I am using DEseq2 and trying to understand the results obtained using different models.
I have the data design as
sample genotype time 1 WT_S1 WT T1 2 WT_S2 WT T1 3 WT_S3 WT T1 4 WT_S4 WT T2 5 WT_S5 WT T2 6 WT_S6 WT T2 7 KO_S1 KO T1 8 KO_S2 KO T1 9 KO_S3 KO T1 10 KO_S4 KO T2 11 KO_S5 KO T2 12 KO_S6 KO T2
I have 3 models.
model1 : ~genotype
model2 : ~time
model3 : ~genotype + time
I get 200 genes as significant using model1 and another 198 genes as significant from model2. However when I use model3, I don’t have any significant genes. I would like to know what samples are being compared when using model 3.
ie, what samples are being compared in model3 when getting results using (obj3, name=”genotype_KO_vs_WT”)? How is it different from model1?
Also,what samples are being compared in model3 when getting results using results(obj2, name=”time_T2_vs_T1″) ? How is it different from model2?
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