Laplacian Eigenfunctions Learn Population Structure

• Published in: PloS one Vol. 4; no. 12; p. e7928
• Main Authors: Zhang, Jun, Niyogi, Partha, McPeek, Mary Sara
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 01.12.2009; Public Library of Science (PLoS)
• Subjects: Analysis; Animals; Birds; Clustering; Computer Simulation; Databases, Genetic; Ecology/Global Change Ecology; Eigenvectors; Euclidean space; Evolutionary Biology/Evolutionary Ecology; Genetic diversity; Genetics; Genetics and Genomics/Population Genetics; Genome-wide association studies; Genomes; Genomics; Genotype & phenotype; Graph theory; Methods; Migration; Outliers (statistics); Passeriformes - genetics; Population Dynamics; Population genetics; Population structure; Principal Component Analysis; Principal components analysis; Rheumatoid arthritis; Studies; United States > US; Illinois; Chicago Illinois

Principal components analysis has been used for decades to summarize genetic variation across geographic regions and to infer population migration history. More recently, with the advent of genome-wide association studies of complex traits, it has become a commonly-used tool for detection and correc...