[BioC] stability of gene lists with gcrma and limma upon changing the number of samples in the normalization

[Richard Friedman]

Dear Bioconductor users.

	I am using gcrma and limma on a dataset of 3 conditions with 2  
replicates
each.

1. First I normalized 2 conditons together (4 arrays) and got 312  
probesets with B>0
using limma comparisons. I used no filtering.

2. Then I normalized all 3 conditions together (6 arrays) and  
compared the
same 2 conditions that I did before. I got 301 probesets with B>0. I  
used no filtering.

3. Comparing the probesets I got before I got in runs 1 and 2 I got  
91 in common.

Does this sound right?
Shouldn't the list be more stable than that?


 > sessionInfo()R version 2.6.1 (2007-11-26) i386-apple-darwin8.10.1
locale:en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages: [1] splines   tools     tcltk     stats      
graphics  grDevices utils     datasets  [9] methods   base
other attached packages: [1] mouse4302probe_2.0.0  
gcrma_2.10.0         matchprobes_1.10.0   mouse4302cdf_2.0.0   [5]  
affylmGUI_1.12.0     affy_1.16.0          preprocessCore_1.0.0  
affyio_1.6.1         [9] Biobase_1.16.3       limma_2.12.0        >

Any suggestions would be appreciated.

THANKS!
Rich
-----------------------------------------------------------
Richard A. Friedman, PhD
Associate Research Scientist,
Biomedical Informatics Shared Resource
Herbert Irving Comprehensive Cancer Center (HICCC)
Lecturer,
Department of Biomedical Informatics (DBMI)
Educational Coordinator,
Center for Computational Biology and Bioinformatics (C2B2)/
National Center for Multiscale Analysis of Genomic Networks (MAGNet)
Box 95, Room 130BB or P&S 1-420C
Columbia University Medical Center
630 W. 168th St.
New York, NY 10032
(212)305-6901 (5-6901) (voice)
friedman at cancercenter.columbia.edu
http://cancercenter.columbia.edu/~friedman/

In Memoriam,
Arthur C. Clarke