On the analysis of sequence data: testing for disease susceptibility loci using patterns of linkage disequilibrium.
On the analysis of sequence data: testing for disease susceptibility loci using patterns of linkage disequilibrium.
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关于序列数据的分析：使用连锁不平衡模式对疾病敏感性基因座进行测试。
DOI：
10.1002/gepi.20638
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发表时间：
2011-12
影响因子：
2.1
通讯作者：
Lange, Christoph
中科院分区：
文献类型：
--
作者：
Lipman, Peter J.;Yip, Wai-Ki;AlChawa, Taofik;Ludwig, Kerstin U.;Mangold, Elisabeth;Lange, Christoph
尽管GWAS有许多成功的应用，但发现DSL仍然有很多困难。这是因为GWAS方法是一种间接作图技术，通常用于识别标记。为了识别DSL，这是理解复杂疾病的遗传途径所必需的，直接检查每个遗传位点的测序数据是必要的。然而，目前缺乏靶向鉴定测序数据中的DSL的方法：现有方法将致病变体定位于区域，而不是单个变体，因此不允许鉴定引起表型关联的独特基因座。在这里，我们已经开发了这样一种方法，以确定是否有证据表明，一个单独的基因座影响测序数据的病例对照状态。这种方法与其他罕见变异方法不同：我们可以识别导致表型和遗传区域之间关联的单个遗传基因座，而不是测试由许多基因座组成的整个区域与表型的关联。对于每个变体，测试确定其他变体上的LD模式是否与该变体是DSL时预期的模式一致。功效模拟表明，该方法成功地检测到因果变量，将其与附近的其他变量（具有因果变量的高LD）区分开来，并且优于标准测试。该方法的效率是特别明显的小样本，这是目前现实的研究，由于序列数据的成本。该方法的实际意义是说明了一个应用程序的序列数据集为非综合征性唇裂或腭裂。所提出的方法涉及一个变量（Bonferroni校正后p=0.002，.062），标准分析未发现该变量。可提供执行代码。
Despite the numerous, successful applications of GWASs, there has been much difficulty in discovering DSLs. This is due to the fact that the GWAS approach is an indirect mapping technique, often identifying markers. For the identification of DSLs, which is required for the understanding of the genetic pathways for complex diseases, sequencing data that examines every genetic locus directly is necessary. Yet there is currently a lack of methodology targeted at the identification of the DSLs in sequencing data: existing methods localize the causal variant to a region, but not to a single variant and therefore do not allow one to identify unique loci that cause the phenotype association. Here, we have developed such a method to determine if there is evidence that an individual loci affects case-control status with sequencing data. This methodology differs from other rare variant approaches: rather than testing an entire region comprised of many loci for association with the phenotype, we can identify the individual genetic locus that causes the association between the phenotype and the genetic region. For each variant, the test determines if the pattern of LD across the other variants coincides with the pattern expected if that variant were a DSL. Power simulations show that the method successfully detects the causal variant, distinguishing it from other nearby variants (in high LD with the causal variant), and outperforms the standard tests. The efficiency of the method is especially apparent with small samples, which are currently realistic for studies due to sequence data costs. The practical relevance of the approach is illustrated by an application to a sequence dataset for nonsyndromic cleft lip with or without cleft palate. The proposed method implicated one variant (p=0.002, .062 after Bonferroni correction), which was not found by standard analyses. Code for implementation is available.
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影响因子：
30.8
作者：
Helbig I;Mefford HC;Sharp AJ;Guipponi M;Fichera M;Franke A;Muhle H;de Kovel C;Baker C;von Spiczak S;Kron KL;Steinich I;Kleefuss-Lie AA;Leu C;Gaus V;Schmitz B;Klein KM;Reif PS;Rosenow F;Weber Y;Lerche H;Zimprich F;Urak L;Fuchs K;Feucht M;Genton P;Thomas P;Visscher F;de Haan GJ;Møller RS;Hjalgrim H;Luciano D;Wittig M;Nothnagel M;Elger CE;Nürnberg P;Romano C;Malafosse A;Koeleman BP;Lindhout D;Stephani U;Schreiber S;Eichler EE;Sander T
通讯作者：
Sander T
影响因子：
11
作者：
通讯作者：
--
影响因子：
4.4
作者：
DEVLIN, B;RISCH, N
通讯作者：
RISCH, N
影响因子：
4.3
作者：
Coffman, Frederick D.;He, Mai;Cohen, Stanley
通讯作者：
Cohen, Stanley
影响因子：
158.5
作者：
Weiss, Lauren A.;Shen, Yiping;Daly, Mark J.
通讯作者：
Daly, Mark J.