I have time series study, where colData files look like
cellLine dex timeStep batch 200142521 TF-1 CTRL 24 A 200142571 TF-1 IFN-g 24 A 200142621 TF-1 CTRL 48 A 200142661 TF-1 IFN-g 48 A 200142701 TF-1 CTRL 72 A 200142741 TF-1 IFN-g 72 A 700347671 TF-1 CTRL 24 B 700347681 TF-1 IFN-g 24 B 700347691 TF-1 CTRL 48 B 700347701 TF-1 IFN-g 48 B 700347711 TF-1 CTRL 72 B 700347721 TF-1 IFN-g 72 B
The aim of the study is to find Significantly differential Expression gene across Time series 24, 48 and 72 hours. I have two replicates for each Time steps.
I have used below design for analysis. dds <- DESeqDataSetFromMatrix(countData = cts, colData = coldata, design = ~ dex + timeStep + dex:timeStep) and then dds <- DESeq(dds ,test="LRT", reduced = ~ dex + timeStep)
My questions/concerns are: 1. Am I am using correct design Matrix for such time series analysis? 2. Since I am having two replicates as time Period so if the Number of replicates is good for such study? ( I don't have any possibility of adding more replicates.