about two way anova on time and treatment
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@james-anderson-1641
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@kevin-r-coombes-1589
Last seen 10.3 years ago
Hi, I usually start this kind of analysis, as you did, with per-gene two- way ANOVAs. I then compute p-values for the significance of the complete ANOVA (in effect comparing the full model with the null model), and use some kind of FDR estimate to set a cutoff on the p-values for statistical significance. With this approach, I only decide on the relative importance of th factors for the genes that have already been identified as "interesting" in the sense that the model explains some part of the expression data. For the interpretation step, you have a couple of choices. One idea is to use Tukey's test for honestly significant difference (again per- gene, but without any other additional correction for multiple testing) to see which groups differs in mean expression. One of the things we've tried recently (see Nakamura et al, Clin Cancer Res, 2007) is to cluster the significant genes and compute average expression profiles for each cluster to see which of the effects are driving the expression. Best, Kevin James Anderson wrote: > Hi, > > I have affy data for time and treatment, I did a two way anova for each gene. What's the correct way to evaluate whether time effect is more imporant or treatment effect is more important? I think averaging the variance component of each gene is not a very good way, since not all genes are equally important, in addition, most of the genes are noisy genes. I am thinking of doing a PCA and take the first several components, instead of doing anova on each gene, I can do two way anova on the scores of the first several component, then I can use a weighted average (weight is determined by the amount of variance each PC captured), is this a good way? Can somebody give me some suggestions on this? Thanks. > > James > > > --------------------------------- > Luggage? GPS? Comic books? > > [[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor
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Lev Soinov ▴ 470
@lev-soinov-2119
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