Cargando…
Joint Bayesian inference of risk variants and tissue-specific epigenomic enrichments across multiple complex human diseases
Genome wide association studies (GWAS) provide a powerful approach for uncovering disease-associated variants in human, but fine-mapping the causal variants remains a challenge. This is partly remedied by prioritization of disease-associated variants that overlap GWAS-enriched epigenomic annotations...
Autores principales: | Li, Yue, Kellis, Manolis |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5062982/ https://www.ncbi.nlm.nih.gov/pubmed/27407109 http://dx.doi.org/10.1093/nar/gkw627 |
Ejemplares similares
-
ChIP-BIT: Bayesian inference of target genes using a novel joint probabilistic model of ChIP-seq profiles
por: Chen, Xi, et al.
Publicado: (2016) -
Bayesian multiple-instance motif discovery with BAMBI: inference of recombinase and transcription factor binding sites
por: Jajamovich, Guido H., et al.
Publicado: (2011) -
Inferring and modeling inheritance of differentially methylated changes across multiple generations
por: Belleau, Pascal, et al.
Publicado: (2018) -
Bayesian inference of ancestral dates on bacterial phylogenetic trees
por: Didelot, Xavier, et al.
Publicado: (2018) -
Large-scale epigenome imputation improves data quality and disease variant enrichment
por: Ernst, Jason, et al.
Publicado: (2015)