A Single Visualization Technique for Displaying Multiple Metabolite-Phenotype Associations
A Single Visualization Technique for Displaying Multiple Metabolite-Phenotype Associations
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DOI：
10.3390/metabo9070128
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发表时间：
2019-07-01
期刊：
影响因子：
4.1
通讯作者：
Cheng, Susan
中科院分区：
文献类型：
--
作者：
Henglin, Mir;Niiranen, Teemu;Cheng, Susan
为了帮助管理和解释人类代谢组学数据，这些数据在数量和复杂性上都在迅速增加，我们需要更好的可视化工具。使用从基于人群的社区研究中抽样的1500名个体的队列中分析的数百个代谢物测量数据集，我们对8个人口统计学和临床特征和结果进行了关联分析。我们比较常用的现有的图形方法与一种新的“雨图”的方法来显示这些分析的结果。"雨图"结合了雨滴图和传统热图的特征，以传达多个关联分析的结果。雨图可以同时指示效应大小、方向性和代谢物与几个性状之间关联的统计显著性。这种方法使得能够用给定性状检查所有代谢物的视觉比较特征。雨图扩展了以往的方法，为资料解释提供了补充信息。在代谢组学的数据可视化方面还需要做更多的工作，以帮助研究人员有效、可行和实用地理解和传达大规模分析结果。
To assist with management and interpretation of human metabolomics data, which are rapidly increasing in quantity and complexity, we need better visualization tools. Using a dataset of several hundred metabolite measures profiled in a cohort of similar to 1500 individuals sampled from a population-based community study, we performed association analyses with eight demographic and clinical traits and outcomes. We compared frequently used existing graphical approaches with a novel ` rain plot' approach to display the results of these analyses. The ` rain plot' combines features of a raindrop plot and a conventional heatmap to convey results of multiple association analyses. A rain plot can simultaneously indicate e ff ect size, directionality, and statistical significance of associations between metabolites and several traits. This approach enables visual comparison features of all metabolites examined with a given trait. The rain plot extends prior approaches and o ff ers complementary information for data interpretation. Additional work is needed in data visualizations for metabolomics to assist investigators in the process of understanding and convey large-scale analysis results e ff ectively, feasibly, and practically.