[BioC] Normalized microarray data and meta-analysis

Paul Leo p.leo at uq.edu.au
Thu Dec 18 01:06:19 CET 2008

No you don't need the raw data. However, do you need to check that
p-values were calculated the same way between experiments (will be
consistent if you use GEO processed data ) - what if one group did a
multiple testing correction and the other did not? Perhaps this is
already accounted for in the method you mentioned?

You may wish to consider if you will combine p-values at the gene level
the probe level. Most favour the probe level due to spline varients etc 

If you comparing cross array platforms then you need to be very careful;
a conservative appraoch is blast probe-to-probe across array platforms
to get the correspondence. Illumina provides "pre-basted" probes sets on
their ftp site for ilumina-affy comparisons. 

Best of luck.


-----Original Message-----
From: bioconductor-bounces at stat.math.ethz.ch
[mailto:bioconductor-bounces at stat.math.ethz.ch] On Behalf Of Mcmahon,
Sent: Thursday, 18 December 2008 8:31 AM
To: bioconductor at stat.math.ethz.ch
Subject: [BioC] Normalized microarray data and meta-analysis

Hello Bioconductor-inos,


I have more of a statistical/philosophical question regarding using raw
vs. normalized data in a microarray meta-analysis.  I've looked through
the bioconductor archives and have found some addressing of this issue,
but not exactly what I'm concerned with.  I don't mean to waste anyone's
time, but I was hoping I could get some help here.


I've performed a meta-analysis using the downloaded data from 3
different GEO data sets (GDS).  It is my understanding that these are
normalized data from the various microarray experiments.  Seems to me
that the  data from those normalized results are normally distributed,
those three experiments are perfectly comparable (if you think the
author's respective normalization approaches  were reasonable).  All you
need to do is calculate some sort of effect size/determine a
p-value/etc. for all genes in the experimental conditions of interest
and then combine these statistics across the different experiments.
However, I consistently read things like "raw data are required for a
microarray meta-analysis."  Does this mean that normalized data are not
directly comparable with eachother?  If so, then why does GEO even host
such data?


Any help would be wonderful!




K. Wyatt McMahon, Ph.D.

Texas Tech University Health Sciences Center

Department of Internal Medicine

3601 4th St. 

Lubbock, TX - 79430


"It's been a good year in the lab when three things work. . . and one of
those is the lights." - Tom Maniatis


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