Genome-wide TWAS of brain and blood tissues identifies novel risk genes for Alzheimer’s disease dementia

Integrate Proteomics Data with GWAS Summary data for Studying Alzheimer’s Disease by Nonparametric Bayesian Method

TIGAR-V2 with nonparametric Bayesian eQTL weights estimated from GTEx V8 & Leveraging multiple reference panels to improve TWAS power by ensemble machine learning

Powerful variance-component method for TWAS identifies novel and known risk genes for Alzheimer’s dementia

Development of Statistical Tool TIGAR for Transcriptome-Integrated Genetic Association Resource