Hi,
I'm new to limma and am trying to figure out how to test for differential expression using a continuous variable. My experimental set-up is two visits for each person and I want to look at change in expression between visit 1 and visit 2. However, I don't want to use visit 1 and visit 2 as the outcome as the visits were taken a various lengths of time apart, so I'm interested in modeling weeks post exposure (visit 1) verses weeks post exposure (visit 2). (I want to see if there's an association with weeks) I've tried:
group<-pheno$Subject
cont.var<-pheno$Weeks
X<-splines::ns(cont.var,df=5)
design<-model.matrix(~0+group+X)
fit <- lmFit(edata2, design)
fit2<-eBayes(fit)
a<-topTable(fit2,coef="group", n=Inf, adjust="fdr")
(But this gives me output for each subject, not weeks)
Or
group<-pheno$Visit
cont.var<-pheno$Weeks
X<-splines::ns(cont.var,df=5)
design<-model.matrix(~group+X)
fit <- lmFit(edata2, design)
fit2<-eBayes(fit)
a<-topTable(fit2,coef="X5", n=Inf, adjust="fdr")
(But this seems equivalent to testing visit 1 verses visit 2)
Unfortunately, I can't post the data here.
edata2 is a dataframe of log transformed expression values (Illumina platform)
Any ideas?
