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BOOST: A fast approach to detecting gene-gene interactions in genome-wide case-control studies
TLDR
In this paper, a simple but powerful method, named "BOolean Operation based Screening and Testing" (BOOST), is introduced to discover unknown gene-gene interactions that underlie complex diseases.Abstract:
Gene-gene interactions have long been recognized to be fundamentally important to understand genetic causes of complex disease traits. At present, identifying gene-gene interactions from genome-wide case-control studies is computationally and methodologically challenging. In this paper, we introduce a simple but powerful method, named `BOolean Operation based Screening and Testing'(BOOST). To discover unknown gene-gene interactions that underlie complex diseases, BOOST allows examining all pairwise interactions in genome-wide case-control studies in a remarkably fast manner. We have carried out interaction analyses on seven data sets from the Wellcome Trust Case Control Consortium (WTCCC). Each analysis took less than 60 hours on a standard 3.0 GHz desktop with 4G memory running Windows XP system. The interaction patterns identified from the type 1 diabetes data set display significant difference from those identified from the rheumatoid arthritis data set, while both data sets share a very similar hit region in the WTCCC report. BOOST has also identified many undiscovered interactions between genes in the major histocompatibility complex (MHC) region in the type 1 diabetes data set. In the coming era of large-scale interaction mapping in genome-wide case-control studies, our method can serve as a computationally and statistically useful tool.read more
Citations
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Journal ArticleDOI
Second-generation PLINK: rising to the challenge of larger and richer datasets
Christopher C. Chang,Carson C. Chow,Laurent C. A. M. Tellier,Shashaank Vattikuti,Shaun Purcell,James J. Lee +5 more
TL;DR: PLINK as discussed by the authors is a C/C++ toolset for genome-wide association studies (GWAS) and research in population genetics, which has been widely used in the literature.
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Detecting epistasis in human complex traits
TL;DR: The purpose of this Review is to summarize recent directions in methodology for detecting epistasis and to discuss evidence of the role of epistasis in human complex trait variation.
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Travelling the world of gene–gene interactions
TL;DR: A perspective view on a selection of currently active analysis strategies and concerns in the context of epistasis detection, and to provide an eye to the future of gene-gene interaction analysis are provided.
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High-density genotyping of immune-related loci identifies new SLE risk variants in individuals with Asian ancestry
Celi Sun,Julio E. Molineros,Loren L. Looger,Xu-jie Zhou,Kwangwoo Kim,Yukinori Okada,Jianyang Ma,Yuan-yuan Qi,Xana Kim-Howard,Prasenjeet Motghare,Krishna Bhattarai,Adam Adler,So Young Bang,Hye Soon Lee,Tae-Hwan Kim,Young Mo Kang,Chang Hee Suh,Won Tae Chung,Yong Beom Park,Jung Yoon Choe,Seung Cheol Shim,Yuta Kochi,Akari Suzuki,Michiaki Kubo,Takayuki Sumida,Kazuhiko Yamamoto,Shin-Seok Lee,Young-Jin Kim,Bok Ghee Han,Mikhail G. Dozmorov,Kenneth M. Kaufman,Jonathan D. Wren,John B. Harley,Nan Shen,Nan Shen,Kek Heng Chua,Hong Zhang,Sang Cheol Bae,Swapan K. Nath +38 more
TL;DR: Ten new SLE susceptibility loci are identified and the new loci share functional and ontological characteristics with previously reported loci and are possible drug targets for SLE therapeutics.
Journal ArticleDOI
GBOOST: a GPU-based tool for detecting gene–gene interactions in genome–wide case control studies
TL;DR: GBOOST achieves a 40-fold speedup compared with BOOST and completes the analysis of Wellcome Trust Case Control Consortium Type 2 Diabetes genome data within 1.34 h on a desktop computer equipped with Nvidia GeForce GTX 285 display card.
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