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Summary Visualizations of Gene Ontology Terms With GO-Figure!
The Gene Ontology (GO) is a cornerstone of functional genomics research that drives discoveries through knowledge-informed computational analysis of biological data from large-scale assays. Key to this success is how the GO can be used to support hypotheses or conclusions about the biology or evolut...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9581009/ https://www.ncbi.nlm.nih.gov/pubmed/36303779 http://dx.doi.org/10.3389/fbinf.2021.638255 |
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author | Reijnders, Maarten J. M. F. Waterhouse, Robert M. |
author_facet | Reijnders, Maarten J. M. F. Waterhouse, Robert M. |
author_sort | Reijnders, Maarten J. M. F. |
collection | PubMed |
description | The Gene Ontology (GO) is a cornerstone of functional genomics research that drives discoveries through knowledge-informed computational analysis of biological data from large-scale assays. Key to this success is how the GO can be used to support hypotheses or conclusions about the biology or evolution of a study system by identifying annotated functions that are overrepresented in subsets of genes of interest. Graphical visualizations of such GO term enrichment results are critical to aid interpretation and avoid biases by presenting researchers with intuitive visual data summaries. Amongst current visualization tools and resources there is a lack of standalone open-source software solutions that facilitate explorations of key features of multiple lists of GO terms. To address this we developed GO-Figure!, an open-source Python software for producing user-customisable semantic similarity scatterplots of redundancy-reduced GO term lists. The lists are simplified by grouping together terms with similar functions using their quantified information contents and semantic similarities, with user-control over grouping thresholds. Representatives are then selected for plotting in two-dimensional semantic space where similar terms are placed closer to each other on the scatterplot, with an array of user-customisable graphical attributes. GO-Figure! offers a simple solution for command-line plotting of informative summary visualizations of lists of GO terms, designed to support exploratory data analyses and dataset comparisons. |
format | Online Article Text |
id | pubmed-9581009 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95810092022-10-26 Summary Visualizations of Gene Ontology Terms With GO-Figure! Reijnders, Maarten J. M. F. Waterhouse, Robert M. Front Bioinform Bioinformatics The Gene Ontology (GO) is a cornerstone of functional genomics research that drives discoveries through knowledge-informed computational analysis of biological data from large-scale assays. Key to this success is how the GO can be used to support hypotheses or conclusions about the biology or evolution of a study system by identifying annotated functions that are overrepresented in subsets of genes of interest. Graphical visualizations of such GO term enrichment results are critical to aid interpretation and avoid biases by presenting researchers with intuitive visual data summaries. Amongst current visualization tools and resources there is a lack of standalone open-source software solutions that facilitate explorations of key features of multiple lists of GO terms. To address this we developed GO-Figure!, an open-source Python software for producing user-customisable semantic similarity scatterplots of redundancy-reduced GO term lists. The lists are simplified by grouping together terms with similar functions using their quantified information contents and semantic similarities, with user-control over grouping thresholds. Representatives are then selected for plotting in two-dimensional semantic space where similar terms are placed closer to each other on the scatterplot, with an array of user-customisable graphical attributes. GO-Figure! offers a simple solution for command-line plotting of informative summary visualizations of lists of GO terms, designed to support exploratory data analyses and dataset comparisons. Frontiers Media S.A. 2021-04-01 /pmc/articles/PMC9581009/ /pubmed/36303779 http://dx.doi.org/10.3389/fbinf.2021.638255 Text en Copyright © 2021 Reijnders and Waterhouse. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Bioinformatics Reijnders, Maarten J. M. F. Waterhouse, Robert M. Summary Visualizations of Gene Ontology Terms With GO-Figure! |
title | Summary Visualizations of Gene Ontology Terms With GO-Figure! |
title_full | Summary Visualizations of Gene Ontology Terms With GO-Figure! |
title_fullStr | Summary Visualizations of Gene Ontology Terms With GO-Figure! |
title_full_unstemmed | Summary Visualizations of Gene Ontology Terms With GO-Figure! |
title_short | Summary Visualizations of Gene Ontology Terms With GO-Figure! |
title_sort | summary visualizations of gene ontology terms with go-figure! |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9581009/ https://www.ncbi.nlm.nih.gov/pubmed/36303779 http://dx.doi.org/10.3389/fbinf.2021.638255 |
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