Improving the visualization, interpretation and analysis of two-sample summary data Mendelian randomization via the Radial plot and Radial regression
By J. Bowden, Wes Spiller, F. Del Greco M, Nuala Sheehan, J. Thompson, Cosetta Minelli, George Davey Smith. International Journal of Epidemiology, 2018
561 citations recorded by the source corpus.
Background: Summary data furnishing a two-sample Mendelian randomization (MR) study are often visualized with the aid of a scatter plot, in which single-nucleotide polymorphism (SNP)–outcome associations are plotted against the SNP–exposure associations to provide an immediate picture of the causal-effect estimate for each individual variant. It is also convenient to overlay the standard inverse-variance weighted (IVW) estimate of causal effect as a fitted slope, to see whether an individual SNP provides evidence that supports, or conflicts with, the overall consensus. Unfortunately, the traditional scatter plot is not the most appropriate means to achieve this aim whenever SNP–outcome associations are estimated with varying degrees of precision and this is reflected in the analysis. Methods: We propose instead to use a small modification of the scatter plot—the Galbraith Radial plot—for the presentation of data and results from an MR study, which enjoys many advantages over the original method. On a practical level, it removes the need to recode the genetic data and enables a more straightforward detection of outliers and influential data points. Its use extends beyond the purely aesthetic, however, to suggest a more general modelling framework to operate within when conducting an MR study, including a new form of MR-Egger regression. Results: We illustrate the methods using data from a two-sample MR study to probe the causal effect of systolic blood pressure on coronary heart disease risk, allowing for the possible effects of pleiotropy. The Radial plot is shown to aid the detection of a single outlying variant that is responsible for large differences between IVW and MR-Egger regression estimates. Several additional plots are also proposed for informative data visualization.
Subfields: Genetics
View Paper: https://www.semanticscholar.org/paper/b75479c7603ae23143465f66f355c94b7d506c06
How researchers see this paper
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In Genetics
- Gibran Hemani
- J. Bowden
- Michael Holmes
- George Davey Smith
- Stephen Burgess
- E. Sanderson
- S. Thompson
- Deborah Lawlor
Citations in the corpus
- Meta‐analysis and Mendelian randomization: A review (2019, methodology): “The Galbraith radial plot has additionally been repurposed for detecting outlying variants in MR.28”
- Evaluating the potential role of pleiotropy in Mendelian randomization studies (2018, methodology): “The detection of outliers is also automated in the Radial MR framework (59).”
- Statistical inference in two-sample summary-data Mendelian randomization using robust adjusted profile score (2018, unknown): “[11] proposed a radial plot β̂j √ wj versus √ wj , where wj is the “weight” of the j th SNP in (3.”