Cargando…
Mixed-effects models for GAW18 longitudinal blood pressure data
In this paper, we propose two mixed-effects models for Genetic Analysis Workshop 18 (GAW18) longitudinal blood pressure data. The first method extends EMMA, an efficient mixed-model association-mapping algorithm. EMMA corrects for population structure and genetic relatedness using a kinship similari...
Autores principales: | Chung, Wonil, Zou, Fei |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4143717/ https://www.ncbi.nlm.nih.gov/pubmed/25519345 http://dx.doi.org/10.1186/1753-6561-8-S1-S87 |
Ejemplares similares
-
Admixture mapping analysis in the context of GWAS with GAW18 data
por: Chen, Mengjie, et al.
Publicado: (2014) -
Multilocus analysis of GAW15 NARAC chromosome 18 case-control data
por: Browning, Sharon R, et al.
Publicado: (2007) -
Application of Bayesian networks to GAW20 genetic and blood lipid data
por: Howey, Richard A. J., et al.
Publicado: (2018) -
Evaluating the concordance between sequencing, imputation and microarray genotype calls in the GAW18 data
por: Rogers, Ally, et al.
Publicado: (2014) -
Comparing the power of family-based association tests for sequence data with applications in the GAW18 simulated data
por: Huang, Jing, et al.
Publicado: (2014)