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DNAi: an open-source AI tool for unbiased DNA fiber analysis
Clément Playout1,2, Yosra Mehrjoo1,3, Renaud Duval1,2
1Research Center, Maisonneuve-Rosemont Hospital, 5415, boulevard de l'Assomption Montréal, H1T 2M4 Québec, Canada.
Nucleic Acids Research
|April 17, 2026
Summary
We developed DNAi, a deep learning tool for automated DNA fiber analysis. This computer vision software significantly improves the speed and reproducibility of measuring DNA replication dynamics from microscopy images.
Area of Science:
- Molecular Biology
- Genetics
- Biotechnology
Background:
- DNA fiber assays are crucial for studying DNA replication dynamics at the single-molecule level.
- Manual analysis of these assays is time-consuming, subjective, and limits experimental throughput.
- Current methods reduce consistency and reproducibility in quantifying DNA fiber length.
Purpose of the Study:
- To develop an automated tool for DNA fiber length quantification.
- To overcome the limitations of manual analysis in DNA fiber assays.
- To enhance the speed, accuracy, and reproducibility of DNA replication studies.
Main Methods:
- Development of DNAi, a computer vision tool utilizing deep learning algorithms.
- Training DNAi on a large dataset of manually annotated DNA fiber images.
- Implementation of a user-friendly interface for visual validation and manual fiber selection.
Main Results:
- DNAi accurately detects and quantifies labeled DNA fiber length, matching human performance.
- The tool demonstrates consistent accuracy across diverse experimental conditions.
- Automated analysis significantly increases experimental throughput and inter-user reliability.
Conclusions:
- DNAi provides a robust, rapid, and reproducible solution for DNA fiber analysis.
- The open-source tool democratizes advanced DNA fiber analysis.
- This advancement facilitates deeper insights into DNA replication dynamics.
