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gViz, a novel tool for the visualization of co-expression networks
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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3214194/ https://www.ncbi.nlm.nih.gov/pubmed/22032859 http://dx.doi.org/10.1186/1756-0500-4-452 |
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author | Helaers, Raphaël Bareke, Eric De Meulder, Bertrand Pierre, Michael Depiereux, Sophie Habra, Naji Depiereux, Eric |
author_facet | Helaers, Raphaël Bareke, Eric De Meulder, Bertrand Pierre, Michael Depiereux, Sophie Habra, Naji Depiereux, Eric |
author_sort | Helaers, Raphaël |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-3214194 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-32141942011-11-12 gViz, a novel tool for the visualization of co-expression networks Helaers, Raphaël Bareke, Eric De Meulder, Bertrand Pierre, Michael Depiereux, Sophie Habra, Naji Depiereux, Eric BMC Res Notes Technical Note 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. BioMed Central 2011-10-27 /pmc/articles/PMC3214194/ /pubmed/22032859 http://dx.doi.org/10.1186/1756-0500-4-452 Text en Copyright ©2011 Bareke et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Technical Note Helaers, Raphaël Bareke, Eric De Meulder, Bertrand Pierre, Michael Depiereux, Sophie Habra, Naji Depiereux, Eric gViz, a novel tool for the visualization of co-expression networks |
title | gViz, a novel tool for the visualization of co-expression networks |
title_full | gViz, a novel tool for the visualization of co-expression networks |
title_fullStr | gViz, a novel tool for the visualization of co-expression networks |
title_full_unstemmed | gViz, a novel tool for the visualization of co-expression networks |
title_short | gViz, a novel tool for the visualization of co-expression networks |
title_sort | gviz, a novel tool for the visualization of co-expression networks |
topic | Technical Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3214194/ https://www.ncbi.nlm.nih.gov/pubmed/22032859 http://dx.doi.org/10.1186/1756-0500-4-452 |
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