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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...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2012
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| Materias: | |
| 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 |