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

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

doi:10.1186/s13059-025-03607-5

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

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^*

^*Corresponding author for this work

The Rachel and Selim Benin School of Engineering and Computer Science

Research output: Contribution to journal › Article › peer-review

Abstract

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.

Original language	English
Article number	141
Journal	Genome Biology
Volume	26
Issue number	1
DOIs	https://doi.org/10.1186/s13059-025-03607-5
State	Published - Dec 2025

Bibliographical note

Publisher Copyright:
© The Author(s) 2025.

Keywords

Cancer genomics
CfDNA
Feature extraction
Fragmentomics

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10.1186/s13059-025-03607-5

https://link.springer.com/content/pdf/10.1186/s13059-025-03607-5.pdfLicense: CC BY

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Wang, H., Mennea, P. D., Chan, Y. K. E., Cheng, Z., Neofytou, M. C., Surani, A. A., Vijayaraghavan, A., Ditter, E. J., Bowers, R., Eldridge, M. D., Shcherbo, D. S., Smith, C. G., Markowetz, F., Cooper, W. N., Kaplan, T., Rosenfeld, N., & Zhao, H. (2025). A standardized framework for robust fragmentomic feature extraction from cell-free DNA sequencing data. Genome Biology, 26(1), Article 141. https://doi.org/10.1186/s13059-025-03607-5

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title = "A standardized framework for robust fragmentomic feature extraction from cell-free DNA sequencing data",

abstract = "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.",

keywords = "Cancer genomics, CfDNA, Feature extraction, Fragmentomics",

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

note = "Publisher Copyright: {\textcopyright} The Author(s) 2025.",

year = "2025",

month = dec,

doi = "10.1186/s13059-025-03607-5",

language = "אנגלית",

volume = "26",

journal = "Genome Biology",

issn = "1474-7596",

publisher = "BioMed Central Ltd.",

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Wang, H, Mennea, PD, Chan, YKE, Cheng, Z, Neofytou, MC, Surani, AA, Vijayaraghavan, A, Ditter, EJ, Bowers, R, Eldridge, MD, Shcherbo, DS, Smith, CG, Markowetz, F, Cooper, WN, Kaplan, T, Rosenfeld, N & Zhao, H 2025, 'A standardized framework for robust fragmentomic feature extraction from cell-free DNA sequencing data', Genome Biology, vol. 26, no. 1, 141. https://doi.org/10.1186/s13059-025-03607-5

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T1 - A standardized framework for robust fragmentomic feature extraction from cell-free DNA sequencing data

AU - Wang, Haichao

AU - Mennea, Paulius D.

AU - Chan, Yu Kiu Elkie

AU - Cheng, Zhao

AU - Neofytou, Maria C.

AU - Surani, Arif Anwer

AU - Vijayaraghavan, Aadhitthya

AU - Ditter, Emma Jane

AU - Bowers, Richard

AU - Eldridge, Matthew D.

AU - Shcherbo, Dmitry S.

AU - Smith, Christopher G.

AU - Markowetz, Florian

AU - Cooper, Wendy N.

AU - Kaplan, Tommy

AU - Rosenfeld, Nitzan

AU - Zhao, Hui

PY - 2025/12

Y1 - 2025/12

N2 - 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.

AB - 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.

KW - Cancer genomics

KW - CfDNA

KW - Feature extraction

KW - Fragmentomics

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AN - SCOPUS:105006801336

SN - 1474-7596

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JO - Genome Biology

JF - Genome Biology

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

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Keywords

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