BeeRapp：一款用于多变量行为数据自动化高通量探索性分析的R闪亮应用程序。
beeRapp: an R shiny app for automated high-throughput explorative analysis of multivariate behavioral data.
作者信息
Busch Anne Marie, Kovlyagina Irina, Lutz Beat, Todorov Hristo, Gerber Susanne
机构信息
Institute of Human Genetics, University Medical Center of the Johannes Gutenberg University Mainz, Mainz 55128, Germany.
Institute of Physiological Chemistry, University Medical Center of the Johannes Gutenberg University Mainz, Mainz 55128, Germany.
出版信息
Bioinform Adv. 2022 Nov 7;2(1):vbac082. doi: 10.1093/bioadv/vbac082. eCollection 2022.
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.
摘要
动物行为研究通常会生成高维数据集，这些数据集由跨不同或相关行为领域的多个相关结果测量值组成。在此，我们介绍了行为探索性分析R闪亮应用程序（beeRapp），它以高通量方式促进对行为数据的探索性和推断性分析。通过采用直观且用户友好的图形用户界面，beeRapp使没有编程和数据科学专业知识的行为科学家能够进行聚类、降维、相关性和推断统计，并以标准化和自动化的方式生成多达数千个高质量的输出图来可视化结果。
可用性和实施
本文的代码和数据可在https://github.com/anmabu/beeRapp上获取。
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