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Related papers: A Robust Framework for Two-Sample Mendelian Random…

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Mendelian randomization (MR) is a method of exploiting genetic variation to unbiasedly estimate a causal effect in presence of unmeasured confounding. MR is being widely used in epidemiology and other related areas of population science. In…

Applications · Statistics 2019-01-03 Qingyuan Zhao , Jingshu Wang , Gibran Hemani , Jack Bowden , Dylan S. Small

Two-sample summary-data Mendelian randomization (MR) has become a popular research design to estimate the causal effect of risk exposures. With the sample size of GWAS continuing to increase, it is now possible to utilize genetic…

Applications · Statistics 2018-11-20 Qingyuan Zhao , Yang Chen , Jingshu Wang , Dylan S. Small

Mendelian randomization is the use of genetic variants to assess the existence of a causal relationship between a risk factor and an outcome of interest. Here, we focus on two-sample summary-data Mendelian randomization analyses with many…

Quantitative Methods · Quantitative Biology 2022-09-16 Apostolos Gkatzionis , Stephen Burgess , Paul J. Newcombe

Mendelian randomization is the use of genetic variants to make causal inferences from observational data. The field is currently undergoing a revolution fuelled by increasing numbers of genetic variants demonstrated to be associated with…

Methodology · Statistics 2018-08-31 Stephen Burgess , Jack Bowden , Frank Dudbridge , Simon G Thompson

In the past decade, the increased availability of genome-wide association studies summary data has popularized Mendelian Randomization (MR) for conducting causal inference. MR analyses, incorporating genetic variants as instrumental…

Methodology · Statistics 2025-08-26 Zhongming Xie , Wanheng Zhang , Jingshen Wang , Chong Wu

Mendelian randomization (MR) has become an essential tool for causal inference in biomedical and public health research. By using genetic variants as instrumental variables, MR helps address unmeasured confounding and reverse causation,…

Methodology · Statistics 2025-11-04 Minhao Yao , Anqi Wang , Xihao Li , Zhonghua Liu

Mendelian randomization (MR) is a powerful method that uses genetic variants as instrumental variables (IVs) to infer the causal effect of a modifiable exposure on an outcome. Although recent years have seen many extensions of basic MR…

Methodology · Statistics 2022-03-15 Sai Li , Ting Ye

Estimating the causal effect of an exposure on an outcome is an important task in many economical and biological studies. Mendelian randomization, in particular, uses genetic variants as instruments to estimate causal effects in…

Methodology · Statistics 2017-06-06 Sai Li

Mendelian Randomization (MR) is a popular method in epidemiology and genetics that uses genetic variation as instrumental variables for causal inference. Existing MR methods usually assume most genetic variants are valid instrumental…

Applications · Statistics 2022-06-15 Daniel Iong , Qingyuan Zhao , Yang Chen

Mendelian randomization uses genetic variants to make causal inferences about the effect of a risk factor on an outcome. With fine-mapped genetic data, there may be hundreds of genetic variants in a single gene region any of which could be…

Methodology · Statistics 2017-07-10 Stephen Burgess , Verena Zuber , Elsa Valdes-Marquez , Benjamin B Sun , Jemma C Hopewell

Mendelian randomization is the use of genetic variants as instrumental variables to assess whether a risk factor is a cause of a disease outcome. Increasingly, Mendelian randomization investigations are conducted on the basis of summarized…

Applications · Statistics 2015-12-15 Stephen Burgess , Jack Bowden

Mendelian randomization uses genetic variants to make causal inferences about a modifiable exposure. Subject to a genetic variant satisfying the instrumental variable assumptions, an association between the variant and outcome implies a…

Methodology · Statistics 2018-04-17 Stephen Burgess , Jeremy A Labrecque

Valid estimation of a causal effect using instrumental variables requires that all of the instruments are independent of the outcome conditional on the risk factor of interest and any confounders. In Mendelian randomization studies with…

Methodology · Statistics 2020-11-23 Andrew J. Grant , Stephen Burgess

Background: Mendelian randomization (MR) has been widely applied to causal inference in medical research. It uses genetic variants as instrumental variables (IVs) to investigate putative causal relationship between an exposure and an…

Methodology · Statistics 2020-11-04 Linyi Zou , Hui Guo , Carlo Berzuini

Mendelian Randomization (MR) is a prominent observational epidemiological research method designed to address unobserved confounding when estimating causal effects. However, core assumptions -- particularly the independence between…

Machine Learning · Computer Science 2026-02-24 Shimeng Huang , Matthew Robinson , Francesco Locatello

Mendelian randomization (MR) is a statistical method exploiting genetic variants as instrumental variables to estimate the causal effect of modifiable risk factors on an outcome of interest. Despite wide uses of various popular two-sample…

Methodology · Statistics 2021-11-17 Anqi Wang , Zhonghua Liu

With the evolution of single-cell RNA sequencing techniques into a standard approach in genomics, it has become possible to conduct cohort-level causal inferences based on single-cell-level measurements. However, the individual gene…

Methodology · Statistics 2025-04-23 Jin-Hong Du , Zhenghao Zeng , Edward H. Kennedy , Larry Wasserman , Kathryn Roeder

Background: Mendelian randomization (MR) is a useful approach to causal inference from observational studies when randomised controlled trials are not feasible. However, study heterogeneity of two association studies required in MR is often…

Methodology · Statistics 2021-12-16 Linyi Zou , Hui Guo , Carlo Berzuini

Mendelian randomization is an instrumental variable method that utilizes genetic information to investigate the causal effect of a modifiable exposure on an outcome. In most cases, the exposure changes over time. Understanding the…

Methodology · Statistics 2024-03-11 Haodong Tian , Ashish Patel , Stephen Burgess

Multivariable Mendelian randomization estimates the causal effect of multiple exposures on an outcome, typically using summary statistics of genetic variant associations. However, exposures of interest in Mendelian randomization…

Methodology · Statistics 2022-03-17 Jiazheng Zhu , Stephen Burgess , Andrew J. Grant
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