Document Type
Article
Publication Date
2-5-2026
Publication Title
Briefings in Bioinformatics
Volume
27
Issue
1
First page number:
1
Last page number:
12
Abstract
Tandem repeats (TRs) play essential roles in a variety of biological functions, and their abnormal expansions are significantly implicated in phenotypic variation and cause >60 human diseases. However, long TR regions cannot be reliably detected using short-read sequencing, and long-read sequencing enables accurate genome-wide detection of TRs. In recent years, various computational tools have been developed to detect and genotype TRs from long-read data. In this survey, we systematically categorize and review 39 computational tools designed for TR detection, visualization and functional interpretation. We discuss their strengths and limitations for TR detection from long-read sequencing data, highlighting current challenges and future directions to advance long-read TR detection methodologies.
Keywords
tandem repeats; computational tools; long-read sequencing
Disciplines
Computational Biology | Genomics
File Format
File Size
1337 KB
Language
English
Rights
IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Repository Citation
Liu, Q.,
Li, J.
(2026).
Computational Tools for Tandem Repeat Detection Using Long-Read Sequencing.
Briefings in Bioinformatics, 27(1),
1-12.
http://dx.doi.org/10.1093/bib/bbag031