Summary Visualizations of Gene Ontology Terms With GO-Figure!

Détails

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Etat: Public
Version: Final published version
Licence: Non spécifiée
ID Serval
serval:BIB_488C95053B55
Type
Article: article d'un périodique ou d'un magazine.
Sous-type
Compte-rendu: analyse d'une oeuvre publiée.
Collection
Publications
Institution
Titre
Summary Visualizations of Gene Ontology Terms With GO-Figure!
Périodique
Frontiers in Bioinformatics
Auteur(s)
Reijnders Maarten J. M. F., Waterhouse Robert M.
ISSN
2673-7647
Statut éditorial
Publié
Date de publication
01/04/2021
Peer-reviewed
Oui
Volume
1
Langue
anglais
Résumé
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.
Open Access
Oui
Financement(s)
Fonds national suisse / Carrières / PP00P3_170664
Création de la notice
01/04/2021 11:33
Dernière modification de la notice
02/04/2021 7:09
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