Modeling the ACMG/AMP variant classification guidelines as a Bayesian classification framework.

ABSTRACT:

Purpose

We evaluated the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) variant pathogenicity guidelines for internal consistency and compatibility with Bayesian statistical reasoning.

Methods

The ACMG/AMP criteria were translated into a naive Bayesian classifier, assuming four levels of evidence and exponentially scaled odds of pathogenicity. We tested this framework with a range of prior probabilities and odds of pathogenicity.

Results

We modeled the ACMG/AMP guidelines using biologically plausible assumptions. Most ACMG/AMP combining criteria were compatible. One ACMG/AMP likely pathogenic combination was mathematically equivalent to pathogenic and one ACMG/AMP pathogenic combination was actually likely pathogenic.

SUBMITTER: Tavtigian SV 

PROVIDER: S-EPMC6336098 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature