I think I have a fairly easy-to-solve problem.
I have an expression table generated from an Affy set. It has one row of gene names (already symbols) and then 180 sample rows. 181 rows total.
So I made another excel file with one row with three different phenotypes I want to compare. That row has a label ("classes") and 180 names. 181 rows total.
In R, I can import each of these
dat <- read.csv("expression.csv") dat <- data.matrix(dat) pheno <- read.csv("pheno.csv") pheno <- data.matrix(pheno)
I can then fit them
fit <- lmFit(dat,pheno)
And ask for an eBayes from limma
fit <- eBayes(fit)
Now, when I view the topTable,
table <- topTable(fit)
My first column has numbers (like "834","1142"), when I'd expect to have gene names there (like "ACTR", "CHRNA1").
What am I doing wrong? Or, rather, am I doing anything right?
pheno? BTW are you sure that
phenohas only the phenodata relevant for your differential expression analysis? Which is your model? $\endgroup$