期刊
NUCLEIC ACIDS RESEARCH
卷 34, 期 10, 页码 3067-3081出版社
OXFORD UNIV PRESS
DOI: 10.1093/nar/gkl381
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资金
- NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES [R01DK062948, R01DK060837] Funding Source: NIH RePORTER
- NIDDK NIH HHS [R01 DK060837, DK060837, R01 DK062948, DK062948] Funding Source: Medline
Genome-wide experimental methods to identify disease genes, such as linkage analysis and association studies, generate increasingly large candidate gene sets for which comprehensive empirical analysis is impractical. Computational methods employ data from a variety of sources to identify the most likely candidate disease genes from these gene sets. Here, we review seven independent computational disease gene prioritization methods, and then apply them in concert to the analysis of 9556 positional candidate genes for type 2 diabetes (T2D) and the related trait obesity. We generate and analyse a list of nine primary candidate genes for T2D genes and five for obesity. Two genes, LPL and BCKDHA, are common to these two sets. We also present a set of secondary candidates for T2D (94 genes) and for obesity (116 genes) with 58 genes in common to both diseases.
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