Cargando…
Hierarchical Generalized Linear Models for Multiple Groups of Rare and Common Variants: Jointly Estimating Group and Individual-Variant Effects
Complex diseases and traits are likely influenced by many common and rare genetic variants and environmental factors. Detecting disease susceptibility variants is a challenging task, especially when their frequencies are low and/or their effects are small or moderate. We propose here a comprehensive...
Autores principales: | Yi, Nengjun, Liu, Nianjun, Zhi, Degui, Li, Jun |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2011
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3228815/ https://www.ncbi.nlm.nih.gov/pubmed/22144906 http://dx.doi.org/10.1371/journal.pgen.1002382 |
Ejemplares similares
-
Evaluation of pooled association tests for rare variant identification
por: Lin, Wan-Yu, et al.
Publicado: (2011) -
Identification of Grouped Rare and Common Variants via Penalized Logistic Regression
por: Ayers, Kristin L, et al.
Publicado: (2013) -
Evaluation of association tests for rare variants using simulated data sets in the Genetic Analysis Workshop 17 data
por: Chen, Wenan, et al.
Publicado: (2011) -
Representations of general linear groups
por: James, G D
Publicado: (1984) -
Detection of rare functional variants using group ISIS
por: Niu, Yue S, et al.
Publicado: (2011)