Predicting the difficulty of pure, strict, epistatic models: metrics for simulated model selection

BACKGROUND: Algorithms designed to detect complex genetic disease associations are initially evaluated using simulated datasets. Typical evaluations vary constraints that influence the correct detection of underlying models (i.e. number of loci, heritability, and minor allele frequency). Such studie...

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Detalles Bibliográficos
Autores principales: Urbanowicz, Ryan J, Kiralis, Jeff, Fisher, Jonathan M, Moore, Jason H
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Methodology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3549792/
https://www.ncbi.nlm.nih.gov/pubmed/23014095
http://dx.doi.org/10.1186/1756-0381-5-15

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3549792/
https://www.ncbi.nlm.nih.gov/pubmed/23014095
http://dx.doi.org/10.1186/1756-0381-5-15

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