ArticleBioinformatics advances2025
FinaleToolkit: accelerating cell-free DNA fragmentation analysis with a high-speed computational toolkit.
Article in Bioinformatics advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Genome-wide variation in cell-free DNA end-motif entropy predicts immunotherapy response in head and neck cancer.The Journal of clinical investigation · 2026Trial
- Cell-free DNA genomic and fragmentomic features for early outcome prediction in large B cell lymphoma.Cell reports. Medicine · 2026Article
- Exploring per-base quality scores as a surrogate marker of cell-free DNA fragmentome.Briefings in bioinformatics · 2026Article
- Cell-free DNA methylome and fragmentome analysis for relapse monitoring of Ewing sarcoma.EMBO molecular medicine · 2026Article
- Genome-Wide Variations of End Motif in Cell-Free DNA Fragments Distinguish Immunotherapy Responders from Non-Responders in Head and Neck Cancer: A Multi-Institute Prospective Study.medRxiv : the preprint server for health sciences · 2026Article
- DNAvi: integration, statistics, and visualization of cell-free DNA fragment traces.Bioinformatics (Oxford, England) · 2026Article
- A standardized framework for robust fragmentomic feature extraction from cell-free DNA sequencing data.Genome biology · 2025Article
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Authors and funding
4 authors.
Funding
Abstract
Motivation: Cell-free DNA (cfDNA) fragmentation pattern represents a promising non-invasive biomarker for disease diagnosis and prognosis. Numerous fragmentation features, such as end motif and window protection score (WPS), have been characterized in cfDNA genomic sequencing. However, the analytical tools developed in these studies are often not released to the liquid biopsy community or are inefficient for genome-wide analysis in large datasets. Results: To address this gap, we have developed FinaleToolkit, a fast and memory-efficient Python package designed to generate comprehensive fragmentation features from large cfDNA genomic sequencing data. For instance, FinaleToolkit can generate genome-wide WPS features from a ∼100× cfDNA whole-genome sequencing (WGS) dataset with over 1 billion fragments in 0.7 h, offering up to a ∼50-fold increase in processing speed compared to original implementations in the same dataset. We have benchmarked FinaleToolkit against original approaches or implementations where possible, confirming its efficacy. Furthermore, FinaleToolkit enabled the genome-wide analysis of fragmentation patterns over arbitrary genomic intervals, significantly boosting the performance for cancer early detection. Availability and implementation: FinaleToolkit is open source and thoroughly documented with both command line interface and Python application programming interface (API) to facilitate its widespread adoption and use within the research community: https://github.com/epifluidlab/FinaleToolkit.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.