We used the most predictive in silico algorithm to estimate the risks of breast cancer associated with subsets of rare missense variants, defined by categories of the in silico score, in ATM, BRCA1, BRCA2, CHEK2, and PALB2. These predictions were then validated using an independent dataset. The gene discussed is ATM; the disease is breast cancer.