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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...
Autores principales: | Wang, Meida, Zhang, Shuanglin, Sha, Qiuying |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
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 |
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