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cfSNV: a software tool for the sensitive detection of somatic mutations from cell-free DNA

Nature Protocols volume 18, pages 1563–1583 (2023)Cite this article

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Abstract

Cell-free DNA (cfDNA) in blood, viewed as a surrogate for tumor biopsy, has many clinical applications, including diagnosing cancer, guiding cancer treatment and monitoring treatment response. All these applications depend on an indispensable, yet underdeveloped task: detecting somatic mutations from cfDNA. The task is challenging because of the low tumor fraction in cfDNA. Recently, we developed the computational method cfSNV, the first method that comprehensively considers the properties of cfDNA for the sensitive detection of mutations from cfDNA. cfSNV vastly outperformed the conventional methods that were developed primarily for calling mutations from solid tumor tissues. cfSNV can accurately detect mutations in cfDNA even with medium-coverage (e.g., ≥200×) sequencing, which makes whole-exome sequencing (WES) of cfDNA a viable option for various clinical utilities. Here, we present a user-friendly cfSNV package that exhibits fast computation and convenient user options. We also built a Docker image of it, which is designed to enable researchers and clinicians with a limited computational background to easily carry out analyses on both high-performance computing platforms and local computers. Mutation calling from a standard preprocessed WES dataset (~250× and ~70 million base pair target size) can be carried out in 3 h on a server with eight virtual CPUs and 32 GB of random access memory.

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Fig. 1: The cfSNV workflow and its techniques.
Fig. 2: Four modules in the cfSNV Docker package.
Fig. 3: Example outputs of the parameter-recommendation module.
Fig. 4: An example output of the variant list and the tumor fraction from cfSNV.

Data availability

No new genomic sequencing data were generated in this study. The datasets used in this protocol included (i) the example data, which are available at the European Nucleotide Archive under the accession numbers ERR850376 and ERR852106; and (ii) the test demo data, which are available at https://zenodo.org/record/7191202/files/demo_data.tar.gz.

Code availability

cfSNV can be obtained at https://github.com/jasminezhoulab/cfSNV_docker. It can be freely used for educational and research purposes by nonprofit institutions and U.S. government agencies only under the UCLA Academic Software License. For information on use for a commercial purpose or by a commercial or for-profit entity, please contact Xianghong Jasmine Zhou (XJZhou@mednet.ucla.edu) and Wenyuan Li (WenyuanLi@mednet.ucla.edu).

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Acknowledgements

This work was supported by National Cancer Institute grant nos. U01CA230705 and R01CA264864 to X.J.Z., R01CA246329 to X.J.Z. and W.L. and U01CA237711 to W.L.

Author information

Authors and Affiliations

  1. Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA, USA

    Shuo Li, Ran Hu, Chun-Chi Liu, Xianghong Jasmine Zhou & Wenyuan Li

  2. Bioinformatics Interdepartmental Graduate Program, University of California at Los Angeles, Los Angeles, CA, USA

    Ran Hu

  3. Institute for Quantitative & Computational Biosciences, University of California at Los Angeles, Los Angeles, CA, USA

    Ran Hu, Colin Small & Xianghong Jasmine Zhou

  4. EarlyDiagnostics Inc., Los Angeles, CA, USA

    Ting-Yu Kang, Chun-Chi Liu, Xianghong Jasmine Zhou & Wenyuan Li

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Contributions

S.L., R.H., C.S., T.-Y.K. and C.-C.L. developed the protocol. S.L. and R.H. wrote the manuscript. W.L. and X.J.Z. supervised the study. All authors discussed and reviewed the manuscript.

Corresponding authors

Correspondence to Xianghong Jasmine Zhou or Wenyuan Li.

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Competing interests

X.J.Z. and W.L. are co-founders of EarlyDiagnostics Inc. C.-C.L. and T.-Y.K. are employees of EarlyDiagnostics Inc. S.L. is a former employee of EarlyDiagnostics Inc. The remaining authors declare no competing interests.

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Nature Protocols thanks Navonil De Sarkar, Alain Thierry and Zhidong Tu for their contribution to the peer review of this work.

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Related links

Key papers using this protocol

Li, S. et al. Nat. Commun. 12, 4172 (2021): https://doi.org/10.1038/s41467-021-24457-2

Li, S. et al. Clin. Cancer Res. 28, 1841–1853 (2022): https://doi.org/10.1158/1078-0432.CCR-21-1242

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Li, S., Hu, R., Small, C. et al. cfSNV: a software tool for the sensitive detection of somatic mutations from cell-free DNA. Nat Protoc 18, 1563–1583 (2023). https://doi.org/10.1038/s41596-023-00807-w

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