MendelianRandomization: an R package for performing Mendelian randomization analyses using summarized data
By O. Yavors’ka, Stephen Burgess. International Journal of Epidemiology, 2017
1,738 citations recorded by the source corpus.
MendelianRandomization is a software package for the R open-source software environment that performs Mendelian randomization analyses using summarized data. The core functionality is to implement the inverse-variance weighted, MR-Egger, and weighted median methods for multiple genetic variants. Several options are available to the user, such as the use of robust regression, fixed- or random-effects models, and the penalization of weights for genetic variants with heterogeneous causal estimates. Extensions to these methods, such as allowing for variants to be correlated, can be chosen if appropriate. Graphical commands allow summarized data to be displayed in an interactive graph, or the plotting of causal estimates from multiple methods for comparison. Although the main method of data entry is directly by the user, there is also an option for allowing summarized data to be incorporated from the PhenoScanner database of genotype—phenotype associations. We hope to develop this feature in future versions of the package.
Subfields: Genetics
View Paper: https://www.semanticscholar.org/paper/b22ebfa0b8da3608d990e1350d396671ad34a1da
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In Genetics
- J. Bowden
- George Davey Smith
- Gibran Hemani
- Stephen Burgess
- Dylan S. Small
- Philip C. Haycock
- S. Thompson
- E. Sanderson
Citations in the corpus
- Confidence intervals for causal effects with invalid instruments by using two‐stage hard thresholding with voting (2016, positive): “…lasso tuned via cross- validation and the initial median estimator and (d) the unweighted median estimator of Bowden et al. (2016) and Burgess et al. (2016) with bootstrapped confidence intervals by using the R package MendelianRandomization (Yavorska and Burgess, 2017) under default settings.”
- Evaluating the potential role of pleiotropy in Mendelian randomization studies (2018, methodology): “Other software packages are available such as MendelianRandomization (96) and gsmr (62) and in Stata, mrrobust (100).”
- The MR-Base platform supports systematic causal inference across the human phenome (2018, methodology): “The MendelianRandomization R package ( Yavorska and Burgess, 2017 ) is a standalone tool comprising several 2SMR methods and, in addition to the methods that we have implemented, we make it easy to import data from MR-Base into that R package.”