Candidate single nucleotide polymorphism selection using publicly available tools: A guide for epidemiologists
Candidate single nucleotide polymorphism selection using publicly available tools: A guide for epidemiologists
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DOI：
10.1093/aje/kwj269
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发表时间：
2006-10-15
影响因子：
5
通讯作者：
Sigurdson, Alice J.
中科院分区：
文献类型：
--
作者：
Bhatti, Parveen;Church, Deanna M.;Sigurdson, Alice J.
单核苷酸多态性 (SNP) 是人类遗传变异最常见的形式，人类基因组中存在数百万个。由于在关联研究中只有 1% 的个体可能会产生超过适度的个体效应，因此为复杂疾病分析选择预测候选变异是一项艰巨的任务。 SNP 发现的技术进步和不断变化的基因组注释带来了大量的信息资源，这些资源很难跨学科掌握。需要一个简化的指南。尽管评估非同义编码 SNP 的方法是已知的，但可以利用其他几种公开可用的计算工具来评估非编码区域中的多态性变异。例如，作者应用多种方法来选择 DNA 双链断裂修复基因中的 SNP。他们选择评估一组预先存在的 57 个经过验证的检测中出现的 SNP，并证明 DNA 依赖性蛋白激酶催化亚基中 83 个潜在 SNP 的新检测开发的合理性。在 140 个 SNP 中，作者消除了 119 个预测较低或中性的变异。他们使用的现有计算方法和他们开发的半定量相对排序策略可以适应先验 SNP 选择或对全基因组扫描或与疾病相关的单倍型块内识别的变异的事后评估。作者展示了一些现有生物信息学工具在大型流行病学研究和遗传分析中的“现实世界”应用。他们还审查了提供相关信息的替代方法。
Single nucleotide polymorphisms (SNPs) are the most common form of human genetic variation, with millions present in the human genome. Because only 1% might be expected to confer more than modest individual effects in association studies, the selection of predictive candidate variants for complex disease analyses is formidable. Technologic advances in SNP discovery and the ever-changing annotation of the genome have led to massive informational resources that can be difficult to master across disciplines. A simplified guide is needed. Although methods for evaluating nonsynonymous coding SNPs are known, several other publicly available computational tools can be utilized to assess polymorphic variants in noncoding regions. As an example, the authors applied multiple methods to select SNPs in DNA double-strand break repair genes. They chose to evaluate SNPs that occurred among a preexisting set of 57 validated assays and to justify new assay development for 83 potential SNPs in the DNA-dependent protein kinase catalytic subunit. Of the 140 SNPs, the authors eliminated 119 variants with low or neutral predictions. The existing computational methods they used and the semiquantitative relative ranking strategy they developed can be adapted to a priori SNP selection or post hoc evaluation of variants identified in whole genome scans or within haplotype blocks associated with disease. The authors show a "real world" application of some existing bioinformatics tools for use in large epidemiologic studies and genetic analyses. They also reviewed alternative approaches that provide related information.