cuteHap: Haplotype‐Aware Structural Variant Detection in Phased Long‐Read Sequencing Data

ABSTRACT Long‐read sequencing has enabled comprehensive exploration of human genome at an unprecedented scale, particularly enhancing our understanding of structural variants (SVs). Phasing, a powerful approach for assigning haplotypes to sequencing reads, enables the generation of haplotype‐aware call sets without requiring whole‐genome assembly and provides a new direction for SV detection. Herein, we present cuteHap, a haplotype‐aware SV detection method designed for phased long‐read sequencing data. cuteHap fully leverages phased alignments and automatically selects a self‐adaptive clustering strategy or a cluster credibility‐prioritized beam search algorithm to achieve accurate haplotype‐resolved SV calls. In addition, cuteHap incorporates a mosaic detection module to resolve somatic mosaicism. cuteHap achieved 6% and 3% higher F1‐scores on Pacific Biosciences High‐Fidelity (PacBio HiFi) and Oxford Nanopore Technologies (ONT) datasets, respectively, and detected a greater diversity of low‐frequency SVs in tumor datasets. Its robust and high‐performance SV detection facilitates the generation of high‐quality haplotype‐resolved call sets and advancing global genomic and genetic research.