I've got an error in a DESeq2 analysis with the model design. I have a treatment vs. control set-up with different time points.
ddsTCpus14 <- DESeqDataSetFromTximport(txifilesevipus14, colData=colDatapus, design = ~ Treatment + Time + Year + Treatment:Time)
X,Time,Treatment,Year Treat_1h_rep1,1h,Treat,Late Treat_1h_rep2,1h,Treat,Late Treat_1h_rep3,1h,Treat,Late Control_1h_rep1,1h,Control,Late Control_1h_rep2,1h,Control,Late Control_1h_rep3,1h,Control,Late Treat_4h_rep1,4h,Treat,Late Treat_4h_rep2,4h,Treat,Late Treat_4h_rep3,4h,Treat,Late Control_4h_rep1,4h,Control,Late Control_4h_rep2,4h,Control,Late Control_4h_rep3,4h,Control,Late Treat_12h_rep1,12h,Treat,Early Treat_12h_rep2,12h,Treat,Early Treat_12h_rep3,12h,Treat,Early Control_12h_rep1,12h,Control,Early Control_12h_rep2,12h,Control,Early Control_12h_rep3,12h,Control,Early
Error in checkFullRank(modelMatrix) : the model matrix is not full rank, so the model cannot be fit as specified. One or more variables or interaction terms in the design formula are linear combinations of the others and must be removed.
I guess it is because the condition Year is nested in Time? The aim of adding Year as a condition is to specify some samples were sequenced one year early than the others. Is there some other ways to remove the effect?