Entering edit mode
Michal Okoniewski
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190
@michal-okoniewski-2676
Last seen 10.3 years ago
Hey Mark,
A question on one-way ANOVA design with edgeR:
I do something like that for 3 groups, so similar case like in the
vignette (glm functionality):
d <- calcNormFactors(d)
d <- estimateCommonDisp(d, verbose=TRUE)
d <- estimateTagwiseDisp(d)
TS <- factor(cc)
design<- model.matrix(~0+TS)
colnames(design) <- levels(TS)
fit <- glmFit(d, design)
fit2 <- glmLRT(fit)
# or fit2 <- glmLRT(fit, coef=1) ???
outTab <- topTags(fit, n=30666)
An the question is:
__ How to get the p-values of the F-test for one-way anova? In a basic
comparison of 3 groups? __
In the vignette you have written:
"The fi t has three parameters. The fi rst is the baseline level of
group 1. The second and third
are the 2 vs 1 and 3 vs 1 di ferences." edgeR vignette (p17, date
March31st 2013)
This sounds to me a bit like hard-coded contrasts? in addition,
default value of coef is ncol(glmfit$design), so 3 in this case. Shall
I use coef=1?
I am a bit confused?
Thanks!
I send a copy to BioC list, as I could not find the answer there.
If I ask stupid question ? please give me a simple solution too :)
Cheers,
Michal
> sessionInfo()
R version 3.0.1 (2013-05-16)
Platform: x86_64-apple-darwin10.8.0 (64-bit)
locale:
[1] 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] stats graphics grDevices utils datasets methods base
other attached packages:
[1] edgeR_3.2.3 limma_3.16.5
loaded via a namespace (and not attached):
[1] tools_3.0.1
--
Dr. Michal Okoniewski
Functional Genomics Center Zurich (mostly Wed-Fri)
Winterthurerstrasse 190, 8057 Zurich
Room Y32 H66, Phone: +41 44 635 39 24
Department of Neuroimmunology and MS Research,
UniSpital Zurich, (mostly Mon-Thu)
Raemistrasse 100, 8091 Zurich
Room: OPS D37, Phone: +41 44 255 1756