Flexible statistical methods for estimating and testing effects in genomic studies with multiple conditions

We introduce new statistical methods for analyzing genomic datasets that measure many effects in many conditions (e.g., gene expression changes under many treatments). These new methods improve on existing methods by allowing for arbitrary correlations in effect sizes among conditions. This flexible...

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Detalles Bibliográficos
Autores principales: Urbut, Sarah M., Wang, Gao, Carbonetto, Peter, Stephens, Matthew
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6309609/
https://www.ncbi.nlm.nih.gov/pubmed/30478440
http://dx.doi.org/10.1038/s41588-018-0268-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6309609/
https://www.ncbi.nlm.nih.gov/pubmed/30478440
http://dx.doi.org/10.1038/s41588-018-0268-8

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