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Article

VCboost: reducing false positives in long-read variant calling for single-nucleotide polymorphism and indel detection in challenging genomic regions.

Briefings in bioinformatics - 3 Jul 2026

Zhang Yuchen, Chen Hu, Liu Xiaoqing, He Pingan, Dai Qi

Abstract excerpt

Long-read sequencing enables improved genome inference but remains challenged by high error rates that lead to excessive false-positive (FP) variant calls, particularly for small INDELs in complex genomic regions. We present VCboost, a deep learning-based post-calling framework designed to reduce FP in single-nucleotide polymorphism (SNP) and indel detection from long-read sequencing data. VCboost extracts...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Identifiers

PMID: 42566707
DOI: 10.1093/bib/bbag405
PMCID: PMC13450691

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

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