Model simplification on microarray data
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@paolo-innocenti-2191
Last seen 10.2 years ago
Dear list, I am working with Affymetrix GeneChip gene expression arrays. I am fitting to every transcript a mixed model (using lme4) that looks like this: lmer(Y ~ female.type*male.type+(1|female.pop)+(1|male.pop)) where Y is the transcript signal. When looking at the results, I realized that many of those terms are not interesting (namely the interaction and the second random effect). For most of the genes (but not all!), a simpler model works much better. The simplification would be carried out using likelihood ratio tests. The question is, does it make sense to fit different models (more specifically, simpler version of the full model) for different genes? Would I still be able to compare the terms that are present for all the genes (for example when I have to adjust the p-value)? Thanks, paolo -- Paolo Innocenti Department of Animal Ecology, EBC Uppsala University Norbyv?gen 18D 75236 Uppsala, Sweden
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