A correction for sample overlap in genome-wide association studies in a polygenic pleiotropy-informed framework

• Published in: BMC genomics Vol. 19; no. 1; pp. 494 - 15
• Main Authors: LeBlanc, Marissa, Zuber, Verena, Thompson, Wesley K., Andreassen, Ole A., Frigessi, Arnoldo, Andreassen, Bettina Kulle
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 25.06.2018; BioMed Central; BMC
• Subjects: Blood pressure; Cancer; Cardiovascular disease; Case-Control Studies; Computer Simulation; Consortia; Covariate-modulated false discovery rate; Cross-phenotype association; Data integration; Genetic aspects; Genetics; Genome-wide association studies; Genome-Wide Association Study - methods; Genomes; Genomics; Genotype; Humans; Lipids; Meta-analysis; Meta-analysis with shared subjects; Methodology; Phenotype; Pleiotropy; Polygenic inheritance; Polymorphism, Single Nucleotide - genetics; Schizophrenia; Statistical analysis; Statistical methods; Statistical tests; Statistics; Studies; Norway; Meta-analysis with shared subjects; Data integration; Cross-phenotype association; Covariate-modulated false discovery rate

There is considerable evidence that many complex traits have a partially shared genetic basis, termed pleiotropy. It is therefore useful to consider integrating genome-wide association study (GWAS) data across several traits, usually at the summary statistic level. A major practical challenge arises...