Article
Assessment of In-Frame Indel Variants in an Unsolved Cohort of Inherited Retinal Diseases Using Machine Learning.
Human mutation - 1 Jan 2026
Rauch David E, Wang Meng, Hafiz Muhammad Jafar Hussain, Brock Daniel C, Li Yumei, Marra Molly, Pennesi Mark E, Yang Paul, Lesley Everett, Lopez Irma, Koenekoop Robert, Collantes Edward Ryan, Bolinao Joanne, Chen Rui
Abstract excerpt
The standard for in silico pathogenicity prediction of in-frame insertions and deletions (indels) is less established compared to other types of variations. We aimed to systematically assess the performance of in silico machine learning (ML) tools on a patient cohort with inherited retinal diseases (IRDs). The performance of four ML tools (CADD, FATHMM-indel, VEST4, and MetaRNN-indel) was compared. Among them,...
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