Mendelian Randomization: Methods for Using Genetic Variants in Causal Estimation. S. Burgess and S. G. Thompson (2015). London, UK: Chapman & Hall/CRC Press. 224 pages, ISBN: 9781466573178.

By S. Grover. 2017

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PhenoScanner: a database of human genotype–phenotype associations (2016, unknown): “Such ‘phenome scans’ could help inform a range of analyses, such as Mendelian randomization analyses, in which genetic variants are used as proxies for modifiable risk factors to attempt to infer causality between traits and diseases (Burgess and Thompson, 2015).”
Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians (2018, unknown): “1 9 12 13”
Bias due to participant overlap in two‐sample Mendelian randomization (2016, unknown): “Mendelian randomization is the use of genetic variants as instrumental variables to assess and estimate the causal effect of a risk factor on an outcome from observational data (Davey Smith & Ebrahim, 2003; Burgess & Thompson, 2015).”
Interpreting findings from Mendelian randomization using the MR-Egger method (2017, unknown): “The technique of Mendelian randomization has become a widely-used part of the epidemiologist’s toolkit for investigating causal relationships between risk factors and outcomes using observational data [1, 2].”
MendelianRandomization: an R package for performing Mendelian randomization analyses using summarized data (2017, background): “1,2 Increasingly, Mendelian randomization analyses are being performed using summarized data, in particular the associations (beta-coefficients and standard errors) of each genetic variant with the exposure and outcome variables.”