APOGEE 2: multi-layer machine-learning model for the interpretable prediction of mitochondrial missense variants.

ABSTRACT: Mitochondrial dysfunction has pleiotropic effects and is frequently caused by mitochondrial DNA mutations. However, factors such as significant variability in clinical manifestations make interpreting the pathogenicity of variants in the mitochondrial genome challenging. Here, we present APOGEE 2, a mitochondrially-centered ensemble method designed to improve the accuracy of pathogenicity predictions for interpreting missense mitochondrial variants. Built on the joint consensus recommendations by the American College of Medical Genetics and Genomics/Association for Molecular Pathology, APOGEE 2 features an improved machine learning method and a curated training set for enhanced performance metrics. It offers region-wise assessments of genome fragility and mechanistic analyses of specific a

SUBMITTER: Bianco SD 

PROVIDER: S-EPMC10439926 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature