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CoExpNetViz: Comparative Co-Expression Networks Construction and Visualization Tool
Motivation: Comparative transcriptomics is a common approach in functional gene discovery efforts. It allows for finding conserved co-expression patterns between orthologous genes in closely related plant species, suggesting that these genes potentially share similar function and regulation. Several...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4700130/ https://www.ncbi.nlm.nih.gov/pubmed/26779228 http://dx.doi.org/10.3389/fpls.2015.01194 |
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author | Tzfadia, Oren Diels, Tim De Meyer, Sam Vandepoele, Klaas Aharoni, Asaph Van de Peer, Yves |
author_facet | Tzfadia, Oren Diels, Tim De Meyer, Sam Vandepoele, Klaas Aharoni, Asaph Van de Peer, Yves |
author_sort | Tzfadia, Oren |
collection | PubMed |
description | Motivation: Comparative transcriptomics is a common approach in functional gene discovery efforts. It allows for finding conserved co-expression patterns between orthologous genes in closely related plant species, suggesting that these genes potentially share similar function and regulation. Several efficient co-expression-based tools have been commonly used in plant research but most of these pipelines are limited to data from model systems, which greatly limit their utility. Moreover, in addition, none of the existing pipelines allow plant researchers to make use of their own unpublished gene expression data for performing a comparative co-expression analysis and generate multi-species co-expression networks. Results: We introduce CoExpNetViz, a computational tool that uses a set of query or “bait” genes as an input (chosen by the user) and a minimum of one pre-processed gene expression dataset. The CoExpNetViz algorithm proceeds in three main steps; (i) for every bait gene submitted, co-expression values are calculated using mutual information and Pearson correlation coefficients, (ii) non-bait (or target) genes are grouped based on cross-species orthology, and (iii) output files are generated and results can be visualized as network graphs in Cytoscape. Availability: The CoExpNetViz tool is freely available both as a PHP web server (link: http://bioinformatics.psb.ugent.be/webtools/coexpr/) (implemented in C++) and as a Cytoscape plugin (implemented in Java). Both versions of the CoExpNetViz tool support LINUX and Windows platforms. |
format | Online Article Text |
id | pubmed-4700130 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-47001302016-01-15 CoExpNetViz: Comparative Co-Expression Networks Construction and Visualization Tool Tzfadia, Oren Diels, Tim De Meyer, Sam Vandepoele, Klaas Aharoni, Asaph Van de Peer, Yves Front Plant Sci Plant Science Motivation: Comparative transcriptomics is a common approach in functional gene discovery efforts. It allows for finding conserved co-expression patterns between orthologous genes in closely related plant species, suggesting that these genes potentially share similar function and regulation. Several efficient co-expression-based tools have been commonly used in plant research but most of these pipelines are limited to data from model systems, which greatly limit their utility. Moreover, in addition, none of the existing pipelines allow plant researchers to make use of their own unpublished gene expression data for performing a comparative co-expression analysis and generate multi-species co-expression networks. Results: We introduce CoExpNetViz, a computational tool that uses a set of query or “bait” genes as an input (chosen by the user) and a minimum of one pre-processed gene expression dataset. The CoExpNetViz algorithm proceeds in three main steps; (i) for every bait gene submitted, co-expression values are calculated using mutual information and Pearson correlation coefficients, (ii) non-bait (or target) genes are grouped based on cross-species orthology, and (iii) output files are generated and results can be visualized as network graphs in Cytoscape. Availability: The CoExpNetViz tool is freely available both as a PHP web server (link: http://bioinformatics.psb.ugent.be/webtools/coexpr/) (implemented in C++) and as a Cytoscape plugin (implemented in Java). Both versions of the CoExpNetViz tool support LINUX and Windows platforms. Frontiers Media S.A. 2016-01-05 /pmc/articles/PMC4700130/ /pubmed/26779228 http://dx.doi.org/10.3389/fpls.2015.01194 Text en Copyright © 2016 Tzfadia, Diels, De Meyer, Vandepoele, Aharoni and Van de Peer. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Plant Science Tzfadia, Oren Diels, Tim De Meyer, Sam Vandepoele, Klaas Aharoni, Asaph Van de Peer, Yves CoExpNetViz: Comparative Co-Expression Networks Construction and Visualization Tool |
title | CoExpNetViz: Comparative Co-Expression Networks Construction and Visualization Tool |
title_full | CoExpNetViz: Comparative Co-Expression Networks Construction and Visualization Tool |
title_fullStr | CoExpNetViz: Comparative Co-Expression Networks Construction and Visualization Tool |
title_full_unstemmed | CoExpNetViz: Comparative Co-Expression Networks Construction and Visualization Tool |
title_short | CoExpNetViz: Comparative Co-Expression Networks Construction and Visualization Tool |
title_sort | coexpnetviz: comparative co-expression networks construction and visualization tool |
topic | Plant Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4700130/ https://www.ncbi.nlm.nih.gov/pubmed/26779228 http://dx.doi.org/10.3389/fpls.2015.01194 |
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