CHITRA: An Interactive Visualization Tool for Comparative Genomic Rearrangement Analysis
Abstract Motivation The increasing availability of chromosome-scale genome assemblies has fuelled a renewed interest in studying chromosomal evolution and rearrangements. Synteny visualization plays a critical role in understanding genome organization, structural variations, and evolutionary relationships. However, existing tools often have steep learning curves, produce static plots, or are limited in their ability to analyze multiple genomes simultaneously. There is a growing need for an intuitive and interactive visualization tool that can effectively explore syntenic relationships and chromosomal rearrangements. Results Here, we present CHITRA, a web-based interactive tool designed to visualize synteny blocks, chromosomal rearrangements, and breakpoints in both linear and circular styles. CHITRA enables real-time exploration of genome structural variations with an intuitive graphical interface, customizable visualization options, and high-resolution export capabilities for publication-ready figures. The tool supports chromosome- and scaffold-level assemblies and allows users to filter, highlight, and interactively examine syntenic relationships. Availability and implementation CHITRA is freely available at https://chitra.bioinformaticsonline.com/, with comprehensive documentation at https://chitra.bioinformaticsonline.com/docs. The source code is open-source and accessible on GitHub at https://github.com/pranjalpruthi/CHITRA.
Authors
- Nityendra Shukla (ORCID: https://orcid.org/0000-0001-6664-5459)
- Preeti Agarwal (ORCID: https://orcid.org/0000-0001-8107-8501)
- Ajay Bhatia (ORCID: https://orcid.org/0000-0003-3962-8500)
- Pranjal Pruthi
- Lata Rani
- Jitendra Naraya
Institutions
- Institute of Genomics and Integrative Biology (IN)
- Central Road Research Institute (IN)
- All India Institute of Medical Sciences (IN)
- Academy of Scientific and Innovative Research (IN)
Publication Details
- Journal
- Bioinformatics Advances
- Published
- 2026-07-17
- DOI
- https://doi.org/10.1093/bioadv/vbag200
- Primary Topic
- Genome Rearrangement Algorithms
- Type
- article
- Field-Weighted Citation Impact
- 0.00