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CoExp: A Web Tool for the Exploitation of Co-expression Networks

Gene co-expression networks are a powerful type of analysis to construct gene groupings based on transcriptomic profiling. Co-expression networks make it possible to discover modules of genes whose mRNA levels are highly correlated across samples. Subsequent annotation of modules often reveals biolo...

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Autores principales: García-Ruiz, Sonia, Gil-Martínez, Ana L., Cisterna, Alejandro, Jurado-Ruiz, Federico, Reynolds, Regina H., Cookson, Mark R., Hardy, John, Ryten, Mina, Botía, Juan A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7943635/
https://www.ncbi.nlm.nih.gov/pubmed/33719340
http://dx.doi.org/10.3389/fgene.2021.630187
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author García-Ruiz, Sonia
Gil-Martínez, Ana L.
Cisterna, Alejandro
Jurado-Ruiz, Federico
Reynolds, Regina H.
Cookson, Mark R.
Hardy, John
Ryten, Mina
Botía, Juan A.
author_facet García-Ruiz, Sonia
Gil-Martínez, Ana L.
Cisterna, Alejandro
Jurado-Ruiz, Federico
Reynolds, Regina H.
Cookson, Mark R.
Hardy, John
Ryten, Mina
Botía, Juan A.
author_sort García-Ruiz, Sonia
collection PubMed
description Gene co-expression networks are a powerful type of analysis to construct gene groupings based on transcriptomic profiling. Co-expression networks make it possible to discover modules of genes whose mRNA levels are highly correlated across samples. Subsequent annotation of modules often reveals biological functions and/or evidence of cellular specificity for cell types implicated in the tissue being studied. There are multiple ways to perform such analyses with weighted gene co-expression network analysis (WGCNA) amongst one of the most widely used R packages. While managing a few network models can be done manually, it is often more advantageous to study a wider set of models derived from multiple independently generated transcriptomic data sets (e.g., multiple networks built from many transcriptomic sources). However, there is no software tool available that allows this to be easily achieved. Furthermore, the visual nature of co-expression networks in combination with the coding skills required to explore networks, makes the construction of a web-based platform for their management highly desirable. Here, we present the CoExp Web application, a user-friendly online tool that allows the exploitation of the full collection of 109 co-expression networks provided by the CoExpNets suite of R packages. We describe the usage of CoExp, including its contents and the functionality available through the family of CoExpNets packages. All the tools presented, including the web front- and back-ends are available for the research community so any research group can build its own suite of networks and make them accessible through their own CoExp Web application. Therefore, this paper is of interest to both researchers wishing to annotate their genes of interest across different brain network models and specialists interested in the creation of GCNs looking for a tool to appropriately manage, use, publish, and share their networks in a consistent and productive manner.
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spelling pubmed-79436352021-03-11 CoExp: A Web Tool for the Exploitation of Co-expression Networks García-Ruiz, Sonia Gil-Martínez, Ana L. Cisterna, Alejandro Jurado-Ruiz, Federico Reynolds, Regina H. Cookson, Mark R. Hardy, John Ryten, Mina Botía, Juan A. Front Genet Genetics Gene co-expression networks are a powerful type of analysis to construct gene groupings based on transcriptomic profiling. Co-expression networks make it possible to discover modules of genes whose mRNA levels are highly correlated across samples. Subsequent annotation of modules often reveals biological functions and/or evidence of cellular specificity for cell types implicated in the tissue being studied. There are multiple ways to perform such analyses with weighted gene co-expression network analysis (WGCNA) amongst one of the most widely used R packages. While managing a few network models can be done manually, it is often more advantageous to study a wider set of models derived from multiple independently generated transcriptomic data sets (e.g., multiple networks built from many transcriptomic sources). However, there is no software tool available that allows this to be easily achieved. Furthermore, the visual nature of co-expression networks in combination with the coding skills required to explore networks, makes the construction of a web-based platform for their management highly desirable. Here, we present the CoExp Web application, a user-friendly online tool that allows the exploitation of the full collection of 109 co-expression networks provided by the CoExpNets suite of R packages. We describe the usage of CoExp, including its contents and the functionality available through the family of CoExpNets packages. All the tools presented, including the web front- and back-ends are available for the research community so any research group can build its own suite of networks and make them accessible through their own CoExp Web application. Therefore, this paper is of interest to both researchers wishing to annotate their genes of interest across different brain network models and specialists interested in the creation of GCNs looking for a tool to appropriately manage, use, publish, and share their networks in a consistent and productive manner. Frontiers Media S.A. 2021-02-24 /pmc/articles/PMC7943635/ /pubmed/33719340 http://dx.doi.org/10.3389/fgene.2021.630187 Text en Copyright © 2021 García-Ruiz, Gil-Martínez, Cisterna, Jurado-Ruiz, Reynolds, Cookson, Hardy, Ryten and Botía. 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) and the copyright owner(s) 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 Genetics
García-Ruiz, Sonia
Gil-Martínez, Ana L.
Cisterna, Alejandro
Jurado-Ruiz, Federico
Reynolds, Regina H.
Cookson, Mark R.
Hardy, John
Ryten, Mina
Botía, Juan A.
CoExp: A Web Tool for the Exploitation of Co-expression Networks
title CoExp: A Web Tool for the Exploitation of Co-expression Networks
title_full CoExp: A Web Tool for the Exploitation of Co-expression Networks
title_fullStr CoExp: A Web Tool for the Exploitation of Co-expression Networks
title_full_unstemmed CoExp: A Web Tool for the Exploitation of Co-expression Networks
title_short CoExp: A Web Tool for the Exploitation of Co-expression Networks
title_sort coexp: a web tool for the exploitation of co-expression networks
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7943635/
https://www.ncbi.nlm.nih.gov/pubmed/33719340
http://dx.doi.org/10.3389/fgene.2021.630187
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