Update on the State of the Science for Analytical Methods for Gene-Environment Interactions

American Journal of Epidemiology

Volumn 186, Issue 7, 2017, Pages 762-770

  Gauderman, W James ^a   Mukherjee, Bhramar ^b   Aschard, Hugues ^c,d   Hsu, Li ^e   Lewinger, Juan Pablo ^a   Patel, Chirag J ^f   Witte, John S ^g   Amos, Christopher ^h   Tai, Caroline G ^g   Conti, David ^a   Torgerson, Dara G ^g   Lee, Seunggeun ^b   Chatterjee, Nilanjan ^i,j  

^a UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

^b UNIVERSITY OF MICHIGAN SCHOOL OF PUBLIC HEALTH   (United States)

^c HARVARD SCHOOL OF PUBLIC HEALTH   (United States)

^d INSTITUT PASTEUR   (France)

^e USA   (United States)

^f HARVARD MEDICAL SCHOOL   (United States)

^g UNIVERSITY OF CALIFORNIA   (United States)

^h DARTMOUTH COLLEGE   (United States)

ⁱ JOHNS HOPKINS BLOOMBERG SCHOOL OF PUBLIC HEALTH   (United States)

^j JOHNS HOPKINS UNIVERSITY SCHOOL OF MEDICINE   (United States)

more..

Author keywords

Exposure; Gene environment interaction; GWAS; Power; Software; Statistical models

Indexed keywords

ANALYTICAL METHOD; COMPLEXITY; ENVIRONMENTAL FACTOR; ETIOLOGY; GENOME; GENOTYPE-ENVIRONMENT INTERACTION; QUANTITATIVE ANALYSIS; SOFTWARE; STATISTICAL ANALYSIS;

ANALYTIC METHOD; GENOME-WIDE ASSOCIATION STUDY; GENOTYPE ENVIRONMENT INTERACTION; QUANTITATIVE TRAIT; SOFTWARE; BAYES THEOREM; BIOLOGICAL MODEL; DISEASE; DNA SEQUENCE; GENETIC PREDISPOSITION; GENETICS; HUMAN; PROCEDURES; STATISTICAL MODEL;

BAYES THEOREM; DISEASE; GENE-ENVIRONMENT INTERACTION; GENETIC PREDISPOSITION TO DISEASE; GENOME-WIDE ASSOCIATION STUDY; HUMANS; LOGISTIC MODELS; MODELS, GENETIC; MODELS, STATISTICAL; SEQUENCE ANALYSIS, DNA; SOFTWARE;

EID: 85030653459     PISSN: 00029262     EISSN: 14766256     Source Type: Journal    
DOI: 10.1093/aje/kwx228     Document Type: Conference Paper

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