Longitudinal analysis setup

I am conducting a study in which I want to explore the effects of an intervention after one year follow up in gut microbiota in humans.

There are 400 participants, 200 from a control group and 200 from an intervention group, and I have data at baseline and at one-year follow up.

I would like to use MaAsLin2 to conduct the longitudinal analysis. Which is the best way to setup the model?

I was thinking to generate a new feature table calculating the delta of the counts and then treat it as cross-sectional. Something like:

res_delta = Maaslin2(delta_counts_clr,
output = “output_delta”,
fixed_effects = c(“intervention_group”, “recruiting_center”, “sex”, “age”)
reference = c(“recruiting_center, center_001”),
max_significance = 0.1,
min_prevalence = 0,
normalization = “NONE”,
transform = “NONE”,
standardize = FALSE)

Any suggestions or tips? Thanks

If I’m understanding the structure of your data, I think it would be better to give the model all the original counts (rather than the delta) and set subject identifier as a random effect.