title: Contextual Hub Analysis Tool (CHAT): A Cytoscape app for identifying contextually relevant hubs in biological networks.
abstract: Highly connected nodes (hubs) in biological networks are topologically important to the structure of the network and have also been shown to be preferentially associated with a range of phenotypes of interest. The relative importance of a hub node, however, can change depending on the biological context. Here, we report a Cytoscape app, the Contextual Hub Analysis Tool (CHAT), which enables users to easily construct and visualize a network of interactions from a gene or protein list of interest, integrate contextual information, such as gene expression or mass spectrometry data, and identify hub nodes that are more highly connected to contextual nodes (e.g. genes or proteins that are differentially expressed) than expected by chance. In a case study, we use CHAT to construct a network of genes that are differentially expressed in Dengue fever, a viral infection. CHAT was used to identify and compare contextual and degree-based hubs in this network. The top 20 degree-based hubs were enriched in pathways related to the cell cycle and cancer, which is likely due to the fact that proteins involved in these processes tend to be highly connected in general. In comparison, the top 20 contextual hubs were enriched in pathways commonly observed in a viral infection including pathways related to the immune response to viral infection. This analysis shows that suchcontextual hubsare considerably more biologically relevant than degree-based hubs and that analyses which rely on the identification of hubs solely based on their connectivity may be biased towards nodes that are highly connected in general rather than in the specific context of interest.
  
  
  BACKGROUND
  CHAT is available for Cytoscape 3.0+ and can be installed via the Cytoscape App Store ( http://apps.cytoscape.org/apps/chat).
authors.affiliation: EMBL Australia Biomedical Informatics Group, Infection & Immunity Theme, South Australian Medical and Health Research Institute, Adelaide, Australia.
authors.forename: Tanja
authors.initials: T
authors.lastname: Muetze
authors.affiliation: EMBL Australia Biomedical Informatics Group, Infection & Immunity Theme, South Australian Medical and Health Research Institute, Adelaide, Australia.
authors.forename: Ivan H
authors.initials: IH
authors.lastname: Goenawan
authors.affiliation: Animal and Bioscience Research Department, Animal and Grassland Research and Innovation Centre, Teagasc, Meath, Ireland.
authors.forename: Heather L
authors.initials: HL
authors.lastname: Wiencko
authors.affiliation: EMBL Australia Biomedical Informatics Group, Infection & Immunity Theme, South Australian Medical and Health Research Institute, Adelaide, Australia.
authors.forename: Manuel
authors.initials: M
authors.lastname: Bernal-Llinares
authors.affiliation: EMBL Australia Biomedical Informatics Group, Infection & Immunity Theme, South Australian Medical and Health Research Institute, Adelaide, Australia.
authors.forename: Kenneth
authors.initials: K
authors.lastname: Bryan
authors.affiliation: EMBL Australia Biomedical Informatics Group, Infection & Immunity Theme, South Australian Medical and Health Research Institute, Adelaide, Australia; School of Medicine, Flinders University, Bedford Park, Australia.
authors.forename: David J
authors.initials: DJ
authors.lastname: Lynn
keywords: CHAT; Network analysis; contextual hub analysis; gene expression data; hubs; hypergeometric test