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cran / glmmSeq

:exclamation: This is a read-only mirror of the CRAN R package repository. glmmSeq — General Linear Mixed Models for Gene-Level Differential Expression. Homepage: https://myles-lewis.github.io/glmmSeq/, https://github.com/myles-lewis/glmmSeq Report bugs for this package: https://github.com/myles-lewis/glmmSeq/issues
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Can glmmseq be used in non-longitudinal data? #1

Open Leran10 opened 1 year ago

Leran10 commented 1 year ago

Hi,

I'm trying to use glmmseq to analyze some dataset in which each patient contributed multiple samples. I want to consider patient ID as random factor and the diagnosis as fixed factor. So my formula would be like:

glmmSeq(~ diagnosis + (1 | patient_ID), countdata = OTU.table, metadata = Sample.table, dispersion = disp, progress = TRUE)

As you can see, I don't have a "Timepoint" variable in this model.

Based on glmmseq manual, glmmseq is "Designed for longitudinal analysis..." If I don't have Timepoint can I still use this model?

Thanks very much! Leran

gaborcsardi commented 1 year ago

Hi, this is a read only mirror of CRAN, please see the package authors in the DESCRIPTION file. Look for Maintainer, BugReports and URL. Thanks!

Leran10 commented 1 year ago

Thanks for letting me know! Leran