Tiffin Nicki, Adie Euan, Turner Frances, Brunner Han G, van Driel Marc A, Oti Martin, Lopez-Bigas Nuria, Ouzounis Christos, Perez-Iratxeta Carolina, Andrade-Navarro Miguel A, Adeyemo Adebowale, Patti Mary Elizabeth, Semple Colin A M, Hide Winston
South African National Bioinformatics Institute, University of the Western Cape, Bellville, 7535, South Africa.
Nucleic Acids Res. 2006 Jun 6;34(10):3067-81. doi: 10.1093/nar/gkl381. Print 2006.
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.
用于识别疾病基因的全基因组实验方法，如连锁分析和关联研究，产生了越来越多的候选基因集，而对这些基因集进行全面的实证分析是不切实际的。计算方法利用来自各种来源的数据，从这些基因集中识别出最有可能的候选疾病基因。在这里，我们回顾了七种独立的计算疾病基因优先级排序方法，然后将它们协同应用于对9556个2型糖尿病（T2D）和相关性状肥胖症的定位候选基因的分析。我们生成并分析了一份包含9个T2D主要候选基因和5个肥胖症主要候选基因的列表。两个基因，LPL和BCKDHA，在这两组中是共同的。我们还给出了一组T2D的次要候选基因（94个基因）和肥胖症的次要候选基因（116个基因），两种疾病共有58个基因。
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