An Efficient Gatekeeper Algorithm for Detecting GxE | Zendy

Jimmy T. Efird | Zendy

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An Efficient Gatekeeper Algorithm for Detecting GxE

Author(s) -

Jimmy T. Efird

Publication year - 2010

Publication title -

cancer informatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.606

H-Index - 31

ISSN - 1176-9351

DOI - 10.4137/cin.s4731

Subject(s) - false positive paradox , single nucleotide polymorphism , selection (genetic algorithm) , intervention (counseling) , computer science , heuristic , medicine , environmental health , machine learning , genetics , biology , artificial intelligence , gene , genotype , psychiatry

The risk for many complex diseases is believed to be a result of the interactive effects of genetic and environmental factors. Developing efficient techniques to identify gene-environment interactions (GxE) is important for unraveling the etiologic basis of many modern day diseases including cancer. The problem of false positives and false negatives continues to pose significant roadblocks to detecting GxE and informing targeted public health screening and intervention. A heuristic gatekeeper method is presented to guide the selection of single nucleotide polymorphisms (SNPs) in the design phase of a GxE study.

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