I am using DEseq2 and trying to understand the results obtained using different models.
I have a data design with 2 genotypes and 2 time points.
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 want to know the differences in results obtained from genotype coefficient and time coefficient when using different models.
Model1) ~ genotype
Since it is comparing the differences in genotype regardless of time , samples 1-6 vs 7-12 are being compared.
Model2) ~ time
This model compares time T2 vs T1 regardless of genotypes. So it is comparing samples (1-3 + 7-9) vs (4-6 +10-12), is this correct?
Model3) ~ genotype + time
My understanding is that this model assumes the genotype effect is the same at both time points and so it adds a time effect to both genotypes.
Does that mean results(obj3, name="genotype_KO_vs_WT") give differences in genotypes by comparing samples 4-6 vs 10-12 ?
What samples are being compared in the results obtained from results(obj3, name="time_T2_vs_T1")? How is it different from model 2?
Model 4) ~ genotype + time + genotype:time
Here I understand results(obj4, name="genotype_KO_vs_WT") gives the differences in genotypes at reference levels ie, samples 1-3 vs 7-9
results(obj4, name="time_T2_vs_T1"). What samples are compared here? How is it different from ‘time_T2_vs_T1’ results in model 2 or model3?
The interaction term as I understand is giving the specific effect due to KO at time T2 controlling for the baseline differences in genotypes. results(obj5, name="genotypeKO.timeT2")
What samples are being compared from the model matrix?