I am unsure how to interpret the M-value produced by limma topTable when analyzing a multi-factoral, multi-level experiment. As an example, suppose I test one gene under the same 2 conditions (1 and 2) in two different experiments (A and B). The mean expressions in the two experiments are very different but in both cases condition 1 has higher expression levels than condition 2. I look at the contrast of condition 1 vs. condition 2 ((A1 + B1) - (A2 + B2)). How does topTable calculate M? Thanks, Mark W. Kimpel MD Department of Psychiatry Indiana University School of Medicine Biotechnology, Research, & Training Center 1345 W. 16th Street Indianapolis, IN 46202 ?

Kimpel, Mark William wrote: > I am unsure how to interpret the M-value produced by limma topTable > when analyzing a multi-factoral, multi-level experiment. > > As an example, suppose I test one gene under the same 2 conditions (1 > and 2) in two different experiments (A and B). The mean expressions > in the two experiments are very different but in both cases condition > 1 has higher expression levels than condition 2. I look at the > contrast of condition 1 vs. condition 2 ((A1 + B1) - (A2 + B2)). That is not a contrast, so your 'M' value will be off by a factor of two. The correct contrast would be (A1 + B1)/2 - (A2 + B2)/2, and then 'M' will be calculated just like you would imagine: (mean(A1) + mean(B1))/2 - (mean(A2) + mean(B2))/2 Best, Jim > > How does topTable calculate M? > > Thanks, > > Mark W. Kimpel MD > > Department of Psychiatry Indiana University School of Medicine > Biotechnology, Research, & Training Center 1345 W. 16th Street > Indianapolis, IN 46202 > > > _______________________________________________ Bioconductor mailing > list Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor -- James W. MacDonald Affymetrix and cDNA Microarray Core University of Michigan Cancer Center 1500 E. Medical Center Drive 7410 CCGC Ann Arbor MI 48109 734-647-5623