Hi,

I'm using EdgeR to analyse a proteomic data with peptide counting. I have
limited experience on R/EdgeR/Statistics so I appreciate some help.
Using the follow code:

 a=file[,2:64]

b=DGEList(counts=a,group=rep(c("La6h","La24h","Lm6h","Lm24h","MO6h","MO24h"
),c(10,11,10,11,10,11)), lib.size=colSums(a))

b <- calcNormFactors(b)

times <- rep(c("La6h","La24h","Lm6h","Lm24h","MO6h","MO24h"),c(10,11,10,11,
10,11))

times <- factor(times,levels=c("La6h","La24h","Lm6h","Lm24h","MO6h","MO24h"
))

design <- model.matrix(~factor(times))

disp <- estimateCommonDisp(b)

fit <- glmFit(b,design,dispersion=disp$common.dispersion)

lrt <- glmLRT(b,fit,coef=fit$design)
disp$common.dispersion = 0.0001004979

All proteins (3430) had a p.value of 0.

I tried also with

fit <- glmFit(b,design,dispersion=disp$common.dispersion)

lrt <- glmLRT(b,fit,coef=fit$design)
disp$common.dispersion =  3.999943

and that gave me all the proteins with p.value lower than 6.29E-05.

That gave a signal that I'm doing something wrong or because of both common
dispersions my data is not a appropriate for the analysis.

Any suggestions or corrections?

--
Fabricio K. Marchini

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