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GCEN: An Easy-to-Use Toolkit for Gene Co-Expression Network Analysis and lncRNAs Annotation

Gene co-expression network analysis has been widely used in gene function annotation, especially for long noncoding RNAs (lncRNAs). However, there is a lack of effective cross-platform analysis tools. For biologists to easily build a gene co-expression network and to predict gene function, we develo...

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Detalles Bibliográficos
Autores principales: Chen, Wen, Li, Jing, Huang, Shulan, Li, Xiaodeng, Zhang, Xuan, Hu, Xiang, Xiang, Shuanglin, Liu, Changning
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9164028/
https://www.ncbi.nlm.nih.gov/pubmed/35723358
http://dx.doi.org/10.3390/cimb44040100
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author Chen, Wen
Li, Jing
Huang, Shulan
Li, Xiaodeng
Zhang, Xuan
Hu, Xiang
Xiang, Shuanglin
Liu, Changning
author_facet Chen, Wen
Li, Jing
Huang, Shulan
Li, Xiaodeng
Zhang, Xuan
Hu, Xiang
Xiang, Shuanglin
Liu, Changning
author_sort Chen, Wen
collection PubMed
description Gene co-expression network analysis has been widely used in gene function annotation, especially for long noncoding RNAs (lncRNAs). However, there is a lack of effective cross-platform analysis tools. For biologists to easily build a gene co-expression network and to predict gene function, we developed GCEN, a cross-platform command-line toolkit developed with C++. It is an efficient and easy-to-use solution that will allow everyone to perform gene co-expression network analysis without the requirement of sophisticated programming skills, especially in cases of RNA-Seq research and lncRNAs function annotation. Because of its modular design, GCEN can be easily integrated into other pipelines.
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spelling pubmed-91640282022-06-04 GCEN: An Easy-to-Use Toolkit for Gene Co-Expression Network Analysis and lncRNAs Annotation Chen, Wen Li, Jing Huang, Shulan Li, Xiaodeng Zhang, Xuan Hu, Xiang Xiang, Shuanglin Liu, Changning Curr Issues Mol Biol Article Gene co-expression network analysis has been widely used in gene function annotation, especially for long noncoding RNAs (lncRNAs). However, there is a lack of effective cross-platform analysis tools. For biologists to easily build a gene co-expression network and to predict gene function, we developed GCEN, a cross-platform command-line toolkit developed with C++. It is an efficient and easy-to-use solution that will allow everyone to perform gene co-expression network analysis without the requirement of sophisticated programming skills, especially in cases of RNA-Seq research and lncRNAs function annotation. Because of its modular design, GCEN can be easily integrated into other pipelines. MDPI 2022-03-25 /pmc/articles/PMC9164028/ /pubmed/35723358 http://dx.doi.org/10.3390/cimb44040100 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Chen, Wen
Li, Jing
Huang, Shulan
Li, Xiaodeng
Zhang, Xuan
Hu, Xiang
Xiang, Shuanglin
Liu, Changning
GCEN: An Easy-to-Use Toolkit for Gene Co-Expression Network Analysis and lncRNAs Annotation
title GCEN: An Easy-to-Use Toolkit for Gene Co-Expression Network Analysis and lncRNAs Annotation
title_full GCEN: An Easy-to-Use Toolkit for Gene Co-Expression Network Analysis and lncRNAs Annotation
title_fullStr GCEN: An Easy-to-Use Toolkit for Gene Co-Expression Network Analysis and lncRNAs Annotation
title_full_unstemmed GCEN: An Easy-to-Use Toolkit for Gene Co-Expression Network Analysis and lncRNAs Annotation
title_short GCEN: An Easy-to-Use Toolkit for Gene Co-Expression Network Analysis and lncRNAs Annotation
title_sort gcen: an easy-to-use toolkit for gene co-expression network analysis and lncrnas annotation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9164028/
https://www.ncbi.nlm.nih.gov/pubmed/35723358
http://dx.doi.org/10.3390/cimb44040100
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