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beeRapp: an R shiny app for automated high-throughput explorative analysis of multivariate behavioral data
Anne Marie Busch1, Irina Kovlyagina2, Beat Lutz2,3
1Institute of Human Genetics, University Medical Center of the Johannes Gutenberg University Mainz, Mainz 55128, Germany.
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.
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