gViz, a novel tool for the visualization of co-expression networks

Raphaël Helaers, Eric Bareke, Bertrand De Meulder, Michael Pierre, Sophie Depiereux, Naji Habra, Eric Depiereux

Résultats de recherche: Contribution à un journal/une revueArticle

Résumé

Background: The quantity of microarray data available on the Internet has grown dramatically over the past years and now represents millions of Euros worth of underused information. One way to use this data is through co-expression analysis. To avoid a certain amount of bias, such data must often be analyzed at the genome scale, for example by network representation. The identification of co-expression networks is an important means to unravel gene to gene interactions and the underlying functional relationship between them. However, it is very difficult to explore and analyze a network of such dimensions. Several programs (Cytoscape, yEd) have already been developed for network analysis; however, to our knowledge, there are no available GraphML compatible programs. Findings. We designed and developed gViz, a GraphML network visualization and exploration tool. gViz is built on clustering coefficient-based algorithms and is a novel tool to visualize and manipulate networks of co-expression interactions among a selection of probesets (each representing a single gene or transcript), based on a set of microarray co-expression data stored as an adjacency matrix. Conclusions: We present here gViz, a software tool designed to visualize and explore large GraphML networks, combining network theory, biological annotation data, microarray data analysis and advanced graphical features.

langue originaleAnglais
Numéro d'article452
journalBMC Research Notes
Volume4
Les DOIs
étatPublié - 28 oct. 2011

    Empreinte digitale

Contient cette citation