is-rSNP: a novel technique for in silico regulatory SNP detection
is-rSNP: a novel technique for in silico regulatory SNP detection
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DOI：
10.1093/bioinformatics/btq378
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发表时间：
2010-09-01
期刊：
影响因子：
5.8
通讯作者：
Kowalczyk, Adam
中科院分区：
文献类型：
--
作者：
Macintyre, Geoff;Bailey, James;Kowalczyk, Adam
动机：确定全基因组关联研究（GWAS）确定的非编码疾病相关单核苷酸多态性（SNP）的功能影响具有挑战性。这些SNPs中的许多可能是调节性SNPs（rSNPs）：影响转录因子（TF）与DNA结合能力的变异。然而，用于鉴定rSNP的实验程序是昂贵且劳动密集的。因此，需要计算机模拟方法进行rSNP预测。通过用TF位置权重矩阵（PWM）对两个等位基因进行评分，可以确定哪些SNP可能是rSNP。然而，以这种方式的预测是嘈杂的，没有方法存在，确定的核苷酸变异的统计学意义上的PWM score.Results：我们已经设计了一种算法，在硅RSNP检测称为是-RSNP。我们采用新的卷积方法来确定PWM分数和等位基因分数之间的比率的完整分布，促进rSNP效应的统计学显著性分配。我们已经在41个实验验证的rSNP上测试了我们的方法，在28个案例中正确预测了TF的破坏。我们还分析了146个与疾病相关的SNP，这些SNP没有已知的功能影响，试图识别候选rSNP。在11个显著预测破坏的TF中，9个先前在文献中有与疾病相关的证据。这些结果表明，is-rSNP是适合于高通量筛选SNPs的潜在的调节功能。这是解释全球WAS的一个有用和重要的工具。
Motivation: Determining the functional impact of non-coding disease-associated single nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWAS) is challenging. Many of these SNPs are likely to be regulatory SNPs (rSNPs): variations which affect the ability of a transcription factor (TF) to bind to DNA. However, experimental procedures for identifying rSNPs are expensive and labour intensive. Therefore, in silico methods are required for rSNP prediction. By scoring two alleles with a TF position weight matrix (PWM), it can be determined which SNPs are likely rSNPs. However, predictions in this manner are noisy and no method exists that determines the statistical significance of a nucleotide variation on a PWM score.Results: We have designed an algorithm for in silico rSNP detection called is-rSNP. We employ novel convolution methods to determine the complete distributions of PWM scores and ratios between allele scores, facilitating assignment of statistical significance to rSNP effects. We have tested our method on 41 experimentally verified rSNPs, correctly predicting the disrupted TF in 28 cases. We also analysed 146 disease-associated SNPs with no known functional impact in an attempt to identify candidate rSNPs. Of the 11 significantly predicted disrupted TFs, 9 had previous evidence of being associated with the disease in the literature. These results demonstrate that is-rSNP is suitable for high-throughput screening of SNPs for potential regulatory function. This is a useful and important tool in the interpretation of GWAS.