Cargando…
graph-GPA 2.0: improving multi-disease genetic analysis with integration of functional annotation data
Genome-wide association studies (GWAS) have successfully identified a large number of genetic variants associated with traits and diseases. However, it still remains challenging to fully understand the functional mechanisms underlying many associated variants. This is especially the case when we are...
Autores principales: | Deng, Qiaolan, Gupta, Arkobrato, Jeon, Hyeongseon, Nam, Jin Hyun, Yilmaz, Ayse Selen, Chang, Won, Pietrzak, Maciej, Li, Lang, Kim, Hang J., Chung, Dongjun |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10370274/ https://www.ncbi.nlm.nih.gov/pubmed/37501720 http://dx.doi.org/10.3389/fgene.2023.1079198 |
Ejemplares similares
-
Statistical Power Analysis for Designing Bulk, Single-Cell, and Spatial Transcriptomics Experiments: Review, Tutorial, and Perspectives
por: Jeon, Hyeongseon, et al.
Publicado: (2023) -
graph-GPA: A graphical model for prioritizing GWAS results and investigating pleiotropic architecture
por: Chung, Dongjun, et al.
Publicado: (2017) -
GPA: A Statistical Approach to Prioritizing GWAS Results by Integrating Pleiotropy and Annotation
por: Chung, Dongjun, et al.
Publicado: (2014) -
ShinyGPA: An interactive visualization toolkit for investigating pleiotropic architecture using GWAS datasets
por: Kortemeier, Emma, et al.
Publicado: (2018) -
Fully automated annotation of mitochondrial genomes using a cluster-based approach with de Bruijn graphs
por: Fiedler, Lisa, et al.
Publicado: (2023)