A comparison of methods for interpreting random forest models of genetic association in the presence of non-additive interactions

BACKGROUND: Non-additive interactions among genes are frequently associated with a number of phenotypes, including known complex diseases such as Alzheimer’s, diabetes, and cardiovascular disease. Detecting interactions requires careful selection of analytical methods, and some machine learning algo...

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Detalles Bibliográficos
Autores principales: Orlenko, Alena, Moore, Jason H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7847145/
https://www.ncbi.nlm.nih.gov/pubmed/33514397
http://dx.doi.org/10.1186/s13040-021-00243-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7847145/
https://www.ncbi.nlm.nih.gov/pubmed/33514397
http://dx.doi.org/10.1186/s13040-021-00243-0

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