Simple and Quick Visualization of Periodical Data Using Microsoft Excel

被引:6
|
作者
Oike, Hideaki [1 ,2 ]
Ogawa, Yukino [1 ]
Oishi, Katsutaka [2 ,3 ,4 ,5 ]
机构
[1] Natl Agr & Food Res Org NARO, Food Res Inst, Tsukuba, Ibaraki 3058642, Japan
[2] Natl Inst Adv Ind Sci & Technol, Biomed Res Inst, Biol Clock Res Grp, Tsukuba, Ibaraki 3058566, Japan
[3] Tokyo Univ Sci, Grad Sch Sci & Technol, Dept Appl Biol Sci, Noda, Chiba 2788510, Japan
[4] Univ Tokyo, Grad Sch Frontier Sci, Dept Computat Biol & Med Sci, Kashiwa, Chiba 2778562, Japan
[5] Univ Tsukuba, Sch Integrat & Global Majors SIGMA, Tsukuba, Ibaraki 3058577, Japan
关键词
actogram; heatmap; biological rhythm; circadian clock; chronobiology; sleep pattern; ECG; EEG;
D O I
10.3390/mps2040081
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Actograms are well-established methods used for visualizing periodic activity of animals in chronobiological research. They help in the understanding of the overall characteristics of rhythms and are instrumental in defining the direction of subsequent detailed analysis. Although there exists specialized software for creating actograms, new users such as students and researchers from other fields often find it inconvenient to use. In this study, we demonstrate a fast and easy method to create actograms using Microsoft Excel. As operations in Excel are simple and user-friendly, it takes only a few minutes to create an actogram. Using this method, it is possible to obtain a visual understanding of the characteristics of rhythms not only from typical activity data, but also from any kind of time-series data such as body temperature, blood sugar level, gene expressions, sleep electroencephalogram, heartbeat, and so on. The actogram thus created can also be converted to the "heatogram" shown by color temperature. As opposed to conventional chronograms, this new type of chronogram facilitates easy understanding of rhythmic features in a more intuitive manner. This method is therefore convenient and beneficial for a broad range of researchers including students as it aids in the better understanding of periodic phenomena from a large amount of time-series data.
引用
收藏
页码:1 / 11
页数:11
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