GOTermViewer: Visualization of Gene Ontology Enrichment in Multiple Differential Gene Expression Analyses.

IF 2.3 Q3 BIOCHEMICAL RESEARCH METHODS
Bioinformatics and Biology Insights Pub Date : 2024-09-18 eCollection Date: 2024-01-01 DOI:10.1177/11779322241271550
Milene Volpato, Mark Hull, Ian M Carr
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引用次数: 0

Abstract

Gene ontology phrases are a widely used set of hierarchical terms that describe the biological properties of genes. These terms are then used to annotate individual genes, making it possible to determine the likely physiological properties of groups of genes such as a list of differentially expressed genes. Consequently, their ability to predict changes in biological features and functions based on alterations in gene expression has made gene ontology terms popular in the wide range of bioinformatic fields, such as differential gene expression and evolutionary biology. However, while they make the analysis easier, it is seldom easy to convey the results in a readily understandable manner. A number of applications have been developed to visualize gene ontology (GO) term enrichment; however, these solutions tend to focus on the display of aggregated results from a single analysis, making them unsuitable for the analysis of a series of experiments such as a time course or response to different drug treatments. As multiple pair wise comparisons are becoming a common feature of RNA profiling experiments, the absence of a mechanism to easily compare them is a significant problem. Consequently, to overcome this obstacle, we have developed GOTermViewer, an application that displays GO term enrichment data as determined by GOstats such that changes in physiological response across a number of individual analyses across a time course or range of drug treatments can be visualized.

GOTermViewer:多重差异基因表达分析中的基因本体富集可视化
基因本体短语是一套广泛使用的分级术语,用于描述基因的生物学特性。这些术语可用于注释单个基因,从而确定基因组(如差异表达基因列表)可能具有的生理特性。因此,基因本体术语能够根据基因表达的变化预测生物特征和功能的变化,这使得基因本体术语在差异基因表达和进化生物学等广泛的生物信息领域大受欢迎。然而,虽然这些术语使分析变得更容易,但要以易于理解的方式传达分析结果却并不容易。目前已经开发了许多应用软件来可视化基因本体(GO)术语富集;然而,这些解决方案往往侧重于显示单次分析的汇总结果,因此不适合分析一系列实验,如时间过程或对不同药物治疗的反应。由于多配对比较正在成为 RNA 图谱分析实验的一个常见特征,因此缺乏一种机制来轻松比较这些结果是一个重大问题。因此,为了克服这一障碍,我们开发了 GOTermViewer 应用程序,它可以显示由 GOstats 确定的 GO 术语富集数据,这样就可以直观地显示在不同时间过程或不同药物治疗范围内进行的多项单独分析中生理反应的变化。
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来源期刊
Bioinformatics and Biology Insights
Bioinformatics and Biology Insights BIOCHEMICAL RESEARCH METHODS-
CiteScore
6.80
自引率
1.70%
发文量
36
审稿时长
8 weeks
期刊介绍: Bioinformatics and Biology Insights is an open access, peer-reviewed journal that considers articles on bioinformatics methods and their applications which must pertain to biological insights. All papers should be easily amenable to biologists and as such help bridge the gap between theories and applications.
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