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ceRNAR: An R package for identification and analysis of ceRNA-miRNA triplets
Competitive endogenous RNA (ceRNA) represents a novel mechanism of gene regulation that controls several biological and pathological processes. Recently, an increasing number of in silico methods have been developed to accelerate the identification of such regulatory events. However, there is still...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Public Library of Science
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9491567/ https://www.ncbi.nlm.nih.gov/pubmed/36084156 http://dx.doi.org/10.1371/journal.pcbi.1010497 |
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author | Hsiao, Yi-Wen Wang, Lin Lu, Tzu-Pin |
author_facet | Hsiao, Yi-Wen Wang, Lin Lu, Tzu-Pin |
author_sort | Hsiao, Yi-Wen |
collection | PubMed |
description | Competitive endogenous RNA (ceRNA) represents a novel mechanism of gene regulation that controls several biological and pathological processes. Recently, an increasing number of in silico methods have been developed to accelerate the identification of such regulatory events. However, there is still a need for a tool supporting the hypothesis that ceRNA regulatory events only occur at specific miRNA expression levels. To this end, we present an R package, ceRNAR, which allows identification and analysis of ceRNA-miRNA triplets via integration of miRNA and RNA expression data. The ceRNAR package integrates three main steps: (i) identification of ceRNA pairs based on a rank-based correlation between pairs that considers the impact of miRNA and a running sum correlation statistic, (ii) sample clustering based on gene-gene correlation by circular binary segmentation, and (iii) peak merging to identify the most relevant sample patterns. In addition, ceRNAR also provides downstream analyses of identified ceRNA-miRNA triplets, including network analysis, functional annotation, survival analysis, external validation, and integration of different tools. The performance of our proposed approach was validated through simulation studies of different scenarios. Compared with several published tools, ceRNAR was able to identify true ceRNA triplets with high sensitivity, low false-positive rates, and acceptable running time. In real data applications, the ceRNAs common to two lung cancer datasets were identified in both datasets. The bridging miRNA for one of these, the ceRNA for MAP4K3, was identified by ceRNAR as hsa-let-7c-5p. Since similar cancer subtypes do share some biological patterns, these results demonstrated that our proposed algorithm was able to identify potential ceRNA targets in real patients. In summary, ceRNAR offers a novel algorithm and a comprehensive pipeline to identify and analyze ceRNA regulation. The package is implemented in R and is available on GitHub (https://github.com/ywhsiao/ceRNAR). |
format | Online Article Text |
id | pubmed-9491567 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-94915672022-09-22 ceRNAR: An R package for identification and analysis of ceRNA-miRNA triplets Hsiao, Yi-Wen Wang, Lin Lu, Tzu-Pin PLoS Comput Biol Research Article Competitive endogenous RNA (ceRNA) represents a novel mechanism of gene regulation that controls several biological and pathological processes. Recently, an increasing number of in silico methods have been developed to accelerate the identification of such regulatory events. However, there is still a need for a tool supporting the hypothesis that ceRNA regulatory events only occur at specific miRNA expression levels. To this end, we present an R package, ceRNAR, which allows identification and analysis of ceRNA-miRNA triplets via integration of miRNA and RNA expression data. The ceRNAR package integrates three main steps: (i) identification of ceRNA pairs based on a rank-based correlation between pairs that considers the impact of miRNA and a running sum correlation statistic, (ii) sample clustering based on gene-gene correlation by circular binary segmentation, and (iii) peak merging to identify the most relevant sample patterns. In addition, ceRNAR also provides downstream analyses of identified ceRNA-miRNA triplets, including network analysis, functional annotation, survival analysis, external validation, and integration of different tools. The performance of our proposed approach was validated through simulation studies of different scenarios. Compared with several published tools, ceRNAR was able to identify true ceRNA triplets with high sensitivity, low false-positive rates, and acceptable running time. In real data applications, the ceRNAs common to two lung cancer datasets were identified in both datasets. The bridging miRNA for one of these, the ceRNA for MAP4K3, was identified by ceRNAR as hsa-let-7c-5p. Since similar cancer subtypes do share some biological patterns, these results demonstrated that our proposed algorithm was able to identify potential ceRNA targets in real patients. In summary, ceRNAR offers a novel algorithm and a comprehensive pipeline to identify and analyze ceRNA regulation. The package is implemented in R and is available on GitHub (https://github.com/ywhsiao/ceRNAR). Public Library of Science 2022-09-09 /pmc/articles/PMC9491567/ /pubmed/36084156 http://dx.doi.org/10.1371/journal.pcbi.1010497 Text en © 2022 Hsiao et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Hsiao, Yi-Wen Wang, Lin Lu, Tzu-Pin ceRNAR: An R package for identification and analysis of ceRNA-miRNA triplets |
title | ceRNAR: An R package for identification and analysis of ceRNA-miRNA triplets |
title_full | ceRNAR: An R package for identification and analysis of ceRNA-miRNA triplets |
title_fullStr | ceRNAR: An R package for identification and analysis of ceRNA-miRNA triplets |
title_full_unstemmed | ceRNAR: An R package for identification and analysis of ceRNA-miRNA triplets |
title_short | ceRNAR: An R package for identification and analysis of ceRNA-miRNA triplets |
title_sort | cernar: an r package for identification and analysis of cerna-mirna triplets |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9491567/ https://www.ncbi.nlm.nih.gov/pubmed/36084156 http://dx.doi.org/10.1371/journal.pcbi.1010497 |
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