PolyDoms: a whole genome database for the identification of non-synonymous coding SNPs with the potential to impact disease.
PolyDoms: a whole genome database for the identification of non-synonymous coding SNPs with the potential to impact disease.
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DOI：
10.1093/nar/gkl826
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发表时间：
2007-01
影响因子：
14.9
通讯作者：
Aronow BJ
中科院分区：
文献类型：
--
作者：
Jegga AG;Gowrisankar S;Chen J;Aronow BJ
随着人类遗传多态性知识的增长，识别那些可能影响个体健康或疾病风险的多态性的机会和挑战也随之增加。一个关键的需求是组织大规模的多态性分析，并优先考虑候选非同义编码 SNP (nsSNP)，这些 SNP 应该在实验和流行病学研究中进行测试，以确定它们对蛋白质功能的特定背景影响。此外，随着高分辨率临床遗传学测试的出现，必须在所有可用的蛋白质特征知识（包括其他已知的突变和多态性）的背景下分析新的多态性。为了解决这个问题，我们开发了 PolyDoms () 作为数据库，以集成应用于整个 Entrez dbSNP 数据集的多个算法程序和功能标准的结果。除了预测所有 nsSNP 的结构和功能影响外，过滤功能还可以基于组识别与特定疾病、解剖学、哺乳动物表型、基因本体、通路或蛋白质域相关的多个基因中潜在有害的 nsSNP。因此，PolyDoms 提供了一种方法来导出候选 SNP 列表，以便在实验或流行病学研究中评估对蛋白质功能和疾病风险关联的影响。 PolyDoms 将继续进行改进以提高其实用性。
As knowledge of human genetic polymorphisms grows, so does the opportunity and challenge of identifying those polymorphisms that may impact the health or disease risk of an individual person. A critical need is to organize large-scale polymorphism analyses and to prioritize candidate non-synonymous coding SNPs (nsSNPs) that should be tested in experimental and epidemiological studies to establish their context-specific impacts on protein function. In addition, with emerging high-resolution clinical genetics testing, new polymorphisms must be analyzed in the context of all available protein feature knowledge including other known mutations and polymorphisms. To approach this, we developed PolyDoms () as a database to integrate the results of multiple algorithmic procedures and functional criteria applied to the entire Entrez dbSNP dataset. In addition to predicting structural and functional impacts of all nsSNPs, filtering functions enable group-based identification of potentially harmful nsSNPs among multiple genes associated with specific diseases, anatomies, mammalian phenotypes, gene ontologies, pathways or protein domains. PolyDoms, thus, provides a means to derive a list of candidate SNPs to be evaluated in experimental or epidemiological studies for impact on protein functions and disease risk associations. PolyDoms will continue to be curated to improve its usefulness.
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