A curated census of pathogenic and likely pathogenic UTR variants and evaluation of deep learning models for variant effect prediction.

Emma Bohn¹, Tammy T Y Lau¹, Omar Wagih¹, Tehmina Masud¹, Daniele Merico^1,2

¹Deep Genomics Inc., Toronto, ON, Canada.

²The Centre for Applied Genomics, Hospital for Sick Children, Toronto, ON, Canada.

Abstract

Introduction: Variants in 5' and 3' untranslated regions (UTR) contribute to rare disease. While predictive algorithms to assist in classifying pathogenicity can potentially be highly valuable, the utility of these tools is often unclear, as it depends on carefully selected training and validation conditions. To address this, we developed a high confidence set of pathogenic (P) and likely pathogen…

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