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Graph-based exploitation of gene ontology using GOxploreR for scrutinizing biological significance
Gene ontology (GO) is an eminent knowledge base frequently used for providing biological interpretations for the analysis of genes or gene sets from biological, medical and clinical problems. Unfortunately, the interpretation of such results is challenging due to the large number of GO terms, their...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7542435/ https://www.ncbi.nlm.nih.gov/pubmed/33028846 http://dx.doi.org/10.1038/s41598-020-73326-3 |
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author | Manjang, Kalifa Tripathi, Shailesh Yli-Harja, Olli Dehmer, Matthias Emmert-Streib, Frank |
author_facet | Manjang, Kalifa Tripathi, Shailesh Yli-Harja, Olli Dehmer, Matthias Emmert-Streib, Frank |
author_sort | Manjang, Kalifa |
collection | PubMed |
description | Gene ontology (GO) is an eminent knowledge base frequently used for providing biological interpretations for the analysis of genes or gene sets from biological, medical and clinical problems. Unfortunately, the interpretation of such results is challenging due to the large number of GO terms, their hierarchical and connected organization as directed acyclic graphs (DAGs) and the lack of tools allowing to exploit this structural information explicitly. For this reason, we developed the R package GOxploreR. The main features of GOxploreR are (I) easy and direct access to structural features of GO, (II) structure-based ranking of GO-terms, (III) mapping to reduced GO-DAGs including visualization capabilities and (IV) prioritizing of GO-terms. The underlying idea of GOxploreR is to exploit a graph-theoretical perspective of GO as manifested by its DAG-structure and the containing hierarchy levels for cumulating semantic information. That means all these features enhance the utilization of structural information of GO and complement existing analysis tools. Overall, GOxploreR provides exploratory as well as confirmatory tools for complementing any kind of analysis resulting in a list of GO-terms, e.g., from differentially expressed genes or gene sets, GWAS or biomarkers. Our R package GOxploreR is freely available from CRAN. |
format | Online Article Text |
id | pubmed-7542435 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-75424352020-10-14 Graph-based exploitation of gene ontology using GOxploreR for scrutinizing biological significance Manjang, Kalifa Tripathi, Shailesh Yli-Harja, Olli Dehmer, Matthias Emmert-Streib, Frank Sci Rep Article Gene ontology (GO) is an eminent knowledge base frequently used for providing biological interpretations for the analysis of genes or gene sets from biological, medical and clinical problems. Unfortunately, the interpretation of such results is challenging due to the large number of GO terms, their hierarchical and connected organization as directed acyclic graphs (DAGs) and the lack of tools allowing to exploit this structural information explicitly. For this reason, we developed the R package GOxploreR. The main features of GOxploreR are (I) easy and direct access to structural features of GO, (II) structure-based ranking of GO-terms, (III) mapping to reduced GO-DAGs including visualization capabilities and (IV) prioritizing of GO-terms. The underlying idea of GOxploreR is to exploit a graph-theoretical perspective of GO as manifested by its DAG-structure and the containing hierarchy levels for cumulating semantic information. That means all these features enhance the utilization of structural information of GO and complement existing analysis tools. Overall, GOxploreR provides exploratory as well as confirmatory tools for complementing any kind of analysis resulting in a list of GO-terms, e.g., from differentially expressed genes or gene sets, GWAS or biomarkers. Our R package GOxploreR is freely available from CRAN. Nature Publishing Group UK 2020-10-07 /pmc/articles/PMC7542435/ /pubmed/33028846 http://dx.doi.org/10.1038/s41598-020-73326-3 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Manjang, Kalifa Tripathi, Shailesh Yli-Harja, Olli Dehmer, Matthias Emmert-Streib, Frank Graph-based exploitation of gene ontology using GOxploreR for scrutinizing biological significance |
title | Graph-based exploitation of gene ontology using GOxploreR for scrutinizing biological significance |
title_full | Graph-based exploitation of gene ontology using GOxploreR for scrutinizing biological significance |
title_fullStr | Graph-based exploitation of gene ontology using GOxploreR for scrutinizing biological significance |
title_full_unstemmed | Graph-based exploitation of gene ontology using GOxploreR for scrutinizing biological significance |
title_short | Graph-based exploitation of gene ontology using GOxploreR for scrutinizing biological significance |
title_sort | graph-based exploitation of gene ontology using goxplorer for scrutinizing biological significance |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7542435/ https://www.ncbi.nlm.nih.gov/pubmed/33028846 http://dx.doi.org/10.1038/s41598-020-73326-3 |
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