Abstract
The efforts of the Human Genome Project are beginning to provide important findings for human health. Technological advances in the laboratory, particularly in characterizing human genomic variation, have created new approaches for studying the human genome - genome-wide association studies (GWAS). However, current statistical and computational strategies are taking only partial advantage of this wealth of information. In the quest for susceptibility genes for complex diseases in GWAS data, several different analytic strategies are being pursued. In a recent report, Baranzini and colleagues used a pathway- and network-based analysis to explore potentially interesting single locus association signals in a GWAS of multiple sclerosis. This and other pathway-based approaches are likely to continue to emerge in the GWAS literature, as they provide a powerful strategy to detect important modest single-locus effects and gene-gene interaction effects.
Highlights
In the search for susceptibility genes for common complex diseases, we are faced with enormous challenges
Recent technological advances enable the genotyping of hundreds of thousands of human single-nucleotide polymorphisms (SNPs) on thousands of samples
The National Human Genome Research Institute (NHGRI) keeps an updated genome-wide association studies (GWAS) catalog on their website [7], which lists over 273 published GWAS so far
Summary
In the search for susceptibility genes for common complex diseases, we are faced with enormous challenges. Baranzini and colleagues used a pathway- and network-based analysis to explore potentially interesting single locus association signals in a GWAS of multiple sclerosis.
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