MR Dictionary

Hierarchical joint Analysis of Marginal summary statistics (hJAM)

MR that analyses marginal summary statistics (i.e., information about associations between single nucleotide polymorphisms (SNPs) and traits from genome-wide association studies (GWASs)) under a hierarchical joint multi-SNP model to identify genetic variants for fine mapping.

Originally proposed to harmonize frameworks that exist between MR and transcriptome-wide association studies (TWASs), the latter of which identifies SNPs associated with gene expression and uses these to estimate the association between predicted gene expression and traits. Both methods of which suffer from pleiotropy due to the multi-functional nature of many genes. The method is useful in situations where multiple traits exist on the causal pathway between the instrumental variables (IVs) and the outcome and/or the SNPs being used as IVs are correlated.


Other terms in 'Pleiotropy-robust two-sample MR methods':