Department of Life Sciences, Imperial College London, London, United Kingdom.
Institute for Neuro- and Behavioral Biology, Westfälische Wilhelms University, 48149 Münster, Germany.
PLoS One. 2019 Jan 16;14(1):e0209331. doi: 10.1371/journal.pone.0209331. eCollection 2019.
The recent development of automatised methods to score various behaviours on a large number of animals provides biologists with an unprecedented set of tools to decipher these complex phenotypes. Analysing such data comes with several challenges that are largely shared across acquisition platform and paradigms. Here, we present rethomics, a set of R packages that unifies the analysis of behavioural datasets in an efficient and flexible manner. rethomics offers a computational solution to storing, manipulating and visualising large amounts of behavioural data. We propose it as a tool to bridge the gap between behavioural biology and data sciences, thus connecting computational and behavioural scientists. rethomics comes with a extensive documentation as well as a set of both practical and theoretical tutorials (available at https://rethomics.github.io).
最近自动化方法的发展为生物学家在大量动物身上对各种行为进行评分提供了前所未有的工具，以破解这些复杂的表型。分析此类数据存在一些挑战，这些挑战在很大程度上跨越了采集平台和范例。在这里，我们提出了 rethomics，这是一组 R 包，以高效灵活的方式统一了行为数据集的分析。rethomics 为存储、操作和可视化大量行为数据提供了一种计算解决方案。我们建议将其作为连接行为生物学和数据科学的桥梁，从而将计算科学家和行为科学家联系起来。rethomics 提供了广泛的文档以及实用和理论教程（可在 https://rethomics.github.io 上获得）。
