We employed linear regression models to test the association between cell-type proportions and disease status (R Foundation for Statistical Computing, ver.3.3.3). We used stepwise discriminant analysis (stepAIC function of R package MASS, version 7.3–45) to determine significant covariates and to correct for confounding effects. We included RIN, batch, age at death, and post-mortem interval (PMI) as covariates for the Mayo Clinic analyses. For MSBB analyses, we corrected for RIN, PMI, race, batch, and age at death. We also used linear-mixed models to perform multiple-region association analysis, employing random slopes and random intercepts grouping by observations and by donors [61], and correcting for the same covariates previously described.
