Hello!
thank you for the nice documentation and the DESeq2 package.
I have an experiment with three timepoints (duration
) and three treatments (conc_nM
). There are also four biological replicates (animal
) repeated at each duration-treatment combination.
This is the experiment design:
| | 0| 100| 250|
|:--------|--:|---:|---:|
|3H | 4| 4| 4|
|12H | 4| 4| 4|
|3D | 4| 4| 4|
|21D | 4| 4| 4|
I would like to identify differentially expressed genes within each time-point and also to identify genes whose response to treatment is influenced by the time-point:
For this, I applied the following procedure to estimate coefficients:
dds <- DESeqDataSetFromMatrix(countData = gene_cts, colData = sample_info, design = ~ animal + duration + conc_nM + duration:conc_nM)
dds_2 <- DESeq(dds, test = "LRT", reduced = ~animal + duration + conc_nM)
Then I get the following coefficients:
> resultsNames(dds_2)
[1] "Intercept" "animal_pig_2_vs_pig_1" "animal_pig_3_vs_pig_1" "animal_pig_4_vs_pig_1" "duration_12H_vs_3H" "duration_3D_vs_3H"
[7] "duration_21D_vs_3H" "conc_nM_100_vs_0" "conc_nM_250_vs_0" "duration12H.conc_nM100" "duration3D.conc_nM100" "duration21D.conc_nM100"
[13] "duration12H.conc_nM250" "duration3D.conc_nM250" "duration21D.conc_nM250"
To find differentialy expressed genes within timepoints (i.e. 12h), I could do this:
results(dds_2, name = "duration12H.conc_nM100")
results(dds_2, name = "duration12H.conc_nM250")
results(dds_2, contrast = list("duration12H.conc_nM250","duration12H.conc_nM100"))
But I am not sure how to get the results for time-point 3h
My questions are:
Is the data modelled correctly?
How to get coefficients for time-point 3h? Is this implicit in the coefficients
conc_nM_100_vs_0
andconc_nM_250_vs_0
?How to extract the p-values for genes whose response to treatment is influenced by time?
Thanks!
sorry about the earlier post, somehow I pushed the wrong combination of keys and the post went online before I finished writing it. I understad, your time-limitation. Thanks anyway :)