title: Variant interpretation through Bayesian fusion of frequency and genomic knowledge.
abstract: Variant interpretation is a central challenge in genomic medicine. A recent study demonstrates the power of Bayesian statistical approaches to improve interpretation of variants in the context of specific genes and syndromes. Such Bayesian approaches combine frequency (in the form of observed genetic variation in cases and controls) with biological annotations to determine a probability of pathogenicity. These Bayesian approaches complement other efforts to catalog human variation. See related Research; 10.1186/s13073-014-0120-4.
authors: Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030 USA ; Department of Statistics, Rice University, Houston, TX 77005 USA ; Program in Structural and Computational Biology and Molecular Biophysics, Baylor College of Medicine, Houston, TX 77030 USA.
authors: Chad A
authors: CA
authors: Shaw
authors: Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030 USA.
authors: Ian M
authors: IM
authors: Campbell
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