Evidence map›Paper›PMID 41561440›Full record

ArticleFrontiers in bioinformatics2025

A novel and accelerated method for integrated alignment and variant calling from short and long reads.

Jinnan Hu, Donald Freed, Hanying Feng, Hong Chen, Zhipan Li, Haodong Chen

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Article in Frontiers in bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Chromosome-Level Genome Assembly ofPlants (Basel, Switzerland) · 2026
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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Jinnan HuSentieon Inc., San Jose, CA, United States.
Donald FreedSentieon Inc., San Jose, CA, United States.
Hanying FengSentieon Inc., San Jose, CA, United States.
Hong ChenSentieon Inc., San Jose, CA, United States.
Zhipan LiSentieon Inc., San Jose, CA, United States.
Haodong ChenSentieon Inc., San Jose, CA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Integrating short- and long-read sequencing technologies has become a promising approach for achieving accurate and comprehensive genomic analysis. Although short-read sequencing (Illumina, etc.) offers high base accuracy and cost efficiency, it struggles with structural variant (SV) detection and complex genomic regions. In contrast, long-read sequencing (PacBio HiFi) excels in resolving large SVs and repetitive sequences but is limited by throughput, higher insertion or deletion (indel) error rates, and sequencing costs. Hybrid approaches may combine these technologies and leverage their complementary strengths and different sources of error to provide higher accuracy, more comprehensive results, and higher throughput by lowering the coverage requirement for the long reads. Methods: This study benchmarks the DNAscope Hybrid (DS-Hybrid) pipeline, a novel integrated alignment and variant calling framework that combines short- and long-read data sequenced from the same sample. The DNAscope Hybrid pipeline is a bioinformatics pipeline that runs on generic x86 CPUs. We evaluate its performance across multiple human genome reference datasets (HG002-HG004) using the draft Q100 and Genome in a Bottle v4.2.1 benchmarks. The pipeline's ability to detect small variants [single-nucleotide polymorphisms (SNPs)/indels)], SVs, and copy-number variations (CNVs) is assessed using data from the Illumina and PacBio sequencing systems at varying read depths (5×-30×). Benchmark results are compared to those of DeepVariant. Results: The DNAscope Hybrid pipeline significantly improves SNP and indel calling accuracy, particularly in complex genomic regions. At lower long-read depths (e.g., 5×-10×), the hybrid approach outperforms stand-alone short- or long-read pipelines at full sequencing depths (30×-35×), reducing variant calling errors by at least 50%. Additionally, the DNAscope Hybrid outperforms leading open-source tools for SV and CNV detection and enhances variant discovery in challenging genomic regions. The pipeline also demonstrates clinical utility by identifying variants in disease-associated genes. Moreover, DNAscope Hybrid is highly efficient, achieving less than 90 min runtimes at single standard instance. Conclusion: The DNAscope Hybrid pipeline is a computationally efficient, highly accurate variant calling framework that leverages the advantages of both short- and long-read sequencing. By improving variant detection in challenging genomic regions and offering a robust solution for clinical and large-scale genomic applications, it holds significant promise for genetic disease diagnostics, population-scale studies, and personalized medicine.

Indexed as

accelerated analysishybrid analysismachine learningNGS-next generation sequencingsecondary analysisvariant calling

Identifiers

PMID41561440
PMCPMC12813096

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.