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Genome-Wide Association Studies
Cold Spring Harbor Protocols, 2009INTRODUCTIONThe goal of association studies is to discover genetic variation that differs in frequency between cases and controls or between individuals with different phenotypic values. Until a few years ago, the only method available for such studies was low-throughput analysis in which a single gene was selected and either genotyped for known ...
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Genome-Wide Association Studies
2018Genetic association studies have made a major contribution to our understanding of the genetics of complex disorders over the last 10 years through genome-wide association studies (GWAS). In this chapter, we review the key concepts that underlie the GWAS approach.
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Genome-Wide Association Studies of Cancer
Future Oncology, 2007Genome-wide association studies provide a new and powerful approach to investigate the effect of inherited genetic variation on the risk of human disease. These studies rely on high throughput DNA microarray technology to genotype hundreds of thousands of genetic variants across the human genome.
Eric, Jorgenson, John S, Witte
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[Genome-wide association studies].
Ugeskrift for laeger, 2008Within the last year, genome-wide association (GWA) studies have identified a large number of robust associations between genetic variants and common diseases. Two key premises underlie this burst of discovery. First, the HapMap project has provided a catalogue of human genetic variation.
Bjarke, Feenstra +2 more
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[Genome-wide association studies].
Deutsche medizinische Wochenschrift (1946), 2011Genome-wide association studies (GWAS) are aimed to identify genetic markers of complex human diseases and individual traits. In this context more than 150 gene loci have been found to be associated with about 60 different diseases and personal characteristics.
D, Grimm, H E, Blum, R, Thimme
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R for Genome-Wide Association Studies
2013In recent years R has become de facto statistical programming language of choice for statisticians and it is also arguably the most widely used generic environment for analysis of high-throughput genomic data. In this chapter we discuss some approaches to improve performance of R when working with large SNP datasets.
Gondro, Cedric +2 more
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Genome-Wide Association Study in Humans
2009Genome-wide association studies have opened a new era in the study of the genetic basis of common, multifactorial diseases and traits. Before the introduction of this approach only a handful of common genetic variants showed consistent association for any phenotype.
J Gustav, Smith +1 more
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Genome-wide association studies in atherothrombosis
European Journal of Internal Medicine, 2010Atherothrombotic diseases are complex diseases, arising from the interaction between several genetic and environmental factors. Until recently, the genetic basis of complex diseases in general, and of atherothrombosis in particular, were poorly characterized.
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Genome-wide association studies in pharmacogenomics
Nature Reviews Genetics, 2010Genome-wide association (GWA) studies for pharmacogenomics-related traits are increasingly being performed to identify loci that affect either drug response or susceptibility to adverse drug reactions. Until now, only the largest effects have been detected, partly because of the challenges of obtaining large numbers of cases for pharmacogenomic studies.
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