Bayesian Mendelian Randomization
Bayesian Mendelian Randomization is a statistical framework that integrates Bayesian inference with Mendelian randomization to estimate causal effects in genetic epidemiology by incorporating prior knowledge and uncertainty in genetic instruments, exposure, and outcome relationships.
47
Publications
2.8K
Citations
314
Authors
166
Institutions
Publications per year
2017–2026
42
Parents
47
Bayesian weighted Mendelian randomization for causal inference based on summary statistics
Jia Zhao, Jingsi Ming, Xianghong Hu et al. · Bioinformatics · 2019 · 363 citations · Full text
Shared polygenic risk and causal inferences in amyotrophic lateral sclerosis
Sara Bandrés‐Ciga, Alastair J. Noyce, Gibran Hemani et al. · Annals of Neurology · 2019 · 164 citations · Full text
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MRC Biostatistics Unit
Cambridge, United Kingdom
6 h-index
12 publications
433 citations

University of Bristol
Bristol, United Kingdom
6 h-index
20 publications
1.4K citations

Chinese Academy of Medical Sciences & Peking Union Medical College
Beijing, China
5 h-index
28 publications
1.6K citations
University College London
London, United Kingdom
5 h-index
7 publications
497 citations

Imperial College London
London, United Kingdom
4 h-index
6 publications
426 citations

Zhejiang University
Hangzhou, China
4 h-index
28 publications
1.3K citations
University of Cambridge
Cambridge, United Kingdom
4 h-index
8 publications
237 citations
Medical Research Council
London, United Kingdom
3 h-index
4 publications
302 citations
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3 publications · 161 citations
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3 publications · 91 citations
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3 publications · 409 citations
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PNAS · 2 publications · 176 citations
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JCEM · 2 publications · 147 citations
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