Hi, I want to analyse time-series data. My design is as pasted below,
sample group
H24_Untreated_R1 H24_Untreated
H24_Untreated_R2 H24_Untreated
H24_Untreated_R3 H24_Untreated
H24_Treated_R1 H24_Treated
H24_Treated_R2 H24_Treated
H24_Treated_R3 H24_Treated
H48_Untreated_R1 H48_Untreated
H48_Untreated_R2 H48_Untreated
H48_Untreated_R3 H48_Untreated
H48_Treated_R1 H48_Treated
H48_Treated_R2 H48_Treated
H48_Treated_R3 H48_Treated
I need to find genes changing in response to time. My script is as pasted below,
design <- model.matrix( ~0 + group, data = des) #des is above dataframe
fit <- lmFit(ip,design)
cont.matrix <-makeContrasts(H24_Untreated_vs_H24_Treated = (groupH24_Treated - groupH24_Untreated),
H48_Untreated_vs_H48_Treated = (groupH48_Treated - groupH48_Untreated),
levels = design)
fit.cont <- contrasts.fit(fit, cont.matrix)
fit.cont <- eBayes(fit.cont)
limma.res <- topTable(fit.cont,n="Inf")
"limma.res" has values in pasted below columns H24_Untreated_vs_H24_Treated, H48_Untreated_vs_H48_Treated, AveExpr, F, P.Value, adj.P.Val
My question is , if we take the list of genes based on the adj.P.Val cut-off of interest, are those the genes which are changing in response to time? I am not interested in direction of regulation. Only want to find genes which are changing over time.
