SVhet: towards accurate detection of germline heterozygous deletions using short reads.

ABSTRACT:

Background

Accurate structural variant detection from short-read sequencing data remains challenged by false positives, particularly for heterozygous deletions where reduced allelic support and coverage-based detection methods are ambiguous. Existing SV genotyping and filtering approaches suffer from significant recall reductions, dependencies on additional pre-computed resources, or restriction to depth-based signals that overlook read level evidence.

Results

Here we present SVhet, a novel computational framework that leverages the heterozygosity patterns detected from different read evidences to identify false heterozygous deletions. Comprehensive benchmarking using 31 Human Genome Structural Variation Consortium Phase 3 samples demonstrated SVhet's ability to further redu

SUBMITTER: She CH 

PROVIDER: S-EPMC12798059 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature