[BioC] normalizing with different RNAdeg slopes
tnayar at bcgsc.ca
Thu Apr 20 23:42:18 CEST 2006
Density plots look like they fall into 2-3 groups; with a main peak
about 6.5 (n=~12), and then 4-5 samples at 7.
I'm running the GCRMA/ PCA at the moment.
From: James W. MacDonald [mailto:jmacdon at med.umich.edu]
Sent: Thursday, April 20, 2006 1:10 PM
To: Tarun Nayar
Cc: bioconductor at stat.math.ethz.ch
Subject: Re: [BioC] normalizing with different RNAdeg slopes
Tarun Nayar wrote:
> Hi all,
> I'm dealing with a number of human lymphoma samples, some of which
> have been in freezer storage for up to 20 years. The samples have been
> run on HGU133Aplus2 chips, and have a wide range of 5' to 3'
> slopes (as determined by the RNAdeg function), ranging from 3.8 to
> My understanding is that normalizing chips with such a wide range of
> slopes could lead to innacuracies downstream.
> 1) Are these slopes too different to allow for the chips to be
> normalized together?
It's possible, but I find that the density plots tend to dictate better
how well things will normalize. What do those look like?
> 2) if not, how would one go about working around these slope
> differences? Our PI is dead set on extracting any info possible from
> these 'rare' samples.
I would run RMA or GCRMA on the data, and then do a PCA plot to see how
replicates are grouping. Clusters of replicated samples usually indicate
that samples are (in general) fairly similar, whereas widely dispersed
replicate samples usually indicate that there is a lot of variability
that may not be biological in nature.
> many thanks
> Tarun Nayar Genome Sciences Centre Vancouver, BC
> [[alternative HTML version deleted]]
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James W. MacDonald, M.S.
Affymetrix and cDNA Microarray Core
University of Michigan Cancer Center
1500 E. Medical Center Drive
Ann Arbor MI 48109
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