Data from: Penalized Multi-Marker versus Single-Marker Regression methods for genome-wide association studies of quantitative traits

Hui Yi, Patrick Breheny, Netsanet Iman, Yongmei Liu, Ina Hoeschele, H. Yi, N. Imam, I. Hoeschele & P. Breheny
The data from genome-wide association studies (GWAS) in humans are still predominantly analyzed using single marker association methods. As an alternative to Single Marker Analysis (SMA), all or subsets of markers can be tested simultaneously. This approach requires a form of Penalized Regression (PR) as the number of SNPs is much larger than the sample size. Here we review PR methods in the context of GWAS, extend them to perform penalty parameter and SNP selection...
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