Cargando…
Leveraging Hierarchical Population Structure in Discrete Association Studies
Population structure can confound the identification of correlations in biological data. Such confounding has been recognized in multiple biological disciplines, resulting in a disparate collection of proposed solutions. We examine several methods that correct for confounding on discrete data with h...
Autores principales: | Carlson, Jonathan, Kadie, Carl, Mallal, Simon, Heckerman, David |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2007
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1899226/ https://www.ncbi.nlm.nih.gov/pubmed/17611623 http://dx.doi.org/10.1371/journal.pone.0000591 |
Ejemplares similares
-
Conditional Random Fields for Fast, Large-Scale Genome-Wide Association Studies
por: Huang, Jim C., et al.
Publicado: (2011) -
A Statistical Framework for Modeling HLA-Dependent T Cell Response Data
por: Listgarten, Jennifer, et al.
Publicado: (2007) -
Further Improvements to Linear Mixed Models for Genome-Wide Association
Studies
por: Widmer, Christian, et al.
Publicado: (2014) -
Greater power and computational efficiency for kernel-based association testing of sets of genetic variants
por: Lippert, Christoph, et al.
Publicado: (2014) -
An Exhaustive Epistatic SNP Association Analysis on Expanded Wellcome Trust Data
por: Lippert, Christoph, et al.
Publicado: (2013)