A Fast Association Test for Identifying Pathogenic Variants Involved in Rare Diseases.

ABSTRACT: We present a rapid and powerful inference procedure for identifying loci associated with rare hereditary disorders using Bayesian model comparison. Under a baseline model, disease risk is fixed across all individuals in a study. Under an association model, disease risk depends on a latent bipartition of rare variants into pathogenic and non-pathogenic variants, the number of pathogenic alleles that each individual carries, and the mode of inheritance. A parameter indicating presence of an association and the parameters representing the pathogenicity of each variant and the mode of inheritance can be inferred in a Bayesian framework. Variant-specific prior information derived from allele frequency databases, consequence prediction algorithms, or genomic datasets can be integrated into the i

SUBMITTER: Greene D 

PROVIDER: S-EPMC5501869 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature