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基因本体术语查看器:多种差异基因表达分析中基因本体富集的可视化

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

作者信息

Volpato Milene, Hull Mark, Carr Ian M

机构信息

School of Medicine, University of Leeds, Leeds, UK.

出版信息

Bioinform Biol Insights. 2024 Sep 18;18:11779322241271550. doi: 10.1177/11779322241271550. eCollection 2024.

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.

摘要

基因本体术语是一组广泛使用的层次化术语,用于描述基因的生物学特性。这些术语随后被用于注释单个基因,从而能够确定基因群体(如差异表达基因列表)可能的生理特性。因此,它们基于基因表达变化预测生物学特征和功能变化的能力,使得基因本体术语在广泛的生物信息学领域(如差异基因表达和进化生物学)中广受欢迎。然而,虽然它们使分析变得更容易,但要以易于理解的方式传达结果却很少是容易的。已经开发了许多应用程序来可视化基因本体(GO)术语富集;然而,这些解决方案往往侧重于显示单个分析的汇总结果,使其不适用于对一系列实验(如时间进程或对不同药物治疗的反应)的分析。由于多对比较正成为RNA分析实验的一个常见特征,缺乏一种轻松比较它们的机制是一个重大问题。因此,为了克服这一障碍,我们开发了GOTermViewer,这是一个应用程序,它以由GOstats确定的数据显示GO术语富集情况,从而可以可视化在时间进程或药物治疗范围内多个单独分析中生理反应的变化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0378/11418229/3b6d8bb5499c/10.1177_11779322241271550-fig1.jpg

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