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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.
Afiliação
  • Xin Z; Faculty of IT, Monash University, Clayton, VIC, Australia.
  • Cai Y; Faculty of IT, Monash University, Clayton, VIC, Australia.
  • Dang LT; Southeast University, Nanjing, China.
  • Burke HMS; Australian Regenerative Medicine Institute, Monash University, Clayton, VIC, Australia.
  • Revote J; Systems Biology Institute Australia, Clayton, VIC, Australia.
  • Charitakis N; Australian Regenerative Medicine Institute, Monash University, Clayton, VIC, Australia.
  • Bienroth D; Systems Biology Institute Australia, Clayton, VIC, Australia.
  • Nim HT; Monash eResearch Centre, Monash University, Melbourne, VIC, Australia.
  • Li YF; Murdoch Children's Research Institute, Parkville, VIC, Australia.
  • Ramialison M; Murdoch Children's Research Institute, Parkville, VIC, Australia.
BMC Bioinformatics ; 23(1): 69, 2022 Feb 14.
Article em En | MEDLINE | ID: mdl-35164667
ABSTRACT

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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software Idioma: En Revista: BMC Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Austrália

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software Idioma: En Revista: BMC Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Austrália