An Efficient Algorithm to Assess Genetic Risks Based on Family History

Every person has a potential risk for some genetic diseases, which depends on factors such as genetics, ethnicity, gender, age, and family history. Therefore, genetic risk analysis is an essential component in genetic counseling and should be estimated as accurately as possible for individual and family decision-making. In this paper, we focus on describing basic principles in genetic risk assessment of autosomal recessive diseases within a Bayesian framework. We develop an efficient algorithm to assess genetic risk for each member of a pedigree using Mathematica software, known for its algebraic manipulation capabilities. Moreover, the symbolic implementation of the code is applied to forecast cystic fibrosis (CF) disease in human genetics. Our results demonstrate that the proposed algorithm can achieve accurate risk analyses for CF disease and other autosomal recessive disorders.