Pathway-based approaches for analysis of genomewide association studies.
paper
Cited
Public
Unavailable
- Authors
- Wang, Kai; Li, Mingyao; Bucan, Maja
- Year
- 2007
- Journal
- American journal of human genetics
- PMID
- 17966091
- DOI
- 10.1086/522374
- PMCID
- PMC2276352
Published genomewide association (GWA) studies typically analyze and report single-nucleotide polymorphisms (SNPs) and their neighboring genes with the strongest evidence of association (the "most-significant SNPs/genes" approach), while paying little attention to the rest. Borrowing ideas from microarray data analysis, we demonstrate that pathway-based approaches, which jointly consider multiple contributing factors in the same pathway, might complement the most-significant SNPs/genes approach and provide additional insights into interpretation of GWA data on complex diseases.
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