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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