normalize.invariantset {affy} | R Documentation |
Normalize arrays in an AffyBatch
using an invariant set.
normalize.AffyBatch.invariantset(abatch, prd.td=c(0.003, 0.007), verbose=FALSE,baseline.type=c("mean","median","pseudo-mean","pseudo-median"),type=c("separate","pmonly","mmonly","together")) normalize.invariantset(data, ref, prd.td=c(0.003,0.007))
abatch |
an AffyBatch |
data |
a vector of intensities on a chip (to normalize to the reference). |
ref |
a vector of reference intensities. |
prd.td |
cutoff parameter (details in the bibliographic reference) |
baseline.type |
Specify how to determine the baseline array |
type |
A string specifying how the normalization should be applied. See details for more. |
verbose |
A flag to have a dumps throughout the normalization |
The set of invariant intensities between data
and
ref
is found through an iterative
process (based on the respective ranks the intensities).
This set of intensities is used to generate a normalization curve by
smoothing.
The type
argument should be one of
"separate","pmonly","mmonly","together"
which indicates whether
to normalize only one probe type (PM,MM) or both together or separately.
Respectively a AffyBatch
of normalized objects, or
a vector of normalized intensities, with an attribute "invariant.set"
holding the indexes of the 'invariant' intensities.
L. Gautier <laurent@cbs.dtu.dk> (Thanks to Cheng Li for the discussions about the algorithm.)
Cheng Li and Wing Hung Wong, Model-based analysis of oligonucleotides arrays: model validation, design issues and standard error application. Genome Biology 2001, 2(8):research0032.1-0032.11
normalize
to normalize AffyBatch
objects.