Open AccessA Principal Components-Based Clustering Method to Identify Variants Associated with Complex Traits
Author(s) -
Maureen M. Black,
Richard M. Watanabe
Publication year - 2011
Publication title -
human heredity
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.423
H-Index - 62
eISSN - 1423-0062
pISSN - 0001-5652
DOI - 10.1159/000323567
Subject(s) - linkage disequilibrium , principal component analysis , snp , cluster analysis , biology , genetic association , computational biology , multivariate statistics , genetics , genome wide association study , tag snp , genotype , statistics , computer science , single nucleotide polymorphism , artificial intelligence , gene , mathematics
Multivariate methods ranging from joint SNP to principal components analysis (PCA) have been developed for testing multiple markers in a region for association with disease and disease-related traits. However, these methods suffer from low power and/or the inability to identify the subset of markers contributing to evidence for association under various scenarios.