Saccone Scott F, Saccone Nancy L, Swan Gary E, Madden Pamela A F, Goate Alison M, Rice John P, Bierut Laura J
Department of Psychiatry, Washington University School of Medicine, Saint Louis, Missouri 63110, USA.
Bioinformatics. 2008 Aug 15;24(16):1805-11. doi: 10.1093/bioinformatics/btn315. Epub 2008 Jun 19.
A challenging problem after a genome-wide association study (GWAS) is to balance the statistical evidence of genotype-phenotype correlation with a priori evidence of biological relevance.
We introduce a method for systematically prioritizing single nucleotide polymorphisms (SNPs) for further study after a GWAS. The method combines evidence across multiple domains including statistical evidence of genotype-phenotype correlation, known pathways in the pathologic development of disease, SNP/gene functional properties, comparative genomics, prior evidence of genetic linkage, and linkage disequilibrium. We apply this method to a GWAS of nicotine dependence, and use simulated data to test it on several commercial SNP microarrays.
A comprehensive database of biological prioritization scores for all known SNPs is available at http://zork.wustl.edu/gin. This can be used to prioritize nicotine dependence association studies through a straightforward mathematical formula-no special software is necessary.
Supplementary data are available at Bioinformatics online.
全基因组关联研究（GWAS）之后的一个具有挑战性的问题是，要在基因型与表型相关性的统计证据与生物学相关性的先验证据之间取得平衡。
我们引入了一种在GWAS之后对单核苷酸多态性（SNP）进行系统排序以供进一步研究的方法。该方法整合了多个领域的证据，包括基因型与表型相关性的统计证据、疾病病理发展中的已知途径、SNP/基因功能特性、比较基因组学、遗传连锁的先验证据以及连锁不平衡。我们将此方法应用于尼古丁依赖的GWAS，并使用模拟数据在几种商业SNP微阵列上对其进行测试。
所有已知SNP的生物学优先级评分综合数据库可在http://zork.wustl.edu/gin获取。可通过一个简单的数学公式用于对尼古丁依赖关联研究进行优先级排序，无需特殊软件。
补充数据可在《生物信息学》在线获取。
