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bioRxiv · 10.64898/2025.12.04.692264

Context-aware simulation enables systematic optimization of long-read mapping parameters

Hu, J.·Fang, D.·Jin, X.·Yang, C.
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Abstract

The performance of long-read mapping is critical yet highly sensitive to parameter choices. We present CycSim, a context-aware simulator that models sequence-context-dependent errors from empirical sequencing data, coupled with a Bayesian optimization framework for systematic parameter tuning. CycSim more accurately reproduces real error profiles than existing simulators, enabling reliable simulation-based optimization. The framework identified parameter configurations that achieved 2.78-fold faster mapping for data from the newly developed Cyclone platform, and consistently improved both mapping efficiency (8.14-32.65% faster) and structural variant calling accuracy (0.75-1.70% higher F1) across ONT, HiFi, and Cyclone datasets, providing a robust and generalizable foundation for analysis-goal-driven parameter refinement.

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Hu, J., Fang, D., Jin, X., Yang, C.. 2025-12-08. Context-aware simulation enables systematic optimization of long-read mapping parameters. https://doi.org/10.64898/2025.12.04.692264

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