Open alienzj opened 5 months ago
Hi @alienzj Thank you for using SIAMCAT! I think there are several things that you could do:
T1
and T2
. For each species and patient, you could calculate the change that happened between time points and then use this table of differences as input for SIAMCAT and then calculate associations between groupsid
as a random effect like this: check.associations(sc.obj, formula='feat~label+(1|id)')
. This will fit a random effect model to each feature and output the significance for the difference in label (group
in your example), with a random effect for the patient IDLet me know if that works! :)
Dear @jakob-wirbel ,
Thank you so much for your suggestions. Let me try it.
Dear Siamcat team,
may I know how to do differential taxonomic analysis using longitudinal model and siamcat?
How to compare the difference of taxonomic composition of
normal
anddisease
group acrossT1
andT2
? And we know for subjecta
orb
, they may have different taxonomic composition atT1
andT2
regards ofnormal
anddisease condition
.