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Open Access Highly Accessed Research article

An application of Random Forests to a genome-wide association dataset: Methodological considerations & new findings

Benjamin A Goldstein13*, Alan E Hubbard1, Adele Cutler2 and Lisa F Barcellos1*

Author Affiliations

1 Division of Biostatistics, School of Public Health, University of California, Berkeley, CA, USA

2 Department of Mathematics & Statistics, Utah State University, Logan UT, USA

3 Genetic Epidemiology and Genomics Laboratory, Division of Epidemiology, School of Public Health, University of California, Berkeley, CA, USA

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BMC Genetics 2010, 11:49  doi:10.1186/1471-2156-11-49

Published: 14 June 2010

Additional files

Additional file 1:

Comparison of RF results with original GWA screen in MS cases and controls. The top 16 SNPs identified by IMSGC [19] and corresponding rank for a tag SNPs derived from RF analysis. EVI5 and KANKI ranking the highest based on RF results, with rs10735781 having multiple tag SNPs. *The two SNPs in IL2RA serve as tag SNPs for one another.

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