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<p>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.</p>

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A standardized framework for robust fragmentomic feature extraction from cell-free DNA sequencing data

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年5月23日

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  • Haichao Wang,
  • Paulius D. Mennea,
  • Yu Kiu Elkie Chan,
  • Zhao Cheng,
  • Maria C. Neofytou,
  • Arif Anwer Surani,
  • Aadhitthya Vijayaraghavan,
  • Emma-Jane Ditter,
  • Richard Bowers,
  • Matthew D. Eldridge,
  • Dmitry S. Shcherbo,
  • Christopher G. Smith,
  • Florian Markowetz,
  • Wendy N. Cooper,
  • Tommy Kaplan,
  • Nitzan Rosenfeld,
  • Hui Zhao

摘要

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.