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FinaleToolkit: Accelerating Cell-Free DNA Fragmentation Analysis with a High-Speed Computational Toolkit.

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FinaleToolkit: accelerating cell-free DNA fragmentation analysis with a high-speed computational toolkit.

James Wenhan Li1,2,3, Ravi Bandaru1,2, Kundan Baliga4

  • 1Department of Biochemistry and Molecular Genetics, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, United States.

Bioinformatics Advances
|November 12, 2025
PubMed
Summary

FinaleToolkit is a new, efficient Python package for analyzing cell-free DNA (cfDNA) fragmentation patterns. It accelerates genome-wide analysis of cfDNA, improving non-invasive disease detection and prognosis.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Diagnostics

Background:

  • Cell-free DNA (cfDNA) fragmentation patterns are valuable non-invasive biomarkers for disease diagnosis and prognosis.
  • Existing analytical tools for cfDNA fragmentation analysis are often not publicly available or are inefficient for large-scale, genome-wide studies.
  • Key fragmentation features like end motifs and window protection scores (WPS) require efficient computational methods for comprehensive characterization.

Purpose of the Study:

  • To develop a fast and memory-efficient computational tool for generating comprehensive cfDNA fragmentation features from large genomic datasets.
  • To address the limitations of existing analytical tools in terms of accessibility and efficiency for genome-wide cfDNA analysis.
  • To facilitate the widespread adoption and application of cfDNA fragmentation analysis in liquid biopsy research.

Main Methods:

  • Development of FinaleToolkit, a Python package for processing cfDNA whole-genome sequencing (WGS) data.
  • Implementation of algorithms for generating genome-wide fragmentation features, including window protection scores (WPS).
  • Benchmarking FinaleToolkit against existing methods to evaluate its speed, memory efficiency, and efficacy.

Main Results:

  • FinaleToolkit significantly enhances processing speed, achieving up to a ~50-fold increase compared to original implementations for genome-wide WPS feature generation.
  • The toolkit efficiently processes large cfDNA WGS datasets (e.g., ~100x coverage, >1 billion fragments) in a short time (e.g., 0.7 hours).
  • Enabled genome-wide analysis of cfDNA fragmentation patterns over arbitrary genomic intervals, improving performance for early cancer detection.

Conclusions:

  • FinaleToolkit provides an efficient and accessible solution for analyzing cfDNA fragmentation patterns in large datasets.
  • The open-source nature and comprehensive documentation (CLI and Python API) promote its adoption by the research community.
  • This tool has the potential to advance non-invasive disease diagnostics and prognostics through improved liquid biopsy analysis.