A computationally efficient clustering linear combination approach to jointly analyze multiple phenotypes for GWAS

There has been an increasing interest in joint analysis of multiple phenotypes in genome-wide association studies (GWAS) because jointly analyzing multiple phenotypes may increase statistical power to detect genetic variants associated with complex diseases or traits. Recently, many statistical meth...

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Detalles Bibliográficos
Autores principales: Wang, Meida, Zhang, Shuanglin, Sha, Qiuying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9049312/
https://www.ncbi.nlm.nih.gov/pubmed/35482827
http://dx.doi.org/10.1371/journal.pone.0260911

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9049312/
https://www.ncbi.nlm.nih.gov/pubmed/35482827
http://dx.doi.org/10.1371/journal.pone.0260911

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