PrediXcan implementations use elastic net models motivated by our observation that gene expression variation is mostly driven by sparse components27. TWAS implementations have used Bayesian Sparse Linear Mixed Models25 (BSLMM). SMR fits into this scheme with prediction models consisting solely of the top eQTL for each gene (weights are not necessary here since only one SNP is used at a time).
