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Haplotype synthesis analysis reveals functional variants underlying known genome-wide associated susceptibility loci

机译:单倍型合成分析揭示了已知的全基因组相关易感基因座的功能变异

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Motivation: The functional mechanisms underlying disease association remain unknown for Genome-wide Association Studies (GWAS) susceptibility variants located outside coding regions. Synthesis of effects from multiple surrounding functional variants has been suggested as an explanation of hard-to-interpret findings. We define filter criteria based on linkage disequilibrium measures and allele frequencies which reflect expected properties of synthesizing variant sets. For eligible candidate sets, we search for haplotype markers that are highly correlated with associated variants. Results: Via simulations we assess the performance of our approach and suggest parameter settings which guarantee 95% sensitivity at 20-fold reduced computational cost. We apply our method to 1000 Genomes data and confirmed Crohn's Disease (CD) and Type 2 Diabetes (T2D) variants. A proportion of 36.9% allowed explanation by three-variant-haplotypes carrying at least two functional variants, as compared to 16.4% for random variants (P = 1: 72 x 10(-8)). Association could be explained by missense variants for MUC19, PER3 (CD) and HMG20A (T2D). In a CD GWAS-imputed using haplotype reference consortium data (64 976 haplotypes)-we could confirm the syntheses of MUC19 and PER3 and identified synthesis by missense variants for 6 further genes (ZGPAZ, GPR65, CLN3/NPIPB8, LOC102723878, rs2872507, GCKR). In all instances, the odds ratios of the synthesizing haplotypes were virtually identical to that of the index SNP. In summary, we demonstrate the potential of synthesis analysis to guide functional follow-up of GWAS findings. Availability and implementation: All methods are implemented in the C/C++ toolkit GetSynth, available at http://sourceforge.net/projects/getsynth/.
机译:动机:对于位于编码区外部的全基因组关联研究(GWAS)易感性变体,疾病关联的功能机制仍然未知。已经提出了来自多种周围功能变体的效应的合成,以解释难以解释的发现。我们基于连锁不平衡量度和等位基因频率定义筛选标准,这些标准反映了合成变异集的预期特性。对于合格的候选集,我们搜索与相关变体高度相关的单倍型标记。结果:通过仿真,我们评估了该方法的性能,并提出了建议的参数设置,这些参数设置可在将计算成本降低20倍的情况下确保95%的灵敏度。我们将我们的方法应用于1000个基因组数据并确认了克罗恩病(CD)和2型糖尿病(T2D)变异。 36.9%的比例允许通过携带至少两个功能变体的三变体单倍型进行解释,而随机变体的比例为16.4%(P = 1:72 x 10(-8))。可以用MUC19,PER3(CD)和HMG20A(T2D)的错义变体解释关联。在使用单倍型参考联合体数据(64 976个单倍型)估算的CD GWAS中,我们可以确认MUC19和PER3的合成,并通过错义变体鉴定了6个其他基因(ZGPAZ,GPR65,CLN3 / NPIPB8,LOC102723878,rs2872507,GCKR)的合成)。在所有情况下,合成单倍型的优势比实际上与索引SNP的优势比相同。总而言之,我们证明了合成分析在指导GWAS发现的功能随访方面的潜力。可用性和实现:所有方法都在C / C ++工具包GetSynth中实现,该工具包可从http://sourceforge.net/projects/getsynth/获得。

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