiles.robust(x,copy=TRUE,weights=NULL, remove.extreme=c("variance","mean","both","none"), n.remove=1,use.median=FALSE,use.log2=FALSE)
Arguments
x
A matrix of intensities, columns are chips, rows are probes
copy
Make a copy of matrix before normalizing. Usually safer to
work with a copy
weights
A vector of weights, one for each chip
remove.extreme
If weights is null, then this will be used for
determining which chips to remove from the calculation of the
normalization distribution, See details for more info
n.remove
number of chips to remove
use.median
if TRUE use the median to compute normalization
chip, otherwise uses a weighted mean
use.log2
work on log2 scale. This means we will be using the
geometric mean rather than ordinary mean