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Published on: January 7, 2019
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Improving the visualization, interpretation and analysis of two-sample summary data Mendelian randomization via the
Jack Bowden1, Wesley Spiller1, Fabiola Del Greco M2
1MRC Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, UK.
International Journal of Epidemiology
|July 3, 2018
Summary
The Galbraith Radial plot offers a superior method for visualizing Mendelian randomization (MR) study data compared to traditional scatter plots. This improved visualization aids in identifying outliers and interpreting causal effects more effectively.
Area of Science:
- Genetics
- Biostatistics
- Epidemiology
Background:
- Two-sample Mendelian randomization (MR) studies commonly use scatter plots to visualize SNP-outcome associations against SNP-exposure associations.
- Traditional scatter plots face limitations when SNP-outcome associations have varying precision, potentially misrepresenting causal effect estimates.
- The current visualization methods may not adequately reveal individual SNP contributions or conflicts with the overall consensus.
Purpose of the Study:
- To introduce the Galbraith Radial plot as an improved visualization tool for two-sample MR studies.
- To demonstrate the advantages of the Radial plot over traditional scatter plots in data presentation and analysis.
- To propose a more general modeling framework for MR studies, including novel regression techniques.
Main Methods:
- The study proposes the Galbraith Radial plot, a modification of the scatter plot, for MR data visualization.
- This method simplifies data handling by removing the need for genetic data recoding.
- The Radial plot facilitates straightforward detection of outliers and influential data points.
Main Results:
- The Galbraith Radial plot was applied to a two-sample MR study investigating the causal effect of systolic blood pressure on coronary heart disease risk.
- The plot effectively identified an outlying variant responsible for discrepancies between inverse-variance weighted (IVW) and MR-Egger regression estimates.
- Several supplementary plots were introduced to enhance data visualization and interpretation.
Conclusions:
- The Galbraith Radial plot is recommended as a replacement for scatter plots in visualizing, analyzing, and interpreting two-sample summary data MR studies.
- The proposed visualization method aids in detecting influential variants and understanding pleiotropy.
- Associated software is available to support the implementation of the Radial plot in MR analyses.
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