Ranking causal variants and associated regions in genome-wide association studies by the support vector machine and random forest

Abstract

We study the number of causal variants and associated regions identified by top SNPs in rankings given by the popular 1 df chi-squared statistic, support vector machine (SVM) and the random forest (RF) on simulated and real data. If we apply the SVM and RF to the top 2r chi-square-ranked SNPs, where r is the number of SNPs with P-values within the… (More)
DOI: 10.1093/nar/gkr064

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Cite this paper

@inproceedings{Roshan2011RankingCV, title={Ranking causal variants and associated regions in genome-wide association studies by the support vector machine and random forest}, author={Usman Roshan and Satish Chikkagoudar and Zhi Wei and Kai Wang and Hakon Hakonarson}, booktitle={Nucleic acids research}, year={2011} }