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GlobeCorr: interactive globe-based visualization for correlation datasets
MOTIVATION: Increasingly complex omics datasets are being generated, along with associated diverse categories of metadata (environmental, clinical, etc.). Looking at the correlation between these variables can be critical to identify potential confounding factors and novel relationships. To date, so...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9832964/ https://www.ncbi.nlm.nih.gov/pubmed/36698766 http://dx.doi.org/10.1093/bioadv/vbac099 |
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author | Arab, Mariam Woods, Nolan Garlock, Emma S Winsor, Geoffrey L Parks, Jaclyn P Jia, Baofeng Doiron, Dany Takaro, Tim K Brook, Jeffrey R Brinkman, Fiona S L |
author_facet | Arab, Mariam Woods, Nolan Garlock, Emma S Winsor, Geoffrey L Parks, Jaclyn P Jia, Baofeng Doiron, Dany Takaro, Tim K Brook, Jeffrey R Brinkman, Fiona S L |
author_sort | Arab, Mariam |
collection | PubMed |
description | MOTIVATION: Increasingly complex omics datasets are being generated, along with associated diverse categories of metadata (environmental, clinical, etc.). Looking at the correlation between these variables can be critical to identify potential confounding factors and novel relationships. To date, some correlation globe software has been developed to aid investigations; however, they lack secure, dynamic visualization capability. RESULTS: GlobeCorr.ca is a web-based application designed to provide user-friendly, interactive visualization and analysis of correlation datasets. Users load tabular data listing pairwise variables and their correlation values, and GlobeCorr creates a dynamic visualization using ribbons to represent positive and negative correlations, optionally grouped by domain/category (such as microbiome taxa against other metadata). GlobeCorr runs securely (locally on a user’s computer) and provides a simple method for users to visualize and summarize complex datasets. This tool is applicable to a wide range of disciplines and domains of interest, including the bioinformatics/microbiome and metadata examples provided within. AVAILABILITY AND IMPLEMENTATION: See https://GlobeCorr.ca; Code provided under an open source MIT license: https://github.com/brinkmanlab/globecorr. |
format | Online Article Text |
id | pubmed-9832964 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-98329642023-01-24 GlobeCorr: interactive globe-based visualization for correlation datasets Arab, Mariam Woods, Nolan Garlock, Emma S Winsor, Geoffrey L Parks, Jaclyn P Jia, Baofeng Doiron, Dany Takaro, Tim K Brook, Jeffrey R Brinkman, Fiona S L Bioinform Adv Application Note MOTIVATION: Increasingly complex omics datasets are being generated, along with associated diverse categories of metadata (environmental, clinical, etc.). Looking at the correlation between these variables can be critical to identify potential confounding factors and novel relationships. To date, some correlation globe software has been developed to aid investigations; however, they lack secure, dynamic visualization capability. RESULTS: GlobeCorr.ca is a web-based application designed to provide user-friendly, interactive visualization and analysis of correlation datasets. Users load tabular data listing pairwise variables and their correlation values, and GlobeCorr creates a dynamic visualization using ribbons to represent positive and negative correlations, optionally grouped by domain/category (such as microbiome taxa against other metadata). GlobeCorr runs securely (locally on a user’s computer) and provides a simple method for users to visualize and summarize complex datasets. This tool is applicable to a wide range of disciplines and domains of interest, including the bioinformatics/microbiome and metadata examples provided within. AVAILABILITY AND IMPLEMENTATION: See https://GlobeCorr.ca; Code provided under an open source MIT license: https://github.com/brinkmanlab/globecorr. Oxford University Press 2023-01-06 /pmc/articles/PMC9832964/ /pubmed/36698766 http://dx.doi.org/10.1093/bioadv/vbac099 Text en © The Author(s) 2023. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Application Note Arab, Mariam Woods, Nolan Garlock, Emma S Winsor, Geoffrey L Parks, Jaclyn P Jia, Baofeng Doiron, Dany Takaro, Tim K Brook, Jeffrey R Brinkman, Fiona S L GlobeCorr: interactive globe-based visualization for correlation datasets |
title | GlobeCorr: interactive globe-based visualization for correlation datasets |
title_full | GlobeCorr: interactive globe-based visualization for correlation datasets |
title_fullStr | GlobeCorr: interactive globe-based visualization for correlation datasets |
title_full_unstemmed | GlobeCorr: interactive globe-based visualization for correlation datasets |
title_short | GlobeCorr: interactive globe-based visualization for correlation datasets |
title_sort | globecorr: interactive globe-based visualization for correlation datasets |
topic | Application Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9832964/ https://www.ncbi.nlm.nih.gov/pubmed/36698766 http://dx.doi.org/10.1093/bioadv/vbac099 |
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