Benchmarking within-sample minority variant detection with short-read sequencing in <i>M. tuberculosis</i>
Our analysis provides evidence to support best practices for low-frequency variant calling, including tool choice, masking and filtering. We also develop and provide a new error model that excludes false positive low-frequency variant calls from FreeBayes output.
Authors
- Shandukani Mulaudzi
- Sanjana G. Kulkarni (ORCID: https://orcid.org/0000-0002-9883-610X)
- María C. Marín (ORCID: https://orcid.org/0000-0002-7149-287X)
- Maha R Farhat
Institutions
- Lemuel Shattuck Hospital (US)
- Massachusetts General Hospital (US)
- Dana-Farber Cancer Institute (US)
Publication Details
- Journal
- bioRxiv (Cold Spring Harbor Laboratory)
- Published
- 2026-02-16
- DOI
- https://doi.org/10.64898/2026.02.13.704885
- Primary Topic
- Tuberculosis Research and Epidemiology
- Type
- article
- Field-Weighted Citation Impact
- 0.00