Hello,
I want to determine if there are genes that are differentially expressed between males and females for each treatment (none, low, and high). For gender my reference level is set as female and for treatment my reference level is set as none. Samples and script below.
sample | treatment | gender |
---|---|---|
1 | none | female |
2 | none | female |
3 | none | female |
4 | none | male |
5 | none | male |
6 | none | male |
7 | low | female |
8 | low | female |
9 | low | female |
10 | low | male |
11 | low | male |
12 | low | male |
13 | high | female |
14 | high | female |
15 | high | female |
16 | high | male |
17 | high | male |
18 | high | male |
#design matrix >dds = DESeqDataSetFromMatrix(countData=countdata, colData=coldata, design=~gender+treatment+gender:treatment) #set reference levels >dds$treatment=relevel(dds$treatment, ref="none") >dds$gender=relevel(dds$gender, ref="female") >dds = DESeq(dds) >res=results(dds) >resultsNames(dds) [1] "Intercept" "gender_male_vs_female" "treatment_low_vs_none" "treatment_high_vs_none" "gendermale.treatmentlow" "gendermale.treatmenthigh"
1) So is my design set up correctly for the question I want to answer, which genes are differentially expressed between males and females under a specific treatment?
2) And does "gendermale.treatmentlow" look for DEGs between males and females for low treatments, whereas "gendermale.treatmenthigh" looks for DEGS between males and females for high treatment?
3) Why is there no "gendermale.treatmentnone"?
I agree that the alternate design is easier to understand. I guess I am still confused what exactly the interaction coeffcients are comparing against.
After running the alternate design my resultsNames(dds) are:
Is res=results(dds, name=treatmentlow.gendermale) then comparing low treatment males to low treatment females? If not, then what is it comparing against?
In the new design each of the interaction terms is the male versus female difference for that treatment group.