Hi all,

I have a longitudinal study consisting of two groups of samples (Healthy vs Sick). Each subject has two time points (Baseline and Post). Because of the longitudinal nature of the study, I know I need to control for repeated sampling when looking for potential biomarkers using DESeq2.

Each individual has a individual (unique) ID associated with them.

Here is a simplified example of my data:

condition timepoint individual
healthy      baseline   001
healthy      post       001
healthy      baseline   002
healthy      post       002
sick         baseline   003
sick         post       003
sick         baseline   004
sick         post       004

Since I'm interested in the effect of Condition but want to control for Individual, first I tried:

~ individual + condition

but this results in the "matrix is not full rank" error. I read the associated DESeq2 vignette but am still having trouble understanding what terms my formula needs to have (https://www.bioconductor.org/packages/release/bioc/vignettes/DESeq2/inst/doc/DESeq2.html#model-matrix-not-full-rank).

I can't determine whether the time point term needs to be included as well, though including it in the design formula still causes problems anyway. I feel like there is some "linear combination" I'm just not seeing or understanding here.

Any help is appreciated.