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Justin Borevitz
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170
@justin-borevitz-1002
Last seen 10.0 years ago
It is adhoc and I?ve only thought a little about how to do regional
correction more systematically (the way field studies correct for
wet/soil
spots locally effecting growth). Something like the xy pos of the
feature
is in the model for differential expression. This would be quite
computational and normalization wouldn?t come in the standard way
either.
So bg.correct from RMA is not spatial correction. It doesn?t consider
the XY
pos. It does a global per array correction for each array, but
assumes
normal noise and exponential RNA signal. Ben Bolstad was going to
model
normal noise and normal signal for DNA, but I don?t think he has done
it
yet, no pressure Ben... We might be in lower demand however SNP
arrays
might benefit tremendously from normal/normal. SNP arrays do have
their own
correction method with the oligo package though and I?m not sure if
anyone
tired this for RNA or if it makes sense even.
Yes quantile normalization is the next step and good luck with the
maize
SFPs, if you use whole genome random labeling I guess it will be
noisily but
possible with enough replicates. The deletions sure should be.
Otherwise a
complexity reduction eg AFPL etc might help, see our Barley paper
http://genomebiology.com/2005/6/6/r54
-----
Justin Borevitz
http://naturalsystems.org/lab
________________________________________
From: Michael Gore [mailto:mag87@cornell.edu]
Sent: Friday, October 13, 2006 6:08 PM
To: 'Justin Borevitz'
Subject: Spatial Correction
Hi Justin,
?
I have a quick question for you.? How does one determine the
appropriate
array size and filter size for spatial correction?
?
Is spatial correction comparable to RMA, followed by Quantiles?
?
Right now, we are doing SFP with the Affy Maize GeneChip.
?
Thanks,
?
Mike
?
?
library(affy)
read.cel <- function(cel.file, cel.image = F, spatial.correct=T,
median=F,
?????????????????????????????????? array.size = 712, filter.size = 51,
jpeg.save=T){
?