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.
CONCLUSIONS: 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.
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.
CONCLUSIONS: 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.
摘要：
背景：在探索各种组学数据集的过程中，经常进行基因本体论（GO）富集分析。尽管生物学家可以使用各种各样的工具来进行这种分析，仍然缺乏以易于解释的方式对过度表达的GO进行有意义的可视化。
结果：MonashGeneOntology（MonaGO）是一种新颖的基于Web的可视化系统，可提供直观的，用于执行GO富集分析和可视化结果的交互式和响应式界面。MonaGO支持基因列表以及GO术语作为输入。可视化结果可以导出为高分辨率图像或在新的会话中恢复，允许分析的可重复性。MonaGO与11种基于9个功能的最先进的GO富集可视化工具之间的广泛比较表明，MonaGO是一个独特的平台，同时允许在一个单一的输出页面中进行交互式可视化。可通过具有可自定义显示选项的Web浏览器直接访问。
结论：MonaGO结合了动态聚类和交互式可视化以及自定义选项，以帮助生物学家获得有意义的表示过度表示的GO术语，以无偏方式产生简化的输出。MonaGO将促进GO分析的解释，并将帮助生物学家对结果进行表示。
结果：MonashGeneOntology（MonaGO）是一种新颖的基于Web的可视化系统，可提供直观的，用于执行GO富集分析和可视化结果的交互式和响应式界面。MonaGO支持基因列表以及GO术语作为输入。可视化结果可以导出为高分辨率图像或在新的会话中恢复，允许分析的可重复性。MonaGO与11种基于9个功能的最先进的GO富集可视化工具之间的广泛比较表明，MonaGO是一个独特的平台，同时允许在一个单一的输出页面中进行交互式可视化。可通过具有可自定义显示选项的Web浏览器直接访问。
结论：MonaGO结合了动态聚类和交互式可视化以及自定义选项，以帮助生物学家获得有意义的表示过度表示的GO术语，以无偏方式产生简化的输出。MonaGO将促进GO分析的解释，并将帮助生物学家对结果进行表示。
