StrVCTVRE: A supervised learning method to predict the pathogenicity of human genome structural variants.

ABSTRACT: Whole-genome sequencing resolves many clinical cases where standard diagnostic methods have failed. However, at least half of these cases remain unresolved after whole-genome sequencing. Structural variants (SVs; genomic variants larger than 50 base pairs) of uncertain significance are the genetic cause of a portion of these unresolved cases. As sequencing methods using long or linked reads become more accessible and SV detection algorithms improve, clinicians and researchers are gaining access to thousands of reliable SVs of unknown disease relevance. Methods to predict the pathogenicity of these SVs are required to realize the full diagnostic potential of long-read sequencing. To address this emerging need, we developed StrVCTVRE to distinguish pathogenic SVs from benign SVs that overlap

SUBMITTER: Sharo AG 

PROVIDER: S-EPMC8874149 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature