A1 Refereed original research article in a scientific journal
A Single Visualization Technique for Displaying Multiple Metabolite-Phenotype Associations
Authors: Henglin M., Niiranen T., Watrous J.D., Lagerborg K.A., Antonelli J., Claggett B.L., Demosthenes E.J., von Jeinsen B., Demler O., Vasan R.S., Larson M.G., Jain M., Cheng S.
Publisher: MDPI
Publication year: 2019
Journal: Metabolites
Journal acronym: METABOLITES
Article number: ARTN 128
Volume: 9
Issue: 7
Number of pages: 7
DOI: https://doi.org/10.3390/metabo9070128
Web address : https://www.mdpi.com/2218-1989/9/7/128
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/42158632
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.
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