It always amazes me how much we can explain using mixed-effects models.
#Statistics #modeling #lmer #rstats #lme4 #Bioinformatics #DataScience
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@rohitfarmer
True. What did you use it for?
@devSJR to model the change in immunity over time during space flights among NASA astronauts. I am modeling how inter-subject variation differs from within-subject variation over time for a viral infection. We have used PhIP-Seq, a high-throughput technique, to profile changes in the antibody repertoire. Hopefully, I will get the paper submitted this year.
@rohitfarmer
First time I heard about PhIP-Seq was some time ago in
https://academic.oup.com/bioinformatics/article/39/10/btad583/7280694
Sounds super interesting. Just to get an idea, can you say sth about the samples (number, time points ...)?
@devSJR We use PhIP-Stat for most of our analysis. In this project, we performed PhIP-Seq on 11 subjects across 7 time points using one of our in-house libraries. We identified a few species of interest that are enriched, and now I am modeling whether the antibody response that we have detected changes over time, along with other effects. It's still at an early stage.
@rohitfarmer Thanks, now I have a better idea. Getting samples from NASA astronauts to learn about immunity over time during space flights was not on my bingo list. Please let me know when the paper is out.