Cargando…
MonaGO: a novel gene ontology enrichment analysis visualisation system
BACKGROUND: Gene ontology (GO) enrichment analysis is frequently undertaken during exploration of various -omics data sets. Despite the wide array of tools available to biologists to perform this analysis, meaningful visualisation of the overrepresented GO in a manner which is easy to interpret is s...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8845231/ https://www.ncbi.nlm.nih.gov/pubmed/35164667 http://dx.doi.org/10.1186/s12859-022-04594-1 |
_version_ | 1784651628317507584 |
---|---|
author | Xin, Ziyin Cai, Yujun Dang, Louis T. Burke, Hannah M. S. Revote, Jerico Charitakis, Natalie Bienroth, Denis Nim, Hieu T. Li, Yuan-Fang Ramialison, Mirana |
author_facet | Xin, Ziyin Cai, Yujun Dang, Louis T. Burke, Hannah M. S. Revote, Jerico Charitakis, Natalie Bienroth, Denis Nim, Hieu T. Li, Yuan-Fang Ramialison, Mirana |
author_sort | Xin, Ziyin |
collection | PubMed |
description | BACKGROUND: Gene ontology (GO) enrichment analysis is frequently undertaken during exploration of various -omics data sets. Despite the wide array of tools available to biologists to perform this analysis, meaningful visualisation of the overrepresented GO in a manner which is easy to interpret is still lacking. RESULTS: Monash Gene Ontology (MonaGO) is a novel web-based visualisation system that provides an intuitive, interactive and responsive interface for performing GO enrichment analysis and visualising the results. MonaGO supports gene lists as well as GO terms as inputs. Visualisation results can be exported as high-resolution images or restored in new sessions, allowing reproducibility of the analysis. An extensive comparison between MonaGO and 11 state-of-the-art GO enrichment visualisation tools based on 9 features revealed that MonaGO is a unique platform that simultaneously allows interactive visualisation within one single output page, directly accessible through a web browser with customisable display options. CONCLUSION: MonaGO combines dynamic clustering and interactive visualisation as well as customisation options to assist biologists in obtaining meaningful representation of overrepresented GO terms, producing simplified outputs in an unbiased manner. MonaGO will facilitate the interpretation of GO analysis and will assist the biologists into the representation of the results. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-022-04594-1. |
format | Online Article Text |
id | pubmed-8845231 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-88452312022-02-16 MonaGO: a novel gene ontology enrichment analysis visualisation system Xin, Ziyin Cai, Yujun Dang, Louis T. Burke, Hannah M. S. Revote, Jerico Charitakis, Natalie Bienroth, Denis Nim, Hieu T. Li, Yuan-Fang Ramialison, Mirana BMC Bioinformatics Software BACKGROUND: Gene ontology (GO) enrichment analysis is frequently undertaken during exploration of various -omics data sets. Despite the wide array of tools available to biologists to perform this analysis, meaningful visualisation of the overrepresented GO in a manner which is easy to interpret is still lacking. RESULTS: Monash Gene Ontology (MonaGO) is a novel web-based visualisation system that provides an intuitive, interactive and responsive interface for performing GO enrichment analysis and visualising the results. MonaGO supports gene lists as well as GO terms as inputs. Visualisation results can be exported as high-resolution images or restored in new sessions, allowing reproducibility of the analysis. An extensive comparison between MonaGO and 11 state-of-the-art GO enrichment visualisation tools based on 9 features revealed that MonaGO is a unique platform that simultaneously allows interactive visualisation within one single output page, directly accessible through a web browser with customisable display options. CONCLUSION: MonaGO combines dynamic clustering and interactive visualisation as well as customisation options to assist biologists in obtaining meaningful representation of overrepresented GO terms, producing simplified outputs in an unbiased manner. MonaGO will facilitate the interpretation of GO analysis and will assist the biologists into the representation of the results. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-022-04594-1. BioMed Central 2022-02-14 /pmc/articles/PMC8845231/ /pubmed/35164667 http://dx.doi.org/10.1186/s12859-022-04594-1 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Software Xin, Ziyin Cai, Yujun Dang, Louis T. Burke, Hannah M. S. Revote, Jerico Charitakis, Natalie Bienroth, Denis Nim, Hieu T. Li, Yuan-Fang Ramialison, Mirana MonaGO: a novel gene ontology enrichment analysis visualisation system |
title | MonaGO: a novel gene ontology enrichment analysis visualisation system |
title_full | MonaGO: a novel gene ontology enrichment analysis visualisation system |
title_fullStr | MonaGO: a novel gene ontology enrichment analysis visualisation system |
title_full_unstemmed | MonaGO: a novel gene ontology enrichment analysis visualisation system |
title_short | MonaGO: a novel gene ontology enrichment analysis visualisation system |
title_sort | monago: a novel gene ontology enrichment analysis visualisation system |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8845231/ https://www.ncbi.nlm.nih.gov/pubmed/35164667 http://dx.doi.org/10.1186/s12859-022-04594-1 |
work_keys_str_mv | AT xinziyin monagoanovelgeneontologyenrichmentanalysisvisualisationsystem AT caiyujun monagoanovelgeneontologyenrichmentanalysisvisualisationsystem AT danglouist monagoanovelgeneontologyenrichmentanalysisvisualisationsystem AT burkehannahms monagoanovelgeneontologyenrichmentanalysisvisualisationsystem AT revotejerico monagoanovelgeneontologyenrichmentanalysisvisualisationsystem AT charitakisnatalie monagoanovelgeneontologyenrichmentanalysisvisualisationsystem AT bienrothdenis monagoanovelgeneontologyenrichmentanalysisvisualisationsystem AT nimhieut monagoanovelgeneontologyenrichmentanalysisvisualisationsystem AT liyuanfang monagoanovelgeneontologyenrichmentanalysisvisualisationsystem AT ramialisonmirana monagoanovelgeneontologyenrichmentanalysisvisualisationsystem |