[BioC] limma for finding differentialy expressed genes of several groups

[priya [guest]]

I would like to find the differentially expressed genes for several variables using the limma package for several groups.

 -- output of sessionInfo(): 

I have the rma normalized matrix in the following format :


ID_REF GSM362180    GSM362181  GSM362188    GSM362189  GSM362192
244901 5.094871713 4.626623079 4.554272515 4.748604391 4.759221647
244902 5.194528083 4.985930299 4.817426064 5.151654407 4.838741605
244903 5.412329253 5.352970877 5.06250609  5.305709079 8.365082403
244904 5.529220594 5.28134657  5.467445095 5.62968933  5.458388909
244905 5.024052699 4.714631878 4.792865831 4.843975286 4.657188246
244906 5.786557533 5.242403911 5.060605782 5.458148567 5.890061836

where the different columns correspond to four different types of promoters and each of the four promoters has a biological replicate so totally there are 8 columns.

I tried using the Limma package to find the differentially expressed genes across several promoters ( with replicates) and I always get an error as Iam new to r and unable to understand it fully .

This is the code that I used:

Group <- factor(c("p1", "p1", "p2", "p2", "p3","p3","p3","p4","p4"), levels = c("GSM362180","GSM362181","GSM362188","GSM362189","GSM362192","GSM362193","GSM362194","GSM362197","GSM362198"))

design <- model.matrix(~0 + Group)

colnames(design) <- c("GSM362180","GSM362181","GSM362188","GSM362189","GSM362192","GSM362193","GSM362194","GSM362197","GSM362198")
fit <- lmFit(modified, design)

where modified is the rma normalized data matrix as inputted in the above format.
I get the following error:

Coefficients not estimable: GSM362180 GSM362181 GSM362188 GSM362189 GSM362192 GSM362193 GSM362194 GSM362197 GSM362198 
Error in lm.fit(design, t(M)) : 0 (non-NA) cases


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