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Restricted maximum-likelihood method for learning latent variance components in gene expression data with known and unknown confounders
Random effects models are popular statistical models for detecting and correcting spurious sample correlations due to hidden confounders in genome-wide gene expression data. In applications where some confounding factors are known, estimating simultaneously the contribution of known and latent varia...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Oxford University Press
2021
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9210293/ https://www.ncbi.nlm.nih.gov/pubmed/34864982 http://dx.doi.org/10.1093/g3journal/jkab410 |