LEAP: Using machine learning to support variant classification in a clinical setting

Volume: 41, Issue: 6, Pages: 1079 - 1090
Published: Apr 1, 2020
Abstract
Advances in genome sequencing have led to a tremendous increase in the discovery of novel missense variants, but evidence for determining clinical significance can be limited or conflicting. Here, we present Learning from Evidence to Assess Pathogenicity (LEAP), a machine learning model that utilizes a variety of feature categories to classify variants, and achieves high performance in multiple genes and different health conditions. Feature...
Paper Details
Title
LEAP: Using machine learning to support variant classification in a clinical setting
Published Date
Apr 1, 2020
Volume
41
Issue
6
Pages
1079 - 1090
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