Mixed model approach with paired sample design
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I have a very similar experimental design to the one mentioned in #12. Is it also possible to include the sample pairing information using the mixed model approach?
label | sample_id | group_id
C1 | S1 | control
C2 | S2 | control
T1 | S1 | treated
T2 | S2 | treated
If so, the ∼1+group_id+(1|sample_id) model that is fit for each gene would include the pairing information rather than the unique sample labels. Is this an appropriate model to use or should the pairing information be included in some other way?
Hi,
It's not appropriate to replace the sample_id with the pair id, but it's possible to use both. Within muscat you won't be able to model the "pair effect" as a random effect, but you can model it as a fixed effect while still treating the sample effect as a random variable.
To do this, store the pair id in a variable (e.g. pair_id), and then use mmDS with covs="pair_id". This will amount to:
~1+group_id+pair_id+(1|sample_id)
Pierre-Luc
Hi Pierre-Luc,
Thank you for your fast and helpful response! I will try it out.