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 Genètica i Microbiologia (Facultat de Biociències)
UAB, 08193 Bellaterra (Barcelona), Spain
Phone: 34-660938553
E-mail: oihane.iraz...@uab.cat / o.iraz...@gmail.com
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