A Single Visualization Technique for Displaying Multiple Metabolite-Phenotype Associations

TL;DR

This paper introduces an innovative rain plot visualization technique that consolidates complex metabolite-phenotype association results into a single, comprehensive graphic, enhancing interpretability of large-scale metabolomics data.

Contribution

The study presents a novel rain plot method that effectively visualizes multiple metabolite-phenotype associations in one view, improving upon existing graphical approaches.

Findings

Rain plot combines raindrop and heatmap features for clarity.

Facilitates comparison across metabolites and clinical outcomes.

Applicable to various molecular phenotyping datasets.

Abstract

More advanced visualization tools are needed to assist with the analyses and interpretation of human metabolomics data, which are rapidly increasing in quantity and complexity. Using a dataset of several hundred bioactive lipid metabolites profiled in a cohort of over 1400 individuals sampled from a population-based community study, we performed a comprehensive set of association analyses relating all metabolites with eight demographic and cardiometabolic traits and outcomes. We then compared existing graphical approaches with an adapted rain plot approach to display the results of these analyses. The rain plot combines the features of a raindrop plot and a parallel heatmap approach to succinctly convey, in a single visualization, the results of relating complex metabolomics data with multiple phenotypes. This approach complements existing tools, particularly by facilitating comparisons between individual metabolites and across a range of pre-specified clinical outcomes. We anticipate that this single visualization technique may be further extended and applied to alternate study designs using different types of molecular phenotyping data.