Genome-wide association study heterogeneous cohort homogenization via subject weight knock-down

• Published in: PloS one Vol. 7; no. 10; p. e48653
• Main Authors: Valente, André X C N, Zischkau, Joseph, Shin, Joo Heon, Gao, Yuan, Sarkar, Abhijit
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 29.10.2012; Public Library of Science (PLoS)
• Subjects: Algorithms; Analysis; Biology; Cohort Studies; Computer Science; Computer Simulation; Contingency tables; Disease susceptibility; Gene Frequency; Genetic aspects; Genetic Predisposition to Disease - genetics; Genetics; Genome-wide association studies; Genome-Wide Association Study - methods; Genome-Wide Association Study - statistics & numerical data; Genomes; Genomics; Genotype; Homogenization; Humans; Laboratories; Logistic Models; Mathematics; Medical research; Medicine; Methods; Movement disorders; Neurodegenerative diseases; Parkinson Disease - genetics; Parkinson's disease; Phenotype; Polymorphism, Single Nucleotide; Population; Population (statistical); Population structure; Principal components analysis; Reproducibility of Results; Studies; Washington DC; United States > US; Maryland; Portugal; Baltimore Maryland
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0048653

Population structure can be a source of both false-positive and false-negative findings in a genome-wide association study. This article proposes an approach that helps to reduce the false-positives. It consists of homogenizing the diseased/healthy phenotype ratio across the cohort, by decreasing the statistical weight of selected individuals. After homogenization, the cohort is statistically handled as if originating from a single well-mixed population. The method was applied to homogenize a Parkinson's disease genome-wide association study cohort.