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Question
From your document, it seems that you can only use one factor to do the contrast in differential gene expression analysis.
What if we need to combine two factors?
What have I tried
In my "samples.tsv", I have two different developmental stages. Each stage has three different treatments. Each treatment has 3 biological samples.
I know that I can do:
contrasts:
stages_4_5
treatments_Control_Treatment1
How about contrasts: (stages 4 treatement 1) vs (stages 5 treatment 1) or different combination of both factors?
You can add additional columns to the samples.tsv. Here is your example:
samples
stages
treatments
st
s1
4
treatment1
s4t1
s2
4
treatment1
s4t1
s3
5
treatment1
s5t1
s4
5
treatment1
s5t1
s5
6
treatment1
s6t1
s6
6
treatment1
s6t1
In the config.yaml, the contrast would now be: st_s5t1_s4t1 or st_s4t1_s5t1.
Note: every sample that has a label in the contrast column will be used by DESeq2 to calculate the dispersion in your data. So it is generally best to include them all.
Question
From your document, it seems that you can only use one factor to do the contrast in differential gene expression analysis.
What if we need to combine two factors?
What have I tried
In my "samples.tsv", I have two different developmental stages. Each stage has three different treatments. Each treatment has 3 biological samples.
I know that I can do:
contrasts:
How about contrasts: (stages 4 treatement 1) vs (stages 5 treatment 1) or different combination of both factors?
stages | treatments
4 | Control
4 | Control
4 | Control
4 | Treatment1
4 | Treatment1
4 | Treatment1
4 | Treatment2
4 | Treatment2
4 | Treatment2
4 | Treatment3
4 | Treatment3
4 | Treatment3
5 | Control
5 | Control
5 | Control
5 | Treatment1
5 | Treatment1
5 | Treatment1
5 | Treatment2
5 | Treatment2
5 | Treatment2
5 | Treatment3
5 | Treatment3
5 | Treatment3
Thank you for your attention
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