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Updated: May 12, 2026
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A Standardized Liquid Biopsy Preanalytical Protocol for Downstream Circulating-Free DNA Applications
Published on: September 16, 2022
A comprehensive toolkit for analyzing cell-free DNA genomic sequencing data in liquid biopsy
Junpeng Zhou1, Keyao Zhu1,2, Xiaoqian Huang1
1Jiangsu Key Laboratory of Drug Discovery and Translational Research for Brain Diseases, School of Basic Medical Sciences, Soochow University, Suzhou 215123, China.
Iscience
|May 11, 2026
Summary
A new toolkit, cfDNAanalyzer, streamlines liquid biopsy analysis using plasma cell-free DNA (cfDNA). It aids researchers in biomarker discovery and improves cancer diagnostics through standardized computational tools.
Area of Science:
- Genomics
- Computational Biology
- Precision Medicine
Background:
- Liquid biopsy using plasma cell-free DNA (cfDNA) offers non-invasive disease insights, particularly for cancer.
- Existing computational tools for cfDNA analysis are fragmented, hindering comprehensive genomic and epigenomic landscape exploration.
- The need for unified, versatile tools is critical to keep pace with diverse cfDNA features and machine learning applications.
Purpose of the Study:
- To introduce cfDNAanalyzer, a user-friendly toolkit for streamlined cfDNA analysis.
- To integrate feature extraction, selection, and machine learning model construction for cfDNA data.
- To support researchers and clinicians, including those with limited bioinformatics expertise, in liquid biopsy research.
Main Methods:
- Developed cfDNAanalyzer, a toolkit for automated preprocessing, multimodal data integration, and interpretable output.
- Integrated feature extraction, selection, and machine learning model construction within the toolkit.
- Benchmarked cfDNAanalyzer against existing toolkits using shared feature types and real-world cfDNA datasets.
Main Results:
- cfDNAanalyzer demonstrated broader feature coverage and efficient runtime compared to existing toolkits.
- The toolkit achieved comparable or improved predictive accuracy across shared feature types.
- Real-world data analysis revealed cfDNAanalyzer's capability to discover biologically meaningful signals and enhance diagnostic performance through feature integration.
Conclusions:
- cfDNAanalyzer standardizes and accelerates cfDNA analysis, facilitating reproducible biomarker discovery.
- The toolkit advances translational liquid biopsy research by enabling more accessible and comprehensive genomic and epigenomic analysis.
- This tool empowers researchers and clinicians to leverage cfDNA for improved disease diagnosis and precision medicine.
