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ceRNAshiny: An Interactive R/Shiny App for Identification and Analysis of ceRNA Regulation
The competing endogenous RNA (ceRNA) network is a newly discovered post-transcriptional regulation that controls both physiological and pathological progresses. Increasing research studies have been pivoted on this theory to explore the function of novel non-coding RNAs, pseudogenes, circular RNAs,...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9136144/ https://www.ncbi.nlm.nih.gov/pubmed/35647026 http://dx.doi.org/10.3389/fmolb.2022.865408 |
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author | Song, Yueqiang Li, Jia Mao, Yiming Zhang, Xi |
author_facet | Song, Yueqiang Li, Jia Mao, Yiming Zhang, Xi |
author_sort | Song, Yueqiang |
collection | PubMed |
description | The competing endogenous RNA (ceRNA) network is a newly discovered post-transcriptional regulation that controls both physiological and pathological progresses. Increasing research studies have been pivoted on this theory to explore the function of novel non-coding RNAs, pseudogenes, circular RNAs, and messenger RNAs. Although there are several R packages or computational tools to analyze ceRNA networks, an urgent need for easy-to-use computational tools still remains to identify ceRNA regulation. Besides, the conventional tools were mainly devoted to investigating ceRNAs in malignancies instead of those in neurodegenerative diseases. To fill this gap, we developed ceRNAshiny, an interactive R/Shiny application, which integrates widely used computational methods and databases to provide and visualize the construction and analysis of the ceRNA network, including differential gene analysis and functional annotation. In addition, demo data in ceRNAshiny could provide ceRNA network analyses about neurodegenerative diseases such as Parkinson’s disease. Overall, ceRNAshiny is a user-friendly application that benefits all researchers, especially those who lack an established bioinformatic pipeline and are interested in studying ceRNA networks. |
format | Online Article Text |
id | pubmed-9136144 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91361442022-05-28 ceRNAshiny: An Interactive R/Shiny App for Identification and Analysis of ceRNA Regulation Song, Yueqiang Li, Jia Mao, Yiming Zhang, Xi Front Mol Biosci Molecular Biosciences The competing endogenous RNA (ceRNA) network is a newly discovered post-transcriptional regulation that controls both physiological and pathological progresses. Increasing research studies have been pivoted on this theory to explore the function of novel non-coding RNAs, pseudogenes, circular RNAs, and messenger RNAs. Although there are several R packages or computational tools to analyze ceRNA networks, an urgent need for easy-to-use computational tools still remains to identify ceRNA regulation. Besides, the conventional tools were mainly devoted to investigating ceRNAs in malignancies instead of those in neurodegenerative diseases. To fill this gap, we developed ceRNAshiny, an interactive R/Shiny application, which integrates widely used computational methods and databases to provide and visualize the construction and analysis of the ceRNA network, including differential gene analysis and functional annotation. In addition, demo data in ceRNAshiny could provide ceRNA network analyses about neurodegenerative diseases such as Parkinson’s disease. Overall, ceRNAshiny is a user-friendly application that benefits all researchers, especially those who lack an established bioinformatic pipeline and are interested in studying ceRNA networks. Frontiers Media S.A. 2022-05-13 /pmc/articles/PMC9136144/ /pubmed/35647026 http://dx.doi.org/10.3389/fmolb.2022.865408 Text en Copyright © 2022 Song, Li, Mao and Zhang. https://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 | Molecular Biosciences Song, Yueqiang Li, Jia Mao, Yiming Zhang, Xi ceRNAshiny: An Interactive R/Shiny App for Identification and Analysis of ceRNA Regulation |
title | ceRNAshiny: An Interactive R/Shiny App for Identification and Analysis of ceRNA Regulation |
title_full | ceRNAshiny: An Interactive R/Shiny App for Identification and Analysis of ceRNA Regulation |
title_fullStr | ceRNAshiny: An Interactive R/Shiny App for Identification and Analysis of ceRNA Regulation |
title_full_unstemmed | ceRNAshiny: An Interactive R/Shiny App for Identification and Analysis of ceRNA Regulation |
title_short | ceRNAshiny: An Interactive R/Shiny App for Identification and Analysis of ceRNA Regulation |
title_sort | cernashiny: an interactive r/shiny app for identification and analysis of cerna regulation |
topic | Molecular Biosciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9136144/ https://www.ncbi.nlm.nih.gov/pubmed/35647026 http://dx.doi.org/10.3389/fmolb.2022.865408 |
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