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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| Principais autores: | , , |
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| Format: | Artigo |
| Sprog: | Inglês |
| Udgivet: |
Public Library of Science (PLoS)
2022-01-01
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| Serier: | PLoS ONE |
| Online adgang: | https://doi.org/10.1371/journal.pone.0260911 |
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