CoNekT : an open-source framework for comparative genomic and transcriptomic network analyses

The recent accumulation of gene expression data in the form of RNA sequencing creates unprecedented opportunities to study gene regulation and function. Furthermore, comparative analysis of the expression data from multiple species can elucidate which functional gene modules are conserved across spe...

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Main Authors: Proost, Sebastian, Mutwil, Marek
Other Authors: School of Biological Sciences
Format: Journal Article
Language:English
Published: 2018
Subjects:
Online Access:https://hdl.handle.net/10356/88144
http://hdl.handle.net/10220/45652
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author Proost, Sebastian
Mutwil, Marek
author2 School of Biological Sciences
author_facet School of Biological Sciences
Proost, Sebastian
Mutwil, Marek
author_sort Proost, Sebastian
collection NTU
description The recent accumulation of gene expression data in the form of RNA sequencing creates unprecedented opportunities to study gene regulation and function. Furthermore, comparative analysis of the expression data from multiple species can elucidate which functional gene modules are conserved across species, allowing the study of the evolution of these modules. However, performing such comparative analyses on raw data is not feasible for many biologists. Here, we present CoNekT (Co-expression Network Toolkit), an open source web server, that contains user-friendly tools and interactive visualizations for comparative analyses of gene expression data and co-expression networks. These tools allow analysis and cross-species comparison of (i) gene expression profiles; (ii) co-expression networks; (iii) co-expressed clusters involved in specific biological processes; (iv) tissue-specific gene expression; and (v) expression profiles of gene families. To demonstrate these features, we constructed CoNekT-Plants for green alga, seed plants and flowering plants (Picea abies, Chlamydomonas reinhardtii, Vitis vinifera, Arabidopsis thaliana, Oryza sativa, Zea mays and Solanum lycopersicum) and thus provide a web-tool with the broadest available collection of plant phyla. CoNekT-Plants is freely available from http://conekt.plant.tools, while the CoNekT source code and documentation can be found at https://github.molgen.mpg.de/proost/CoNekT/.
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spelling ntu-10356/881442023-02-28T16:56:36Z CoNekT : an open-source framework for comparative genomic and transcriptomic network analyses Proost, Sebastian Mutwil, Marek School of Biological Sciences Comparative Genomic DRNTU::Science::Biological sciences Transcriptomic Network The recent accumulation of gene expression data in the form of RNA sequencing creates unprecedented opportunities to study gene regulation and function. Furthermore, comparative analysis of the expression data from multiple species can elucidate which functional gene modules are conserved across species, allowing the study of the evolution of these modules. However, performing such comparative analyses on raw data is not feasible for many biologists. Here, we present CoNekT (Co-expression Network Toolkit), an open source web server, that contains user-friendly tools and interactive visualizations for comparative analyses of gene expression data and co-expression networks. These tools allow analysis and cross-species comparison of (i) gene expression profiles; (ii) co-expression networks; (iii) co-expressed clusters involved in specific biological processes; (iv) tissue-specific gene expression; and (v) expression profiles of gene families. To demonstrate these features, we constructed CoNekT-Plants for green alga, seed plants and flowering plants (Picea abies, Chlamydomonas reinhardtii, Vitis vinifera, Arabidopsis thaliana, Oryza sativa, Zea mays and Solanum lycopersicum) and thus provide a web-tool with the broadest available collection of plant phyla. CoNekT-Plants is freely available from http://conekt.plant.tools, while the CoNekT source code and documentation can be found at https://github.molgen.mpg.de/proost/CoNekT/. Published version 2018-08-23T05:37:57Z 2019-12-06T16:57:00Z 2018-08-23T05:37:57Z 2019-12-06T16:57:00Z 2018 Journal Article Proost, S., & Mutwil, M. (2018). CoNekT: an open-source framework for comparative genomic and transcriptomic network analyses. Nucleic Acids Research, 46(W1), W133-W140. doi:10.1093/nar/gky336 0305-1048 https://hdl.handle.net/10356/88144 http://hdl.handle.net/10220/45652 10.1093/nar/gky336 en Nucleic Acids Research © The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com. 8 p. application/pdf
spellingShingle Comparative Genomic
DRNTU::Science::Biological sciences
Transcriptomic Network
Proost, Sebastian
Mutwil, Marek
CoNekT : an open-source framework for comparative genomic and transcriptomic network analyses
title CoNekT : an open-source framework for comparative genomic and transcriptomic network analyses
title_full CoNekT : an open-source framework for comparative genomic and transcriptomic network analyses
title_fullStr CoNekT : an open-source framework for comparative genomic and transcriptomic network analyses
title_full_unstemmed CoNekT : an open-source framework for comparative genomic and transcriptomic network analyses
title_short CoNekT : an open-source framework for comparative genomic and transcriptomic network analyses
title_sort conekt an open source framework for comparative genomic and transcriptomic network analyses
topic Comparative Genomic
DRNTU::Science::Biological sciences
Transcriptomic Network
url https://hdl.handle.net/10356/88144
http://hdl.handle.net/10220/45652
work_keys_str_mv AT proostsebastian conektanopensourceframeworkforcomparativegenomicandtranscriptomicnetworkanalyses
AT mutwilmarek conektanopensourceframeworkforcomparativegenomicandtranscriptomicnetworkanalyses