Liu, QingzhongSung, Andrew H.Chen, ZhongxueYang, Mary QuHuang, XudongYang, Jack2022-01-252022-01-252007-07-25Liu Q, Yang J, Chen Z, Yang M, Sung AH, Huang X (2008). Supervised-learning based TagSNPs for genome-wide disease classification, BMC Genomics 9 (Suppl 1): S6. doi:10.1186/1471-2164-9-S1-S6https://hdl.handle.net/20.500.11875/3263The article was originally published by BMC Genomics. doi:10.1186/1471-2164-9-S1-S6Comprehensive evaluation of common genetic variations through association of single nucleotide polymorphisms (SNPs) with complex human diseases on the genome-wide scale is an active area in human genome research. One of the fundamental questions in a SNP-disease association study is to find an optimal subset of SNPs with predicting power for disease status. To find that subset while reducing study burden in terms of time and costs, one can potentially reconcile information redundancy from associations between SNP markersen-USassociation of single nucleotide polymorphisms (SNPs)predicting poweractive areaArticle