esloco: simulation-based estimation of local coverage in long-read DNA sequencing

Weich A, Lischer C, Vera J (2026)

Publication Type: Journal article

Publication year: 2026

Journal

Bioinformatics (Oxford, England) Oxford University Press (OUP): Policy B - Oxford Open Option B

Book Volume: 42

Article Number: btag009

Journal Issue: 2

DOI: 10.1093/bioinformatics/btag009

Abstract

Long-read DNA sequencing is increasingly applied for whole-genome studies, yet experimental planning often lacks reliable estimates of target region coverage, leading to costly and time-consuming pilot studies and replicates. We present esloco, a Monte Carlo-based simulation framework for estimating local coverage in long-read sequencing experiments, including scenarios with unknown target regions (e.g. viral integration, CRISPR-Cas9) or PCR-free designs (e.g. base modifications). By modeling coverage as a function of sequencing depth and read length distribution, esloco enables informed predictions of local sequencing outcomes. Benchmarking across a 45-gene panel demonstrated close agreement with empirical data, underscoring the framework’s reliability.

Authors with CRIS profile

Adrian Weich Department of Dermatology Christopher Lischer Department of Medicine 5 – Haematology and Oncology Julio Vera González Professur für Tumorimmunologie (Schwerpunkt Systembiologie)

How to cite

APA:

Weich, A., Lischer, C., & Vera, J. (2026). esloco: simulation-based estimation of local coverage in long-read DNA sequencing. Bioinformatics (Oxford, England), 42(2). https://doi.org/10.1093/bioinformatics/btag009

MLA:

Weich, Adrian, Christopher Lischer, and Julio Vera. "esloco: simulation-based estimation of local coverage in long-read DNA sequencing." Bioinformatics (Oxford, England) 42.2 (2026).

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