[BioC] normalization and outlier detection

[echang4 at life.uiuc.edu]

Hi everyone,

I am new to analysis of microarrays, so I'm sorry if the answers to my
questions should be obvious. But I would really appreciate any inputs... I
should also mention that I am a biology grad student and not a
statistician.

1) My question is regarding the normalization procedures for Affymetrix
U133 arrays. It seems like the best way to normalize arrays is by using
the RMA method (better than dChip or Affymetrix's Tukey's biweight?) I
would like to use quantile normalization between arrays, so I have been
using Bolstad's RMAExpress to analyze my .CEL files and then examining the
residual images. If I encounter some horribly-looking arrays, is it wise
to leave those arrays out of the subsequent analysis? or is there some way
of removing the outliers (like dChip) and then apply the RMA procedure
again? Or is that unnecessary?

2) Is there some sort of guideline to determine if the RNA was of low
quality (due to experimenter's error etc) or if the
labelling/hybridization was done incorrectly?

3) What is the difference between limma and RMA? Are there any
publications discussing the merit of one method over the other?


Thank you very much,
Edmund Chang
Graduate student- Physiology
University of Illinois, Urbana-Champaign
ecc0101 at yahoo.com
217-333-7836