I have 3 time points (0h, 120h, 240h) data in replicates. I need to find out the effect of a gene knock-down on cell death mechanisms i.e., genes affected by knock-down. Is 3 times points are enough to consider as time series data. Shall I do pairwise comparision of different time points or do time series analysis sing DESeq2. Here is an example code. Please help me with a code to get normalzed counts as well. Here is an example code I have written after going through DESeq2 Manual.
library(DESeq2) Time = rep(c("0h", "120h", "240h"), each = 2)
Treat = c(rep("Control", 2), rep("Treat", 4))
nameD <- paste(Treat, Time, c(rep(LETTERS[1:2], 1), rep(LETTERS[3:4], 2)), sep = "_")
sampleInfo <- data.frame(row.names = nameD, Time = Time, Treat = Treat)
countdata=read.table("counts.matrix", header=T, row.names=1)
ddsMat <- DESeqDataSetFromMatrix(countData=countdata, colData=sampleInfo, design=~ Time + Treat+Time:Treat)
I am getting following error with above code
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.