Abstract
BackgroundInference 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.ResultsWe 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.ConclusionsWe 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.AvailabilityTogether 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.
Highlights
Inference of cancer-causing genes and their biological functions are crucial but challenging due to the heterogeneity of somatic mutations
Availability: Together with a user manual, the ZDOG app is freely available at GitHub
It is available in the Cytoscape app store and users can install it using the Cytoscape App Manager
Summary
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. With the advent of highthroughput genome sequencing technology, different genomic resources have become available for identifying cancer-causing mutations in oncogenes, including the Catalogue of Somatic Mutations in Cancer (COSMIC) [2] and The Cancer Genome Atlas (TCGA) [3]. The accumulation of cancer genomic data demonstrates mutational heterogeneity between different cancers and between different genomes of the same cancer. This reveals that only a handful of oncogenes mutate frequently, whereas many cancer-causing genes mutate rarely [3].
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