Steiger filtering
Resources
Code (Language: R) Website Paper (Pub Date: 2017-08-10)
Other URLS: none
Method Contact: Gibran Hemani ( g.hemani@bristol.ac.uk)
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
Steiger filtering aims to improve MR analyses by identifying genetic factors that primarily associate with an unintended trait. For example in the situation where the hypothesised outcome in fact influences the hypothesised exposure, apparent instruments for the exposure may primarily associate with the outcome, and lead to bias in the MR estimate. Steiger filtering aims to remove such instruments from the data prior to analysis.