Volpato, M., Hull, M. and Carr, I.M. orcid.org/0000-0001-9544-1068
(Cover date: January-December 2024)
GOTermViewer: Visualisation of Gene Ontology enrichment in multiple differential gene expression analyses.
Bioinformatics and Biology Insights, 18.
ISSN 1177-9322
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.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2024. This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
Keywords: | Gene ontology enrichment, RNA seq analysis, next-generation sequencing, differential gene expression analysis |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Medical Research (LIMR) > Division of Molecular Medicine |
Depositing User: | Symplectic Publications |
Date Deposited: | 02 Aug 2024 08:34 |
Last Modified: | 10 Oct 2024 13:10 |
Published Version: | https://journals.sagepub.com/doi/10.1177/117793222... |
Status: | Published |
Publisher: | SAGE Publishing |
Identification Number: | 10.1177/11779322241271550 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:215650 |