期刊
AMERICAN JOURNAL OF HUMAN GENETICS
卷 81, 期 6, 页码 1278-1283出版社
CELL PRESS
DOI: 10.1086/522374
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资金
- NIMH NIH HHS [R01-MH604687] Funding Source: Medline
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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