Hi! I'm sorry for bothering you. I'm a new R-user and I'm having some problems while doing a microarray analysis. I'm comparing the whole genome array of a Salmonella serovar to another 25, and my goal is to determine which genes are differentially expressed. I'm using limma package and running the next code, 


DIFFERENTIAL EXPRESSION i
#several groups comparisson (by serovars)

groups <- read.table("ClusteringSamples.txt", head=T, sep='\t')

f <- factor(groups$Serovar)
design <- model.matrix(~0 + f) 

colnames(design) <- c("Abortusovis", "Agona", "Anatum", "Arizonae", "Braenderup",
       "Bredeney", "Cholerasuis", "Derby", "Enteritidis", "Gallinarum", "Goelzau", 
        "Hadar", "Havana", "Infantis", "Kedougou", "Mbandaka", "Mikawasima", "Ohio", 
        "ParatiphyA", "ParatiphyB", "Pos.Control", "Pullorum", "Typhi", 
        "Typhimurium", "Virchow") 
           #Convertir a vectores!

summary(is.na(data)) #check if there is any missing value in the dataset. 

fit <- lmFit(data, design)

contrast.matrix <- makeContrasts(Abortusovis-Pos.Control, Agona-Pos.Control, 
        Anatum-Pos.Control, Arizonae-Pos.Control, Braenderup-Pos.Control, 
        Bredeney-Pos.Control, Cholerasuis-Pos.Control, Derby-Pos.Control, 
        Enteritidis-Pos.Control, Gallinarum-Pos.Control, Goelzau-Pos.Control, 
        Hadar-Pos.Control, Havana-Pos.Control, Infantis-Pos.Control, 
        Kedougou-Pos.Control, Mbandaka-Pos.Control, Mikawasima-Pos.Control, 
        Ohio-Pos.Control, ParatiphyA-Pos.Control, ParatiphyB-Pos.Control, 
        Pos.Control-Pos.Control, Pullorum-Pos.Control, Typhi-Pos.Control, 
        Typhimurium-Pos.Control, Virchow-Pos.Control, 
                               levels=design)

fit1 <- contrasts.fit(fit, contrast.matrix)
fit2 <- eBayes(fit1)

But when I try to run eBayes correction to then compute topTable and get those differentially expressed genes, I get and error back:  


Error in eigen(cor.matrix, symmetric = TRUE) : 
  infinite or missing values in 'x'
In addition: Warning messages:
1: In ebayes(fit = fit, proportion = proportion, stdev.coef.lim = stdev.coef.lim,  :
  Estimation of var.prior failed - set to default value
2: In cov2cor(object$cov.coefficients) :
  diag(.) had 0 or NA entries; non-finite result is doubtful

I try to eliminate those missing values, but then I only can compute the contrast matrix of 13 of my 25 different serovars. 
How can I solve the problem? I'll appreciate the all the help and advices. 

Oihane
__
Oihane Irazoki Sanchez
PhD Student, Molecular Microbiology

Depart. de Genčtica i Microbiologia (Facultat de Biocičncies)
UAB, 08193 Bellaterra (Barcelona), Spain

Phone: 34-660938553
E-mail: oihane.irazoki@uab.cat / o.irazoki@gmail.com


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