View source: R/normalize.invariantset.R
normalize.invariantset | 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 |
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 |
specifies how to determine the baseline array. |
type |
a string specifying how the normalization should be applied. See details for more. |
verbose |
logical indicating printing 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.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.