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beeRapp: an R shiny app for automated high-throughput explorative analysis of multivariate behavioral data
SUMMARY: Animal behavioral studies typically generate high-dimensional datasets consisting of multiple correlated outcome measures across distinct or related behavioral domains. Here, we introduce the BEhavioral Explorative analysis R shiny APP (beeRapp) that facilitates explorative and inferential...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9710645/ https://www.ncbi.nlm.nih.gov/pubmed/36699414 http://dx.doi.org/10.1093/bioadv/vbac082 |
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author | Busch, Anne Marie Kovlyagina, Irina Lutz, Beat Todorov, Hristo Gerber, Susanne |
author_facet | Busch, Anne Marie Kovlyagina, Irina Lutz, Beat Todorov, Hristo Gerber, Susanne |
author_sort | Busch, Anne Marie |
collection | PubMed |
description | SUMMARY: Animal behavioral studies typically generate high-dimensional datasets consisting of multiple correlated outcome measures across distinct or related behavioral domains. Here, we introduce the BEhavioral Explorative analysis R shiny APP (beeRapp) that facilitates explorative and inferential analysis of behavioral data in a high-throughput fashion. By employing an intuitive and user-friendly graphical user interface, beeRapp empowers behavioral scientists without programming and data science expertise to perform clustering, dimensionality reduction, correlational and inferential statistics and produce up to thousands of high-quality output plots visualizing results in a standardized and automated way. AVAILABILITY AND IMPLEMENTATION: The code and data underlying this article are available at https://github.com/anmabu/beeRapp. |
format | Online Article Text |
id | pubmed-9710645 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-97106452023-01-24 beeRapp: an R shiny app for automated high-throughput explorative analysis of multivariate behavioral data Busch, Anne Marie Kovlyagina, Irina Lutz, Beat Todorov, Hristo Gerber, Susanne Bioinform Adv Application Note SUMMARY: Animal behavioral studies typically generate high-dimensional datasets consisting of multiple correlated outcome measures across distinct or related behavioral domains. Here, we introduce the BEhavioral Explorative analysis R shiny APP (beeRapp) that facilitates explorative and inferential analysis of behavioral data in a high-throughput fashion. By employing an intuitive and user-friendly graphical user interface, beeRapp empowers behavioral scientists without programming and data science expertise to perform clustering, dimensionality reduction, correlational and inferential statistics and produce up to thousands of high-quality output plots visualizing results in a standardized and automated way. AVAILABILITY AND IMPLEMENTATION: The code and data underlying this article are available at https://github.com/anmabu/beeRapp. Oxford University Press 2022-11-07 /pmc/articles/PMC9710645/ /pubmed/36699414 http://dx.doi.org/10.1093/bioadv/vbac082 Text en © The Author(s) 2022. 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 Busch, Anne Marie Kovlyagina, Irina Lutz, Beat Todorov, Hristo Gerber, Susanne beeRapp: an R shiny app for automated high-throughput explorative analysis of multivariate behavioral data |
title | beeRapp: an R shiny app for automated high-throughput explorative analysis of multivariate behavioral data |
title_full | beeRapp: an R shiny app for automated high-throughput explorative analysis of multivariate behavioral data |
title_fullStr | beeRapp: an R shiny app for automated high-throughput explorative analysis of multivariate behavioral data |
title_full_unstemmed | beeRapp: an R shiny app for automated high-throughput explorative analysis of multivariate behavioral data |
title_short | beeRapp: an R shiny app for automated high-throughput explorative analysis of multivariate behavioral data |
title_sort | beerapp: an r shiny app for automated high-throughput explorative analysis of multivariate behavioral data |
topic | Application Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9710645/ https://www.ncbi.nlm.nih.gov/pubmed/36699414 http://dx.doi.org/10.1093/bioadv/vbac082 |
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