Automatic DNA replication tract measurement to assess replication and repair dynamics at the single-molecule level

Author:

Li Longjie12,Kolinjivadi Arun Mouli3,Ong Kok Haur12,Young David M14,Marini Gabriel Pik Liang2,Chan Sock Hoai56,Chong Siao Ting3,Chew Ee Ling5,Lu Haoda2,Gole Laurent1,Yu Weimiao12ORCID,Ngeow Joanne356

Affiliation:

1. Institute of Molecular and Cell Biology, A*STAR , Singapore 138673, Singapore

2. Bioinformatics Institute, A*STAR , Singapore 138671, Singapore

3. Lee Kong Chian School of Medicine, Nanyang Technological University , Singapore 308232, Singapore

4. Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California , San Francisco, CA 94158, USA

5. Cancer Genetics Service, Division of Medical Oncology, National Cancer Centre , Singapore 169610, Singapore

6. Oncology Academic Clinical Program, Duke-NUS Medical School Singapore , Singapore 169857, Singapore

Abstract

Abstract Motivation DNA fibre assay has a potential application in genomic medicine, cancer and stem cell research at the single-molecule level. A major challenge for the clinical and research implementation of DNA fibre assays is the slow speed in which manual analysis takes place as it limits the clinical actionability. While automatic detection of DNA fibres speeds up this process considerably, current publicly available software have limited features in terms of their user interface for manual correction of results, which in turn limit their accuracy and ability to account for atypical structures that may be important in diagnosis or investigative studies. We recognize that core improvements can be made to the GUI to allow for direct interaction with automatic results to preserve accuracy as well as enhance the versatility of automatic DNA fibre detection for use in variety of situations. Results To address the unmet needs of diverse DNA fibre analysis investigations, we propose DNA Stranding, an open-source software that is able to perform accurate fibre length quantification (13.22% mean relative error) and fibre pattern recognition (R > 0.93) with up to six fibre patterns supported. With the graphical interface, we developed, user can conduct semi-automatic analyses which benefits from the advantages of both automatic and manual processes to improve workflow efficiency without compromising accuracy. Availability and implementation The software package is available at https://github.com/lgole/DNAStranding. Supplementary information Supplementary data are available at Bioinformatics online.

Funder

National Research Foundation Singapore, Clinician Scientist

Singapore Ministry of Health’s National Medical Research Council

Ministry of Education, Singapore, Academic Research Fund Tier 1

National Cancer Centre Research Fund Terry Fox Grant

Nanyang Technological University Start-Up

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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