Cargando…
An application of Random Forests to a genome-wide association dataset: Methodological considerations & new findings
BACKGROUND: As computational power improves, the application of more advanced machine learning techniques to the analysis of large genome-wide association (GWA) datasets becomes possible. While most traditional statistical methods can only elucidate main effects of genetic variants on risk for disea...
| Autores principales: | , , , |
|---|---|
| Formato: | Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2010
|
| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2896336/ https://www.ncbi.nlm.nih.gov/pubmed/20546594 http://dx.doi.org/10.1186/1471-2156-11-49 |