CellTrackVis: interactive browser-based visualization for analyzing cell trajectories and lineages

Changbeom Shim, Wooil Kim, Tran Thien Dat Nguyen, Du Yong Kim, Yu Suk Choi, Yon Dohn Chung

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Automatic cell tracking methods enable practitioners to analyze cell behaviors efficiently. Notwithstanding the continuous development of relevant software, user-friendly visualization tools have room for further improvements. Typical visualization mostly comes with main cell tracking tools as a simple plug-in, or relies on specific software/platforms. Although some tools are standalone, limited visual interactivity is provided, or otherwise cell tracking outputs are partially visualized. Results: This paper proposes a self-reliant visualization system, CellTrackVis, to support quick and easy analysis of cell behaviors. Interconnected views help users discover meaningful patterns of cell motions and divisions in common web browsers. Specifically, cell trajectory, lineage, and quantified information are respectively visualized in a coordinated interface. In particular, immediate interactions among modules enable the study of cell tracking outputs to be more effective, and also each component is highly customizable for various biological tasks. Conclusions: CellTrackVis is a standalone browser-based visualization tool. Source codes and data sets are freely available at http://github.com/scbeom/celltrackvis with the tutorial at http://scbeom.github.io/ctv_tutorial.

Original languageEnglish
Article number124
JournalBMC Bioinformatics
Volume24
Issue number1
DOIs
Publication statusPublished - 2023 Dec

Bibliographical note

Publisher Copyright:
© 2023, The Author(s).

Keywords

  • Cell lineage
  • Cell tracking
  • Cell trajectory
  • Data visualization

ASJC Scopus subject areas

  • Structural Biology
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Applied Mathematics

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