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CORE GREML for estimating covariance between random effects in linear mixed models for complex trait analyses
As a key variance partitioning tool, linear mixed models (LMMs) using genome-based restricted maximum likelihood (GREML) allow both fixed and random effects. Classic LMMs assume independence between random effects, which can be violated, causing bias. Here we introduce a generalized GREML, named COR...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7442840/ https://www.ncbi.nlm.nih.gov/pubmed/32826890 http://dx.doi.org/10.1038/s41467-020-18085-5 |