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

Area of Science:

• Genomics and Bioinformatics
• Cancer Research
• Molecular Diagnostics

Background:

• Cell-free DNA (cfDNA) in blood serves as a non-invasive surrogate for tumor biopsies.
• Clinical applications of cfDNA include cancer diagnosis, treatment guidance, and response monitoring.
• Accurate detection of somatic mutations from cfDNA is essential but challenging due to low tumor fractions.

Purpose of the Study:

• To introduce cfSNV, a novel computational method for sensitive somatic mutation detection in cfDNA.
• To present a user-friendly cfSNV package and Docker image for accessible analysis.
• To demonstrate the utility of cfSNV for clinical applications using whole-exome sequencing (WES) data.

Main Methods:

• Development of the cfSNV computational method, specifically designed to account for cfDNA properties.
• Comparative analysis of cfSNV against conventional mutation-calling methods using simulated and real cfDNA data.
• Implementation of cfSNV into a user-friendly package with a Docker image for broad accessibility.

Main Results:

• cfSNV significantly outperforms conventional methods in detecting somatic mutations from cfDNA.
• The method achieves accurate mutation detection even with medium-coverage sequencing (≥200×), enabling cfDNA WES.
• The cfSNV package provides fast computation (e.g., 3 hours for a standard WES dataset) and ease of use.

Conclusions:

• cfSNV represents a significant advancement in sensitive and accurate somatic mutation detection from cfDNA.
• The developed package and Docker image lower the barrier for researchers and clinicians to utilize cfDNA analysis.
• cfSNV facilitates the clinical utility of cfDNA, particularly through cost-effective whole-exome sequencing.