An "almost exhaustive" search-based sequential permutation method for detecting epistasis in disease association studies

Genetic Epidemiology

Volumn 34, Issue 5, 2010, Pages 434-443

  Ma, Li ^a   Assimes, Themistocles L ^b   Asadi, Narges B ^c   Iribarren, Carlos ^d   Quertermous, Thomas ^b   Wong, Wing H ^a  

^a STANFORD UNIVERSITY   (United States)

^b STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

^c Stanford University   (United States)

^d DIVISION OF RESEARCH   (United States)

Author keywords

Case control study; Frequent pattern mining; Genetic interaction; Nonparametric test

Indexed keywords

ARTICLE; CARDIOVASCULAR DISEASE; CORONARY ARTERY DISEASE; DISEASE ASSOCIATION; GENE LOCUS; GENETIC EPISTASIS; RISK FACTOR;

ALGORITHMS; ALLELES; CASE-CONTROL STUDIES; COMPUTER SIMULATION; CORONARY DISEASE; EPISTASIS, GENETIC; GENETIC MARKERS; HUMANS; MODELS, GENETIC; MODELS, STATISTICAL; MOLECULAR EPIDEMIOLOGY; POLYMORPHISM, SINGLE NUCLEOTIDE; RISK;

EID: 77954198559     PISSN: 07410395     EISSN: 10982272     Source Type: Journal    
DOI: 10.1002/gepi.20496     Document Type: Article

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