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Genome-wide TWAS of brain and blood tissues identifies novel risk genes for Alzheimer’s disease dementia
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A Profiling of DNA Modifications in Neurodegenerative and Neuropsychiatric Disorders
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Alzheimer's Disease Pathology Imputation and Risk Prediction Using Clinical Indices
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Integrate Proteomics Data with GWAS Summary data for Studying Alzheimer’s Disease by Nonparametric Bayesian Method
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TIGAR-V2 with nonparametric Bayesian eQTL weights estimated from GTEx V8 & Leveraging multiple reference panels to improve TWAS power by ensemble machine learning
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Powerful variance-component method for TWAS identifies novel and known risk genes for Alzheimer’s dementia
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