stability of gene lists with gcrma and limma upon changing the number of samples in the normalization
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@richard-friedman-513
Last seen 9.6 years ago
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
Cancer limma gcrma Cancer limma gcrma • 756 views
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@sean-davis-490
Last seen 12 weeks ago
United States
On Wed, Apr 2, 2008 at 6:51 PM, Richard Friedman <friedman at="" cancercenter.columbia.edu=""> wrote: > 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? Hi, Richard. I don't think anyone can comment fully on this without access to the data. However, it is not unusual for gene lists to change significantly when you add 1/3 more data, particularly when you have a small number of samples to begin with. Both gcrma and limma will be affected by the additional data, even though you are apparently making the same comparison in both cases 1 and 2. Hope that helps. Sean
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