Hi
I have just switched to analysing my data with a continuous instead of 2 group variable with limma. Is this correct with the addition of covariates in this manner?
design <- model.matrix(~des4$DAS28.0M+des4$AGE+des4$GENDER+des4$RACE)
matrix <- data.matrix(data3)
fit <- lmFit(matrix,design)
fit <- eBayes(fit)
top2 <- topTable(fit,coef=2,number=Inf,sort.by="P")
significant <- subset(top2, top2$adj.P.Val < 0.01)
Thanks,
Chris
Right sorry this is just baseline arthritis disease activity we are modelling here. I don't think we would expect many genes to go in opposite directions depending on gender and race so I will just proceed to use this model - based on what you have said here. Thanks.