Laboratory Automated Interrogation of Data: an interactive web application for visualization of multilevel data from biological experiments

被引:0
作者
Dando, Owen R. [1 ,2 ,3 ,4 ]
Kozic, Zrinko [1 ,4 ]
Booker, Sam A. [1 ,2 ,4 ]
Hardingham, Giles E. [1 ,2 ,3 ,4 ]
Kind, Peter C. [1 ,2 ,4 ]
机构
[1] Univ Edinburgh, Simons Initiat Developing Brain, Edinburgh EH8 9XD, Scotland
[2] Univ Edinburgh, Patrick Wild Ctr, Edinburgh EH8 9XD, Scotland
[3] Univ Edinburgh, UK Dementia Res Inst, Edinburgh EH16 4SB, Scotland
[4] Univ Edinburgh, Ctr Discovery Brain Sci, Edinburgh EH8 9XD, Scotland
关键词
data; visualization; automatization; statistics; R Shiny; CLUSTERED DATA; TOOL;
D O I
10.1093/braincomms/fcae074
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
A key step in understanding the results of biological experiments is visualization of the data. Many laboratory experiments contain a range of measurements that exist within a hierarchy of interdependence. An automated and facile way to visualize and interrogate such multilevel data, across many experimental variables, would (i) lead to improved understanding of the results, (ii) help to avoid misleading interpretation of statistics and (iii) easily identify outliers and sources of batch and confounding effects. While many excellent graphing solutions already exist, they are often geared towards the production of publication-ready plots and the analysis of a single variable at a time, require programming expertise or are unnecessarily complex for the task at hand. Here, we present Laboratory Automated Interrogation of Data (LAB-AID), an interactive tool specifically designed to automatically visualize and query hierarchical data resulting from biological experiments. Dando et al. present Laboratory Automated Interrogation of Data (LAB-AID), an interactive software tool to visualize and query hierarchical data resulting from biological experiments. LAB-AID helps biologists to understand results, identify outliers and sources of batch and confounding effects and avoid common statistical errors such as pseudoreplication.
引用
收藏
页数:8
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