GSMR
Resources
Code (Language: R) Website Paper (Pub Date: 2018-01-15)
Other URLS: none
Method Contact: Jian Yang ( jian.yang@westlake.edu.cn)
Entry Contact: Gibran Hemani ( g.hemani@bristol.ac.uk)
Context
Analysis Type: UVMR MVMR Network MR Bi-Directional MR Non-Linear
Input Data Types: Ind/Ind Ind/SS SS/Ind SS/SSfamily
Exposure Trait Types: Quantitative Binary Time to event
Outcome Trait Types: Quantitative Binary Time to event
Assumptions and Sources of Bias
| Source of Bias | Addressed |
|---|---|
| Weak instruments | ✗ |
| Winner’s curse | ✗ |
| Sample overlap | ✗ |
| Uncorrelated horizontal pleiotropy | ✓ |
| Correlated horizontal pleiotropy | ✗ |
| Ancestry differences in samples | ✗ |
| Residual confounding in GWAS | ✗ |
| Cross-trait assortative mating | ✗ |
| Index-event/conditioning on heritable trait | ✗ |
Description
GSMR performs a multi-SNP Mendelian randomization analysis using summary-level data from genome-wide association studies, allowing for outlier removal to account for pleiotropy, multivariable models, correlation of instruments and bi-directional effect estimation.