LHC-MR
Resources
Code (Language: R) Website Paper (Pub Date: 2021-12-14)
Other URLS: none
Method Contact: Liza Darrous ( none)
Entry Contact: Jean Morrison ( jvmorr@umich.edu)
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
We propose a Latent Heritable Confounder MR (LHC-MR) method applicable to association summary statistics, which estimates bi-directional causal effects, direct heritability, and confounder effects while accounting for sample overlap.