A standardized framework for robust fragmentomic feature extraction from cell-free DNA sequencing data
Fragmentomics features of cell-free DNA represent promising non-invasive biomarkers for cancer diagnosis. A lack of systematic evaluation of biases in feature quantification hinders the adoption of such applications. We compare features derived from whole-genome sequencing of ten healthy donors using nine library kits and ten data-processing routes and validated in 1182 plasma samples from published studies. Our results clarify the variations from library preparation and feature quantification methods. We design the Trim Align Pipeline and cfDNAPro R package as unified interfaces for data pre-processing, feature extraction, and visualization to standardize multi-modal feature engineering and integration for machine learning.
Authors
- Tommy Kaplan (ORCID: https://orcid.org/0000-0002-1892-5461)
- Yong Kit Samuel Chan (ORCID: https://orcid.org/0000-0003-0922-9357)
- Dmitry Shcherbo (ORCID: https://orcid.org/0000-0002-0266-7015)
- Wendy N. Cooper (ORCID: https://orcid.org/0000-0003-3416-9982)
- Arif Anwer Surani (ORCID: https://orcid.org/0000-0002-5180-9075)
- Richard Bowers
- Emma-Jane Ditter
- Haichao Wang
- Paulius Mennea (ORCID: https://orcid.org/0000-0002-6967-1975)
- Hui Zhao (ORCID: https://orcid.org/0009-0009-2818-2911)
- Christopher G. Smith (ORCID: https://orcid.org/0000-0001-7357-2737)
- Aadhitthya Vijayaraghavan (ORCID: https://orcid.org/0000-0002-6095-8961)
- Maria Neofytou (ORCID: https://orcid.org/0000-0001-7159-3278)
- Nitzan Rosenfeld (ORCID: https://orcid.org/0000-0002-2825-4788)
- Florian Markowetz (ORCID: https://orcid.org/0000-0002-2784-5308)
- Cheng Zhao (ORCID: https://orcid.org/0000-0002-8133-0284)
- Matthew Eldridge (ORCID: https://orcid.org/0000-0002-5799-8911)
Institutions
- Queen Mary University of London (GB)
- Hebrew University of Jerusalem (IL)
- University of Cambridge (GB)
- Cancer Research UK (GB)
- University of Hong Kong (HK)
Publication Details
- Journal
- Genome biology
- Published
- 2025-05-23
- DOI
- https://doi.org/10.1186/s13059-025-03607-5
- Citations
- 14
- Primary Topic
- Cancer Genomics and Diagnostics
- Type
- article
- Field-Weighted Citation Impact
- 12.17