SNPinfo: integrating GWAS and candidate gene information into functional SNP selection for genetic association studies.

SNPinfo: integrating GWAS and candidate gene information into functional SNP selection for genetic association studies.
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SNPINFO:将GWA和候选基因信息整合到遗传关联研究的功能SNP中。

DOI:
10.1093/nar/gkp290
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发表时间:
2009-07
影响因子:
14.9
通讯作者:
Taylor JA
Taylor JA
中科院分区:
生物学2区
文献类型:
--
作者:
Xu Z;Taylor JA

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我们开发了一套基于网络的 SNP 选择工具(可在 http://www.niehs.nih.gov/snpinfo 免费获得),研究人员可以在其中指定基因或连锁区域,并根据 GWAS 结果、连锁不平衡 (LD) 以及编码和非编码 SNP 的预测功能特征来选择 SNP。该算法使用 GWAS SNP P 值数据,并通过 GWAS SNP 查找高 LD 中的所有 SNP,因此选择是从比 GWAS 本身大得多的 SNP 集合中进行的。该程序还可以识别和选择不具有任何 GWAS SNP 的高 LD 的 SNP 的标签 SNP。我们结合了蛋白质结构、基因调控、剪接和 miRNA 结合的功能预测,并考虑 SNP 的替代等位基因是否可能对功能产生不同的影响。用户可以为不同功能类别的 SNP 分配权重,以进一步定制 SNP 选择。该计划考虑了不同人群的 LD 结构,以便一个种族群体的 GWAS 研究可用于为一个或多个其他种族群体选择 SNP。最后,我们提供了一个使用前列腺癌的示例,并证明该算法可以选择一小部分 SNP,其中包括许多最近验证的前列腺癌 SNP。
We have developed a set of web-based SNP selection tools (freely available at http://www.niehs.nih.gov/snpinfo) where investigators can specify genes or linkage regions and select SNPs based on GWAS results, linkage disequilibrium (LD), and predicted functional characteristics of both coding and non-coding SNPs. The algorithm uses GWAS SNP P-value data and finds all SNPs in high LD with GWAS SNPs, so that selection is from a much larger set of SNPs than the GWAS itself. The program can also identify and choose tag SNPs for SNPs not in high LD with any GWAS SNP. We incorporate functional predictions of protein structure, gene regulation, splicing and miRNA binding, and consider whether the alternative alleles of a SNP are likely to have differential effects on function. Users can assign weights for different functional categories of SNPs to further tailor SNP selection. The program accounts for LD structure of different populations so that a GWAS study from one ethnic group can be used to choose SNPs for one or more other ethnic groups. Finally, we provide an example using prostate cancer and demonstrate that this algorithm can select a small panel of SNPs that include many of the recently validated prostate cancer SNPs.
DOI: 10.1371/journal.pbio.0020268
发表时间: 2004-09
期刊: PLoS biology
影响因子: 9.8
作者:
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通讯作者: Sharp PA
DOI: 10.1093/nar/gkg616
发表时间: 2003-07-01
影响因子: 14.9
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DOI: 10.1038/ng1669
发表时间: 2005-11-01
期刊: NATURE GENETICS
影响因子: 30.8
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期刊: CELL
影响因子: 64.5
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