GENOMICON-Seq enables realistic simulation of amplicon and exome sequencing for low-frequency mutation detection

GENOMICON-Seq enables realistic simulation of amplicon and exome sequencing for low-frequency mutation detection

Abstract Accurate detection of low-frequency mutations is crucial for understanding viral evolution and tumorigenesis in humans, but is often confounded by technical artifacts introduced during library preparation and sequencing. We present GENOMICON-Seq, an end-to-end simulation tool that models bo...

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Bibliographic Details
Main Authors: Milan S. Stosic, Jean-Marc Costanzi, Ole Herman Ambur, Trine B. Rounge
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Simulation
Intrahost single nucleotide variants (iSNVs)
Somatic mutations
Single base substitution (SBS) mutational signature
Amplicon sequencing
Whole exome sequencing (WES)
Online Access:https://doi.org/10.1038/s41598-025-05267-8
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Summary:Abstract Accurate detection of low-frequency mutations is crucial for understanding viral evolution and tumorigenesis in humans, but is often confounded by technical artifacts introduced during library preparation and sequencing. We present GENOMICON-Seq, an end-to-end simulation tool that models both amplicon and whole exome sequencing (WES) workflows with realistic biological mutations and technical noise. GENOMICON-Seq inserts ground truth mutations, ranging from APOBEC3-like edits to COSMIC single base substitution signatures, before subjecting samples to simulated PCR errors, probe-capture enrichment, and Illumina-specific sequencing biases. By tracking each mutation’s origin (true or error-derived), researchers can pinpoint detection limits and optimize variant-calling thresholds. We illustrate GENOMICON-Seq’s versatility through study cases involving human papillomavirus (HPV) amplicon sequencing, highlighting the impacts of polymerase fidelity, viral copy number, and read depth on detecting low-frequency mutations. In parallel, WES simulations demonstrate how capture biases and varying allele frequencies affect somatic mutation calls. GENOMICON-Seq is thus a flexible, reproducible framework for assessing new protocols, benchmarking variant callers, and refining data analysis pipelines, ultimately reducing costly trial-and-error in the laboratory. The Docker-based package is freely available at https://github.com/Rounge-lab/GENOMICON-Seq .
ISSN:2045-2322

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