Linking disease associations with regulatory information in the human genome.

Linking disease associations with regulatory information in the human genome.
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DOI:
10.1101/gr.136127.111
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发表时间:
2012-09
期刊:
影响因子:
7
通讯作者:
Snyder M
Snyder M
中科院分区:
生物学1区
文献类型:
--
作者:
Schaub MA;Boyle AP;Kundaje A;Batzoglou S;Snyder M

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全基因组关联研究已经成功地鉴定了与大量表型相关的单核苷酸多态性(SNP)。然而,相关的SNP可能是更大的连锁不平衡区域的一部分。这使得精确鉴定与表型具有生物学联系的SNP变得困难。我们系统地研究了多种类型的ENCODE数据与疾病相关SNP的相关性,并表明在目前确定的相关性中,功能性SNP有显著的富集。当整合多个功能信息来源时,以及当使用最高置信度的疾病相关SNP时,这种富集是最强的。我们提出了一种方法,集成了多种类型的功能数据产生的ENCODE联盟,以帮助确定“功能SNPs”,可能与疾病表型。我们的方法生成推定的功能注释高达80%的所有以前报道的协会。我们发现,对于大多数协会,最有力的实验证据支持的功能SNP是一个SNP的连锁不平衡与报告的协会,而不是报告的SNP本身。我们的研究结果表明,ENCODE联盟生成的实验数据集可以成功地用于提出与疾病和其他表型相关的变异的功能假设。
Genome-wide association studies have been successful in identifying single nucleotide polymorphisms (SNPs) associated with a large number of phenotypes. However, an associated SNP is likely part of a larger region of linkage disequilibrium. This makes it difficult to precisely identify the SNPs that have a biological link with the phenotype. We have systematically investigated the association of multiple types of ENCODE data with disease-associated SNPs and show that there is significant enrichment for functional SNPs among the currently identified associations. This enrichment is strongest when integrating multiple sources of functional information and when highest confidence disease-associated SNPs are used. We propose an approach that integrates multiple types of functional data generated by the ENCODE Consortium to help identify “functional SNPs” that may be associated with the disease phenotype. Our approach generates putative functional annotations for up to 80% of all previously reported associations. We show that for most associations, the functional SNP most strongly supported by experimental evidence is a SNP in linkage disequilibrium with the reported association rather than the reported SNP itself. Our results show that the experimental data sets generated by the ENCODE Consortium can be successfully used to suggest functional hypotheses for variants associated with diseases and other phenotypes.
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影响因子: 7
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