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bigPint: A Bioconductor visualization package that makes big data pint-sized

Interactive data visualization is imperative in the biological sciences. The development of independent layers of interactivity has been in pursuit in the visualization community. We developed bigPint, a data visualization package available on Bioconductor under the GPL-3 license (https://bioconduct...

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Detalles Bibliográficos
Autores principales: Rutter, Lindsay, Cook, Dianne
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7347224/
https://www.ncbi.nlm.nih.gov/pubmed/32542031
http://dx.doi.org/10.1371/journal.pcbi.1007912
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author Rutter, Lindsay
Cook, Dianne
author_facet Rutter, Lindsay
Cook, Dianne
author_sort Rutter, Lindsay
collection PubMed
description Interactive data visualization is imperative in the biological sciences. The development of independent layers of interactivity has been in pursuit in the visualization community. We developed bigPint, a data visualization package available on Bioconductor under the GPL-3 license (https://bioconductor.org/packages/release/bioc/html/bigPint.html). Our software introduces new visualization technology that enables independent layers of interactivity using Plotly in R, which aids in the exploration of large biological datasets. The bigPint package presents modernized versions of scatterplot matrices, volcano plots, and litre plots through the implementation of layered interactivity. These graphics have detected normalization issues, differential expression designation problems, and common analysis errors in public RNA-sequencing datasets. Researchers can apply bigPint graphics to their data by following recommended pipelines written in reproducible code in the user manual. In this paper, we explain how we achieved the independent layers of interactivity that are behind bigPint graphics. Pseudocode and source code are provided. Computational scientists can leverage our open-source code to expand upon our layered interactive technology and/or apply it in new ways toward other computational biology tasks.
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spelling pubmed-73472242020-07-20 bigPint: A Bioconductor visualization package that makes big data pint-sized Rutter, Lindsay Cook, Dianne PLoS Comput Biol Research Article Interactive data visualization is imperative in the biological sciences. The development of independent layers of interactivity has been in pursuit in the visualization community. We developed bigPint, a data visualization package available on Bioconductor under the GPL-3 license (https://bioconductor.org/packages/release/bioc/html/bigPint.html). Our software introduces new visualization technology that enables independent layers of interactivity using Plotly in R, which aids in the exploration of large biological datasets. The bigPint package presents modernized versions of scatterplot matrices, volcano plots, and litre plots through the implementation of layered interactivity. These graphics have detected normalization issues, differential expression designation problems, and common analysis errors in public RNA-sequencing datasets. Researchers can apply bigPint graphics to their data by following recommended pipelines written in reproducible code in the user manual. In this paper, we explain how we achieved the independent layers of interactivity that are behind bigPint graphics. Pseudocode and source code are provided. Computational scientists can leverage our open-source code to expand upon our layered interactive technology and/or apply it in new ways toward other computational biology tasks. Public Library of Science 2020-06-15 /pmc/articles/PMC7347224/ /pubmed/32542031 http://dx.doi.org/10.1371/journal.pcbi.1007912 Text en © 2020 Rutter, Cook http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Rutter, Lindsay
Cook, Dianne
bigPint: A Bioconductor visualization package that makes big data pint-sized
title bigPint: A Bioconductor visualization package that makes big data pint-sized
title_full bigPint: A Bioconductor visualization package that makes big data pint-sized
title_fullStr bigPint: A Bioconductor visualization package that makes big data pint-sized
title_full_unstemmed bigPint: A Bioconductor visualization package that makes big data pint-sized
title_short bigPint: A Bioconductor visualization package that makes big data pint-sized
title_sort bigpint: a bioconductor visualization package that makes big data pint-sized
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7347224/
https://www.ncbi.nlm.nih.gov/pubmed/32542031
http://dx.doi.org/10.1371/journal.pcbi.1007912
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