Department of Ecology and Evolutionary Biology, Brown University, Providence, RI 02912, USA
Department of Ecology and Evolutionary Biology, Brown University, Providence, RI 02912, USA.
J Exp Biol. 2021 Jan 15;224(Pt 2):jeb229377. doi: 10.1242/jeb.229377.
Negative geotaxis (climbing) performance is a useful metric for quantifying health. Manual methods to quantify climbing performance are tedious and often biased, while many available computational methods have challenging hardware or software requirements. We present an alternative: FreeClimber. This open source, Python-based platform subtracts a video's static background to improve detection for flies moving across heterogeneous backgrounds. FreeClimber calculates a cohort's velocity as the slope of the most linear portion of a mean vertical position versus time curve. It can run from a graphical user interface for optimization or a command line interface for high-throughput and automated batch processing, improving accessibility for users with different expertise. FreeClimber outputs calculated slopes, spot locations for follow-up analyses (e.g. tracking), and several visualizations and plots. We demonstrate FreeClimber's utility in a longitudinal study for endurance exercise performance in mitonuclear genotypes using six distinct mitochondrial haplotypes paired with a common nuclear background.
负趋地性（攀爬）表现是量化健康的有用指标。手动量化攀爬表现既繁琐又常常存在偏差，而许多现有的计算方法则具有挑战性的硬件或软件要求。我们提出了一种替代方法：FreeClimber。这个基于 Python 的开源平台通过减去视频的静态背景来提高对在异质背景中移动的苍蝇的检测效果。FreeClimber 计算群体的速度作为平均垂直位置随时间变化的最线性部分的斜率。它可以从图形用户界面进行优化，也可以从命令行界面进行高通量和自动化批处理，为具有不同专业知识的用户提供更好的可访问性。FreeClimber 输出计算出的斜率、用于后续分析（例如跟踪）的斑点位置，以及几个可视化和图表。我们展示了 FreeClimber 在使用六个不同的线粒体单倍型与一个常见的核背景配对的耐力运动表现的纵向研究中的实用性。
