Document Detail

Detecting essential and removable interactions in genome-wide association studies.
MedLine Citation:
PMID:  21165165     Owner:  NLM     Status:  Publisher    
Detection of disease gene interaction effects among the enormous array of single nucleotide polymorphism (SNP) combinations represents the next frontier in genome-wide association (GWA) studies. Here we propose a novel strategy on the basis of the pattern and nature of the interaction, which can be classified as essential (EI) or removable (RI). We provide an analytical framework, including the qualitative conditions for screening EIs/RIs and a RI-to-EI likelihood ratio score to quantitatively measure the effect. In analyzing six GWA data sets, we find that the scores follow an exponential distribution, except in the upper 10(-8) tail region in which the scores become irregular and unpredictable. Our approach is conceptually simple, computationally efficient and detects interactions that can be visualized and unequivocally interpreted.
Chengqing Wu; Hong Zhang; Xiangtao Liu; Andrew Dewan; Robert Dubrow; Zhiliang Ying; Yaning Yang; Josephine Hoh
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Publication Detail:
Journal Detail:
Title:  Statistics and its interface     Volume:  2     ISSN:  1938-7997     ISO Abbreviation:  -     Publication Date:  2009 Jan 
Date Detail:
Created Date:  2010-12-23     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101471232     Medline TA:  Stat Interface     Country:  -    
Other Details:
Languages:  ENG     Pagination:  161-170     Citation Subset:  -    
Yale School of Public Health, New Haven, CT,
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Grant Support
R37 GM047845-18//NIGMS NIH HHS; K25 HG000060-06//NHGRI NIH HHS; R01 EY015771-04//NEI NIH HHS; R21 EY018127-02//NEI NIH HHS; R37 GM047845-18//NIGMS NIH HHS; S10 RR019895-01//NCRR NIH HHS

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