BMC Syst Biol 2012 17;6 Suppl 3:S15. Epub 2012 Dec 17.
Center for Proteomics and Bioinformatics, Case Western Reserve University, Cleveland, OH, USA.
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BMC Bioinformatics 2009 Sep 17;10:294. Epub 2009 Sep 17.
Department of Electrical Engineering, Faculty of Engineering, King Mongkut's University of Technology North Bangkok, Bangkok, Thailand.
Background: Purely epistatic multi-locus interactions cannot generally be detected via single-locus analysis in case-control studies of complex diseases. Recently, many two-locus and multi-locus analysis techniques have been shown to be promising for the epistasis detection. However, exhaustive multi-locus analysis requires prohibitively large computational efforts when problems involve large-scale or genome-wide data. Read More
Am J Hum Genet 2010 Apr 25;86(4):581-91. Epub 2010 Mar 25.
Rosetta Inpharmatics, LLC, and Merck & Co., Inc., 401 Terry Avenue North, Seattle, WA 98109, USA.
Genome-wide association studies (GWAS) have achieved great success identifying common genetic variants associated with common human diseases. However, to date, the massive amounts of data generated from GWAS have not been maximally leveraged and integrated with other types of data to identify associations beyond those associations that meet the stringent genome-wide significance threshold. Here, we present a novel approach that leverages information from genetics of gene expression studies to identify biological pathways enriched for expression-associated genetic loci associated with disease in publicly available GWAS results. Read More
PLoS Genet 2010 May 6;6(5):e1000932. Epub 2010 May 6.
Department of Genetics, Rosetta Inpharmatics, Seattle, Washington, United States of America.
Genome-wide association studies (GWAS) have demonstrated the ability to identify the strongest causal common variants in complex human diseases. However, to date, the massive data generated from GWAS have not been maximally explored to identify true associations that fail to meet the stringent level of association required to achieve genome-wide significance. Genetics of gene expression (GGE) studies have shown promise towards identifying DNA variations associated with disease and providing a path to functionally characterize findings from GWAS. Read More
BMC Genomics 2013 28;14 Suppl 3:S10. Epub 2013 May 28.
National ICT Australia Victorian Research Lab, The University of Melbourne, Parkville, Victoria, Australia.
Background: It has been hypothesized that multivariate analysis and systematic detection of epistatic interactions between explanatory genotyping variables may help resolve the problem of "missing heritability" currently observed in genome-wide association studies (GWAS). However, even the simplest bivariate analysis is still held back by significant statistical and computational challenges that are often addressed by reducing the set of analysed markers. Theoretically, it has been shown that combinations of loci may exist that show weak or no effects individually, but show significant (even complete) explanatory power over phenotype when combined. Read More