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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.
Background:
Inference of cancer-causing genes and their biological functions are crucial but challenging due to the heterogeneity of somatic mutations. The heterogeneity of somatic mutations reveals that only a handful of oncogenes mutate frequently and a number of cancer-causing genes mutate rarely.
Results:
We develop a Cytoscape app, named ZDOG, for visualization of the extent to which mutated genes may affect cancer pathways using the dominating tree model. The dominator tree model allows us to examine conveniently the positional importance of a gene in cancer signalling pathways. This tool facilitates the identification of mutated "master" regulators even with low mutation frequency in deregulated signalling pathways.
Conclusions:
We have presented a model for facilitating the examination of the extent to which mutation in a gene may affect downstream components in a signalling pathway through its positional information. The model is implemented in a user-friendly Cytoscape app which will be freely available upon publication.
Availability:
Together with a user manual, the ZDOG app is freely available at GitHub (https://github.com/rudi2013/ZDOG). It is also available in the Cytoscape app store (http://apps.cytoscape.org/apps/ZDOG) and users can easily install it using the Cytoscape App Manager.
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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