ZDOG: zooming in on dominating genes with mutations in cancer pathways

Rudi Alberts1, Jinyu Chen2, Louxin Zhang3

  • 1Department of Mathematics and Computational Biology Programme, National University of Singapore, Singapore, 119076, Singapore. rudi.alberts@nus.edu.sg.

BMC Bioinformatics
|January 1, 2020
PubMed
Abstract

Insights

Identifying cancer-causing genes is difficult due to mutation heterogeneity. ZDOG, a Cytoscape app, visualizes mutated gene impact on cancer pathways using a dominating tree model, aiding master regulator discovery.

Area of Science:

  • Bioinformatics
  • Systems Biology
  • Cancer Genomics

Background:

  • Somatic mutation heterogeneity poses challenges in identifying cancer-causing genes and their functions.
  • Many cancer-driving genes exhibit rare mutations, complicating traditional analysis.

Purpose of the Study:

  • To develop a computational tool for visualizing the impact of mutated genes on cancer pathways.
  • To facilitate the identification of key regulatory genes, even those with low mutation frequencies.

Main Methods:

  • Development of the ZDOG Cytoscape application.
  • Utilizing a dominating tree model to analyze gene positional importance within signalling pathways.

Main Results:

  • The ZDOG app enables visualization of how mutated genes affect cancer pathways.
  • The dominating tree model effectively identifies critical mutated "master" regulators in deregulated pathways.
  • The tool aids in understanding the downstream effects of gene mutations.

Conclusions:

  • A novel model and user-friendly Cytoscape app (ZDOG) have been developed to assess mutation impact on signalling pathways.
  • ZDOG facilitates the examination of a gene's positional influence on downstream pathway components.
  • The ZDOG app is freely available for use and installation via GitHub and the Cytoscape App Store.

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