Cargando…
Reliable heritability estimation using sparse regularization in ultrahigh dimensional genome-wide association studies
BACKGROUND: Data from genome-wide association studies (GWASs) have been used to estimate the heritability of human complex traits in recent years. Existing methods are based on the linear mixed model, with the assumption that the genetic effects are random variables, which is opposite to the fixed e...
Autores principales: | Li, Xin, Wu, Dongya, Cui, Yue, Liu, Bing, Walter, Henrik, Schumann, Gunter, Li, Chong, Jiang, Tianzi |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6492418/ https://www.ncbi.nlm.nih.gov/pubmed/31039742 http://dx.doi.org/10.1186/s12859-019-2792-7 |
Ejemplares similares
-
Allowing for mandatory covariates in boosting estimation of sparse high-dimensional survival models
por: Binder, Harald, et al.
Publicado: (2008) -
Correntropy induced loss based sparse robust graph regularized extreme learning machine for cancer classification
por: Ren, Liang-Rui, et al.
Publicado: (2020) -
Epigenetics, heritability and longitudinal analysis
por: Nustad, Haakon E., et al.
Publicado: (2018) -
Ultrahigh-dimensional variable selection method for whole-genome gene-gene interaction analysis
por: Ueki, Masao, et al.
Publicado: (2012) -
Obtaining insights from high-dimensional data: sparse principal covariates regression
por: Van Deun, Katrijn, et al.
Publicado: (2018)