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Updated: Jan 13, 2026

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

Adrian Weich1,2,3, Christopher Lischer4, Julio Vera1,2,3

  • 1Department of Dermatology, Friedrich-Alexander-Universität (FAU) Erlangen-Nürnberg and Uniklinikum Erlangen, 91054 Erlangen, Germany.

Bioinformatics (Oxford, England)
|January 9, 2026
PubMed
Summary
This summary is machine-generated.

Estimating local coverage in long-read DNA sequencing is crucial for experimental design. The esloco simulation framework provides reliable predictions, reducing the need for costly pilot studies.

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Area of Science:

  • Genomics
  • Bioinformatics

Background:

  • Long-read DNA sequencing is vital for whole-genome studies.
  • Accurate coverage estimation is essential for experimental planning.
  • Current methods often lack reliable local coverage predictions.

Purpose of the Study:

  • To introduce esloco, a novel simulation framework.
  • To enable accurate estimation of local coverage in long-read sequencing.
  • To support experimental design for various sequencing scenarios.

Main Methods:

  • esloco utilizes Monte Carlo simulations.
  • It models coverage based on sequencing depth and read length distribution.
  • The framework handles unknown target regions and PCR-free designs.

Main Results:

  • Benchmarking showed close agreement between esloco predictions and empirical data.
  • The framework accurately estimates local sequencing outcomes.
  • esloco demonstrated reliability across a 45-gene panel.

Conclusions:

  • esloco offers a reliable solution for predicting local coverage in long-read sequencing.
  • It facilitates informed experimental planning, saving time and resources.
  • The framework supports diverse applications, including viral integration and base modification studies.