Causal modeling in a multi-omic setting: insights from GAW20

BACKGROUND: Increasingly available multilayered omics data on large populations has opened exciting analytic opportunities and posed unique challenges to robust estimation of causal effects in the setting of complex disease phenotypes. The GAW20 Causal Modeling Working Group has applied complementar...

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Detalles Bibliográficos
Autores principales: Auerbach, Jonathan, Howey, Richard, Jiang, Lai, Justice, Anne, Li, Liming, Oualkacha, Karim, Sayols-Baixeras, Sergi, Aslibekyan, Stella W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Methodology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6157026/
https://www.ncbi.nlm.nih.gov/pubmed/30255779
http://dx.doi.org/10.1186/s12863-018-0645-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6157026/
https://www.ncbi.nlm.nih.gov/pubmed/30255779
http://dx.doi.org/10.1186/s12863-018-0645-4

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