Department of Genetics and Genome Biology, University of Leicester, Leicester, UK.
School of Biology and Ecology, University of Maine, Orono, Maine, USA.
J Biol Rhythms. 2020 Jun;35(3):235-245. doi: 10.1177/0748730420901929. Epub 2020 Feb 25.
From 1980 to 1991, Kyriacou, Hall, and collaborators (K&H) reported that the courtship song has a 1-min cycle in the length of mean interpulse intervals (IPIs) that is modulated by circadian rhythm mutations. In 2014, Stern failed to replicate these results using a fully automated method for detecting song pulses. Manual annotation of Stern's song records exposed a ~50% error rate in detection of IPIs, but the corrected data revealed -dependent IPI cycles using a variety of statistical methods. In 2017, Stern et al. dismissed the sine/cosine method originally used by K&H to detect significant cycles, claiming that randomized songs showed as many significant values as real data using cosinor analysis. We first identify a simple mathematical error in Stern et al.'s cosinor implementation that invalidates their critique of the method. Stern et al. also concluded that although the manually corrected wild-type and mutant songs show similar periods to those observed by K&H, each song is usually not significantly rhythmic by the Lomb-Scargle (L-S) periodogram, so any genotypic effect simply reflects "noise." Here, we observe that L-S is extremely conservative compared with 3 other time-series analyses in assessing the significance of rhythmicity, both for conventional locomotor activity data collected in equally spaced time bins and for unequally spaced song records. Using randomization of locomotor and song data to generate confidence limits for L-S instead of the theoretically derived values, we find that L-S is now consistent with the other methods in determining significant rhythmicity in locomotor and song records and that it confirms dependent song cycles. We conclude that Stern and colleagues' failure to identify song cycles stems from the limitations of automated methods in accurately reflecting song parameters, combined with the use of an overly stringent method to discriminate rhythmicity in courtship songs.
从 1980 年到 1991 年,Kyriacou、Hall 和合作者(K&H)报告说,求爱歌曲的平均脉冲间隔(IPI)具有 1 分钟的周期,该周期受昼夜节律突变的调制。2014 年,Stern 使用完全自动化的方法检测歌曲脉冲未能复制这些结果。对 Stern 歌曲记录的手动注释暴露了检测 IPI 时约 50%的错误率,但使用各种统计方法校正数据后显示出了依赖于昼夜节律的 IPI 周期。2017 年,Stern 等人驳回了 K&H 最初用于检测显著周期的正弦/余弦方法,声称使用余弦分析,随机歌曲显示的显著值与真实数据一样多。我们首先确定了 Stern 等人的余弦实施中的一个简单数学错误,该错误使他们对该方法的批评无效。Stern 等人还得出结论,尽管手动校正的野生型和突变型歌曲显示出与 K&H 观察到的相似的周期,但每个歌曲通常都不是通过 Lomb-Scargle(L-S)周期图显著有节奏的,因此任何基因型效应只是反映了“噪音”。在这里,我们观察到与其他 3 种时间序列分析相比,L-S 在评估节律性的显著性方面非常保守,无论是对于在等间隔时间箱中收集的传统运动活动数据还是对于不等间隔的歌曲记录。通过对运动和歌曲数据进行随机化以生成 L-S 的置信限,而不是使用理论上推导的值,我们发现 L-S 现在与其他方法一致,用于确定运动和歌曲记录中的显著节律性,并确认了依赖于昼夜节律的歌曲周期。我们得出结论,Stern 和同事未能识别歌曲周期的原因是自动化方法在准确反映歌曲参数方面的局限性,再加上使用过于严格的方法来区分求爱歌曲中的节律性。