I am seeking advise on model specification for a gene expression data set (24 genes) with the following covariates: age (n=5) and phenotype (n=2, control and disease). The samples are independent (one organ per animal). I would like to evaluate time-dependent (age-dependent) between class (between phenotype) gene expression differences. From the vignette, it appears that the following model specification is appropriate:
cov <- data.frame(tme=age, grp=phenotype)
null_model <- ~grp + ns(tme, df=4, intercept=F)
full_model <- ~grp + ns(tme, df=4, intercept=F) + (grp):ns(tme, df=4, intercept=F)
However, I recognize that this is the model specification for longitudinal sampling, as contrasted to independent sampling.
Could someone please advise?