[HTML][HTML] MendelianRandomization v0. 9.0: updates to an R package for performing Mendelian randomization analyses using summarized data
The MendelianRandomization package is a software package written for the R software
environment that implements methods for Mendelian randomization based on summarized …
environment that implements methods for Mendelian randomization based on summarized …
A Bayesian approach to Mendelian randomization using summary statistics in the univariable and multivariable settings with correlated pleiotropy
Mendelian randomization uses genetic variants as instrumental variables to make causal
inferences on the effect of an exposure on an outcome. Due to the recent abundance of high …
inferences on the effect of an exposure on an outcome. Due to the recent abundance of high …
The goldmine of GWAS summary statistics: a systematic review of methods and tools
Genome-wide association studies (GWAS) have revolutionized our understanding of the
genetic architecture of complex traits and diseases. GWAS summary statistics have become …
genetic architecture of complex traits and diseases. GWAS summary statistics have become …
Mendelian randomization: causal inference leveraging genetic data
Mendelian randomization (MR) leverages genetic information to examine the causal
relationship between phenotypes allowing for the presence of unmeasured confounders …
relationship between phenotypes allowing for the presence of unmeasured confounders …
An integrative multi-context Mendelian randomization method for identifying risk genes across human tissues
Mendelian randomization (MR) provides valuable assessments of the causal effect of
exposure on outcome, yet the application of conventional MR methods for mapping risk …
exposure on outcome, yet the application of conventional MR methods for mapping risk …
Combining Mendelian randomization and network deconvolution for inference of causal networks with GWAS summary data
Mendelian randomization (MR) has been increasingly applied for causal inference with
observational data by using genetic variants as instrumental variables (IVs). However, the …
observational data by using genetic variants as instrumental variables (IVs). However, the …
A metabolomic profile of biological aging in 250,341 individuals from the UK Biobank
S Zhang, Z Wang, Y Wang, Y Zhu, Q Zhou… - Nature …, 2024 - nature.com
The metabolomic profile of aging is complex. Here, we analyse 325 nuclear magnetic
resonance (NMR) biomarkers from 250,341 UK Biobank participants, identifying 54 …
resonance (NMR) biomarkers from 250,341 UK Biobank participants, identifying 54 …
A robust cis-Mendelian randomization method with application to drug target discovery
Z Lin, W Pan - Nature Communications, 2024 - nature.com
Mendelian randomization (MR) uses genetic variants as instrumental variables (IVs) to
investigate causal relationships between traits. Unlike conventional MR, cis-MR focuses on …
investigate causal relationships between traits. Unlike conventional MR, cis-MR focuses on …
Collider bias correction for multiple covariates in GWAS using robust multivariable Mendelian randomization
Genome-wide association studies (GWAS) have identified many genetic loci associated with
complex traits and diseases in the past 20 years. Multiple heritable covariates may be added …
complex traits and diseases in the past 20 years. Multiple heritable covariates may be added …
An augmented Mendelian randomization approach provides causality of brain imaging features on complex traits in a single biobank-scale dataset
Mendelian randomization (MR) is an effective approach for revealing causal risk factors that
underpin complex traits and diseases. While MR has been more widely applied under two …
underpin complex traits and diseases. While MR has been more widely applied under two …