A powerful statistical framework for generalization testing in GWAS, with application to the HCHS/SOL

Genetic Epidemiology

Volumn 41, Issue 3, 2017, Pages 251-258

  Sofer, Tamar ^a   Heller, Ruth ^b   Bogomolov, Marina ^c   Avery, Christy L ^d   Graff, Mariaelisa ^d   North, Kari E ^d   Reiner, Alex P ^e   Thornton, Timothy A ^a   Rice, Kenneth ^a   Benjamini, Yoav ^a   Laurie, Cathy C ^a   Kerr, Kathleen F ^a  

^a UNIVERSITY OF WASHINGTON   (United States)

^b TEL AVIV UNIVERSITY   (Israel)

^c TECHNION ISRAEL INSTITUTE OF TECHNOLOGY   (Israel)

^d The University of North Carolina at Chapel Hill   (United States)

^e Fred Hutchinson Cancer Research Center   (United States)

Author keywords

multiple testing; one sided P values; shared genetics

Indexed keywords

CAUCASIAN; CHOLESTEROL BLOOD LEVEL; FAMILY; FOLLOW UP; GENE MUTATION; GENETIC POLYMORPHISM; GENOME-WIDE ASSOCIATION STUDY; HISPANIC; HUMAN; PUBLIC HEALTH; SINGLE NUCLEOTIDE POLYMORPHISM; STATISTICAL MODEL; STATISTICAL SIGNIFICANCE; ALGORITHM; COMPUTER SIMULATION; GENE LINKAGE DISEQUILIBRIUM; GENETICS; GENOMICS; HUMAN GENOME; PHENOTYPE; PROCEDURES;

ALGORITHMS; COMPUTER SIMULATION; FOLLOW-UP STUDIES; GENOME, HUMAN; GENOME-WIDE ASSOCIATION STUDY; GENOMICS; HISPANIC AMERICANS; HUMANS; LINKAGE DISEQUILIBRIUM; MODELS, STATISTICAL; PHENOTYPE; POLYMORPHISM, SINGLE NUCLEOTIDE;

EID: 85010806721     PISSN: 07410395     EISSN: 10982272     Source Type: Journal    
DOI: 10.1002/gepi.22029     Document Type: Article

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