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ViSEAGO: a Bioconductor package for clustering biological functions using Gene Ontology and semantic similarity
The main objective of ViSEAGO package is to carry out a data mining of biological functions and establish links between genes involved in the study. We developed ViSEAGO in R to facilitate functional Gene Ontology (GO) analysis of complex experimental design with multiple comparisons of interest. It...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6685253/ https://www.ncbi.nlm.nih.gov/pubmed/31406507 http://dx.doi.org/10.1186/s13040-019-0204-1 |
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author | Brionne, Aurélien Juanchich, Amélie Hennequet-Antier, Christelle |
author_facet | Brionne, Aurélien Juanchich, Amélie Hennequet-Antier, Christelle |
author_sort | Brionne, Aurélien |
collection | PubMed |
description | The main objective of ViSEAGO package is to carry out a data mining of biological functions and establish links between genes involved in the study. We developed ViSEAGO in R to facilitate functional Gene Ontology (GO) analysis of complex experimental design with multiple comparisons of interest. It allows to study large-scale datasets together and visualize GO profiles to capture biological knowledge. The acronym stands for three major concepts of the analysis: Visualization, Semantic similarity and Enrichment Analysis of Gene Ontology. It provides access to the last current GO annotations, which are retrieved from one of NCBI EntrezGene, Ensembl or Uniprot databases for several species. Using available R packages and novel developments, ViSEAGO extends classical functional GO analysis to focus on functional coherence by aggregating closely related biological themes while studying multiple datasets at once. It provides both a synthetic and detailed view using interactive functionalities respecting the GO graph structure and ensuring functional coherence supplied by semantic similarity. ViSEAGO has been successfully applied on several datasets from different species with a variety of biological questions. Results can be easily shared between bioinformaticians and biologists, enhancing reporting capabilities while maintaining reproducibility. ViSEAGO is publicly available on https://bioconductor.org/packages/ViSEAGO . |
format | Online Article Text |
id | pubmed-6685253 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-66852532019-08-12 ViSEAGO: a Bioconductor package for clustering biological functions using Gene Ontology and semantic similarity Brionne, Aurélien Juanchich, Amélie Hennequet-Antier, Christelle BioData Min Short Report The main objective of ViSEAGO package is to carry out a data mining of biological functions and establish links between genes involved in the study. We developed ViSEAGO in R to facilitate functional Gene Ontology (GO) analysis of complex experimental design with multiple comparisons of interest. It allows to study large-scale datasets together and visualize GO profiles to capture biological knowledge. The acronym stands for three major concepts of the analysis: Visualization, Semantic similarity and Enrichment Analysis of Gene Ontology. It provides access to the last current GO annotations, which are retrieved from one of NCBI EntrezGene, Ensembl or Uniprot databases for several species. Using available R packages and novel developments, ViSEAGO extends classical functional GO analysis to focus on functional coherence by aggregating closely related biological themes while studying multiple datasets at once. It provides both a synthetic and detailed view using interactive functionalities respecting the GO graph structure and ensuring functional coherence supplied by semantic similarity. ViSEAGO has been successfully applied on several datasets from different species with a variety of biological questions. Results can be easily shared between bioinformaticians and biologists, enhancing reporting capabilities while maintaining reproducibility. ViSEAGO is publicly available on https://bioconductor.org/packages/ViSEAGO . BioMed Central 2019-08-06 /pmc/articles/PMC6685253/ /pubmed/31406507 http://dx.doi.org/10.1186/s13040-019-0204-1 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Short Report Brionne, Aurélien Juanchich, Amélie Hennequet-Antier, Christelle ViSEAGO: a Bioconductor package for clustering biological functions using Gene Ontology and semantic similarity |
title | ViSEAGO: a Bioconductor package for clustering biological functions using Gene Ontology and semantic similarity |
title_full | ViSEAGO: a Bioconductor package for clustering biological functions using Gene Ontology and semantic similarity |
title_fullStr | ViSEAGO: a Bioconductor package for clustering biological functions using Gene Ontology and semantic similarity |
title_full_unstemmed | ViSEAGO: a Bioconductor package for clustering biological functions using Gene Ontology and semantic similarity |
title_short | ViSEAGO: a Bioconductor package for clustering biological functions using Gene Ontology and semantic similarity |
title_sort | viseago: a bioconductor package for clustering biological functions using gene ontology and semantic similarity |
topic | Short Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6685253/ https://www.ncbi.nlm.nih.gov/pubmed/31406507 http://dx.doi.org/10.1186/s13040-019-0204-1 |
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