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J-Circos: an interactive Circos plotter.

Jiyuan An1, John Lai1, Atul Sajjanhar1

  • 1Australian Prostate Cancer Research Centre-Queensland, Institute of Health and Biomedical Innovation, Queensland University of Technology, Princess Alexandra Hospital and Translational Research Institute, Brisbane, QLD 4102, Australia and School of Information Technology, Deakin University, Burwood, VIC 3125, Australia.

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Summary
This summary is machine-generated.

J-Circos is a new interactive visualization tool for generating Circos plots. This Java-based software allows dynamic data addition and interactive exploration of chromosomal interactions and fusion transcripts.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Circos plots visualize chromosomal interactions and fusion transcripts.
  • Existing tools like Circos and RCircos are figure generators, lacking interactivity.
  • Interactive visualization is crucial for complex genomic data analysis.

Purpose of the Study:

  • To develop an interactive Circos plot tool named J-Circos.
  • To enable dynamic data addition and interactive data exploration.
  • To enhance the visualization of complex chromosomal interactions and fusion transcripts.

Main Methods:

  • Developed J-Circos using the Java programming language for cross-platform compatibility (Windows, MacOS, Linux).
  • Implemented interactive features including dynamic data addition, mouse hover display, and zoom in/out functions.
  • Supported data input via flat file formats and a graphical user interface (GUI).

Main Results:

  • J-Circos generates Circos plots with interactive capabilities.
  • Users can dynamically update data and explore specific data points interactively.
  • The tool facilitates the study of complex chromosomal interactions and fusion transcripts.

Conclusions:

  • J-Circos provides an interactive alternative to static Circos plot generators.
  • The tool enhances the visualization and analysis of complex genomic data.
  • J-Circos empowers biologists to better understand chromosomal abnormalities from next-generation sequencing data.