A new computational technique that combines genomic and tau PET imaging data promises a more personalized approach for subtyping Alzheimer’s disease. Based on a novel clustering framework using sparse canonical correlation analysis (SCCA), the integrated approach was successful in identifying four subtypes of Alzheimer’s disease and the top genes associated with each.