I am working on one of the previously published dataset and the experiment is like cell line with infected and control in a time course (T1=1hr,T2=4hr,T3=24hr)
condition timepoint Mac.T1 ctrl T1 Mac.T1.1 ctrl T1 Mac.T1.2 ctrl T1 Mac.T2 ctrl T2 Mac.T2.1 ctrl T2 Mac.T2.2 ctrl T2 Mac.T3 ctrl T3 Mac.T3.1 ctrl T3 Mac.T3.2 ctrl T3 Inf.T1 Inf T1 Inf.T1.1 Inf T1 Inf.T2 Inf T2 Inf.T2.1 Inf T2 Inf.T3 Inf T3 Inf.T3.1 Inf T3 Inf.T3.2 Inf T3 Inf.T3.3 Inf T3
This is the design i used
ds <- DESeqDataSetFromMatrix(countData=counts, colData=samples,design=~ timepoint + condition + timepoint:condition)
dds <- DESeq(dds, test="LRT", reduced = ~ timepoint)
I am interested to look at the differential expression after treatment in T1,T2,T3 time points
using the function, resultsNames(dds)
 "Intercept" "timepoint_T2_vs_T1" "timepoint_T3_vs_T1" "condition_Inf_vs_ctrl"  "timepointT2.conditionInf" "timepointT3.conditionInf"
I tried to look for the differential expression in T2 Inf condition results(dds, name="timepointT3.conditionInf", test="wald") and found none have passed the filter of p<0.05 which cannot be true (published data)
Can anybody help me if i am doing something wrong with the design?