A Machine Learning Approach to Identifying Causal Monogenic Variants in Inflammatory Bowel Disease.

ABSTRACT:

Background and aims

Diagnosis of monogenic disease is increasingly important for patient care and personalizing therapy. However, the current process is nonstandardized, expensive, and time consuming. There is currently no accepted strategy to help identify disease-causing variants in monogenic inflammatory bowel disease (IBD). The aim of the study is to develop a prioritization strategy for monogenic IBD variant discovery through detailed analysis of a whole-exome sequencing (WES) data set.

Methods

All consenting pediatric patients with IBD presenting to our tertiary care hospital during the study period were enrolled and underwent WES (n = 1005). Available family members also underwent WES. Variants were analyzed en masse using the GEMINI framework and were further annotat

SUBMITTER: Mulder DJ 

PROVIDER: S-EPMC11307936 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature