Cargando…
SR-TWAS: Leveraging Multiple Reference Panels to Improve TWAS Power by Ensemble Machine Learning
Multiple reference panels of a given tissue or multiple tissues often exist, and multiple regression methods could be used for training gene expression imputation models for TWAS. To leverage expression imputation models (i.e., base models) trained with multiple reference panels, regression methods,...
Autores principales: | Parrish, Randy L., Buchman, Aron S., Tasaki, Shinya, Wang, Yanling, Avey, Denis, Xu, Jishu, De Jager, Philip L., Bennett, David A., Epstein, Michael P., Yang, Jingjing |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10327185/ https://www.ncbi.nlm.nih.gov/pubmed/37425698 http://dx.doi.org/10.1101/2023.06.20.23291605 |
Ejemplares similares
-
Novel Variance-Component TWAS method for studying complex human diseases with applications to Alzheimer’s dementia
por: Tang, Shizhen, et al.
Publicado: (2021) -
OTTERS: a powerful TWAS framework leveraging summary-level reference data
por: Dai, Qile, et al.
Publicado: (2023) -
TIGAR-V2: Efficient TWAS tool with nonparametric Bayesian eQTL weights of 49 tissue types from GTEx V8
por: Parrish, Randy L., et al.
Publicado: (2021) -
Tissue specificity-aware TWAS (TSA-TWAS) framework identifies novel associations with metabolic, immunologic, and virologic traits in HIV-positive adults
por: Li, Binglan, et al.
Publicado: (2021) -
TWAS at 20: A History of the Third World Academy of Sciences
por: Schaffer, Daniel
Publicado: (2005)