Genome-wide association data classification and SNPs selection using two-stage quality-based Random Forests

BACKGROUND: Single-nucleotide polymorphisms (SNPs) selection and identification are the most important tasks in Genome-wide association data analysis. The problem is difficult because genome-wide association data is very high dimensional and a large portion of SNPs in the data is irrelevant to the d...

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Detalles Bibliográficos
Autores principales: Nguyen, Thanh-Tung, Huang, Joshua Zhexue, Wu, Qingyao, Nguyen, Thuy Thi, Li, Mark Junjie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Proceedings
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4331719/
https://www.ncbi.nlm.nih.gov/pubmed/25708662
http://dx.doi.org/10.1186/1471-2164-16-S2-S5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4331719/
https://www.ncbi.nlm.nih.gov/pubmed/25708662
http://dx.doi.org/10.1186/1471-2164-16-S2-S5

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