Improving machine learning reproducibility in genetic association studies with proportional instance cross validation (PICV)

BACKGROUND: Machine learning methods and conventions are increasingly employed for the analysis of large, complex biomedical data sets, including genome-wide association studies (GWAS). Reproducibility of machine learning analyses of GWAS can be hampered by biological and statistical factors, partic...

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Detalles Bibliográficos
Autores principales: Piette, Elizabeth R., Moore, Jason H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Methodology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5907739/
https://www.ncbi.nlm.nih.gov/pubmed/29713384
http://dx.doi.org/10.1186/s13040-018-0167-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5907739/
https://www.ncbi.nlm.nih.gov/pubmed/29713384
http://dx.doi.org/10.1186/s13040-018-0167-7

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