DESeq2 Design Formula for Time Series Experiment
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gkuffel ▴ 10
@gkuffel-12871
Last seen 3.4 years ago
Loyola University

Hi everyone,

I have miRNA-Seq data for an experiment with the following parameters:

SampleID     Treatment     Timepoint     Patient

   P1_0                  TB                 0             1

   P1_1                  TB                 1             1

   P1_2                  TB                 3             1

   HC1_0                None            0              Control1

   HC1_2                None            3              Control1

   P2_0                  TB                 0              2

   P2_1                  TB                 1              2

  P2_2                   TB                 2              2

   P2_3                  TB                 3              2

   HC2_0                None            0              Control2

  HC2_3                 None            3              Control2

I am really struggling figuring out how to enter the design formula. There are 2 patients each with a baseline sample before treatment and 2 samples at time points after treatment. Each patient has an age-matched control with samples taken at two time points. One patient is a full responder to treatment and one is not but I am blinded to that info. The investigator wants to identify DEmiRNAs in the following:

1. Between patients 

2. As a result of treatment over time

Do I need to include interaction terms? So far I have identified 128 DEmiRNAs using this formula:

design=~timepoint + individual

Which I believe is testing for differences between individuals across all time points, can anyone provide some much needed guidance?

deseq2 • 657 views
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@david-requena-13990
Last seen 4.3 years ago
The Rockefeller University. New York, U…

To compare time points, you should consider "timepoint" in your formula, as you did.

To compare treated vs untreated, you should include "treatment" in your formula.

If you think that your treated patients will experience changes over time, which are different than the changes experienced by the untreated, you should add the interaction term "treatment:timepoint".

I guess that "individual" is your column "patient" or "treatment:age", which are equivalent.

 

I think you'll might find the explanation in the DEseq2 vignette useful (section "Interactions"):

https://bioconductor.org/packages/release/bioc/vignettes/DESeq2/inst/doc/DESeq2.html#interactions

And also these posts:

A: DESeq2 paired multifactor test

With DESeq2 "Not full rank" Error with design ~ line + time + condition

 

David

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David,

Thank you so much for your reply. I have a few more questions if you have time:

1. So with my current design (design =~ Timepoint + Patient) am I testing for differences between patients while controlling for variability caused by time?

2.  If I use the design: design = ~ Timepoint + Treatment, is that testing for differences between treatments while controlling for variability caused by time?

3. When you ask if I think the treated patients will experience changes over time different than changes experienced by untreated do you mean changes caused by the treatment or just naturally ocurring changes?

4. Last and maybe most important question. The most important comparsison the group wants to make is does the treatment have an effect on the patients over time. I still don't understand if I am using the correct design for this.

 

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