A LASSO penalized regression approach for genome-wide association analyses using related individuals: application to the Genetic Analysis Workshop 19 simulated data

We propose a novel LASSO (least absolute shrinkage and selection operator) penalized regression method used to analyze samples consisting of (potentially) related individuals. Developed in the context of linear mixed models, our method models the relatedness of individuals in the sample through a ra...

Descripción completa

Detalles Bibliográficos
Autores principales: Papachristou, Charalampos, Ober, Carole, Abney, Mark
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Proceedings
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5133525/
https://www.ncbi.nlm.nih.gov/pubmed/27980640
http://dx.doi.org/10.1186/s12919-016-0034-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5133525/
https://www.ncbi.nlm.nih.gov/pubmed/27980640
http://dx.doi.org/10.1186/s12919-016-0034-9

Ejemplares similares