DESeq2 effects of treatment at different time points including subject ID
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@catalina-aguilar-hurtado-6554
Last seen 3.4 years ago
United States

Hi all, 

I am doing differential gene expression of 5 different subjects, 2 treatments, 2 time points. I want to combine the response   of the treatment at both time points, but controlling the subject effect. I am not interested  in the effects across the subjects or to each time point. 

Not sure how to do it, 

Now I have:

dds <- DESeqDataSetFromMatrix(
  countData = countdata,
  colData = coldata,
 design = ~Time + Treatment)
dds

dds$Treatment <- factor(dds$Treatment, levels=c("35", "25"))

dds$Treatment <- relevel (dds$Treatment, "35")

dds$Time <- factor(dds$Time)

dds <- DESeq(dds)

But I think this is not taking into account my subject ID? I looked at the contrast option but I understand this is for looking at differences within the factors. 

DESeq2_1.4.5 

Thanks,

Catalina

deseq2 rnaseq differential gene expression • 3.1k views
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Entering edit mode
@mikelove
Last seen 13 hours ago
United States

hi Catalina, 

Just a note, you're 2 version behind the release (1.8) and we recommend keeping up to date if possible (it is not always possible in the middle of a project which relies on other package versions).

I would need to see the column data to see if it is possible to control for subject across treatment:

as.data.frame(colData(dds))

If subject effects are not confounded with treatment you could use: ~ subject + time + treatment

Another small note: giving the level order to factor() means that you don't have to use relevel() because you've already specified the reference level.

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Hi Michael,

Not sure what you mean if the subject is not confounded with treatment. I have 5 subjects, with only have one sample per subject (one subject was sequenced twice at each treatment and time (e.g. A1 and A1.1)).

Fro the factor levels means that the factor I write first is the base level? 35 in my example

Thanks

> as.data.frame(colData(dds))
     Subject Treatment Time
A1         1        35    1
A1.1       1        35    1
A2         2        35    1
A3         3        35    1
A4         4        35    1
A5         5        35    1
B1         1        25    1
B1.1       1        25    1
B2         2        25    1
B3         3        25    1
B4         4        25    1
B5         5        25    1
C1         1        35   24
C1.1       1        35   24
C2         2        35   24
C3         3        35   24
C4         4        35   24
C5         5        35   24
D2         2        25   24
D2.1       2        25   24
D4         4        25   24
D5         5        25   24

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Looks good. My above recommendation is all you need then.
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