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

Gene ontology enrichment RNA seq analysis differential gene expression analysis next-generation sequencing

Journal

Bioinformatics and biology insights
ISSN: 1177-9322
Titre abrégé: Bioinform Biol Insights
Pays: United States
ID NLM: 101467187

Informations de publication

Date de publication:
2024
Historique:
received: 17 10 2023
accepted: 29 06 2024
medline: 24 9 2024
pubmed: 24 9 2024
entrez: 24 9 2024
Statut: epublish

Résumé

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.

Identifiants

pubmed: 39315117
doi: 10.1177/11779322241271550
pii: 10.1177_11779322241271550
pmc: PMC11418229
doi:

Types de publication

Journal Article

Langues

eng

Pagination

11779322241271550

Informations de copyright

© The Author(s) 2024.

Déclaration de conflit d'intérêts

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Auteurs

Milene Volpato (M)

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

Mark Hull (M)

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

Ian M Carr (IM)

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

Classifications MeSH