Identification of genetic association of multiple rare variants using collapsing methods.
Identification of genetic association of multiple rare variants using collapsing methods.
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DOI：
10.1002/gepi.20658
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发表时间：
2011
影响因子：
2.1
通讯作者：
Ziegler, Andreas
中科院分区：
文献类型：
--
作者：
Sun, Yan V. d;Sung, Yun Ju;Tintle, Nathan;Ziegler, Andreas
下一代测序技术允许研究人类中常见和罕见的变异。外显子组在群体水平或家族中测序，以进一步研究人类疾病的遗传学。遗传分析研讨会17（GAW17）提供了来自1000个基因组计划的外显子组数据和模拟表型。这些数据使得能够评估用于稀有变异序列分析的现有和新开发的统计方法，对于稀有变异序列分析，标准统计方法由于等位基因的稀有性而失败。已经提出了各种替代方法，通过组合基因内的多个稀有变体来克服稀有问题。这些方法被称为折叠方法，我们的GAW17小组专注于研究使用罕见变体的现有和新型折叠方法的性能。根据I类误差和功效测量，所有测试方法的性能相似。膨胀的I型错误分数一致观察，可能是由于在这个相对较小的样本中因果和非因果罕见变异之间的配子相不平衡以及人口分层。对先前知识的补充，如适当的协变量和SNP功能信息，增加了检测相关基因的能力。总的来说，破坏罕见变异可以增加识别疾病相关基因的能力。然而，研究罕见变异的遗传关联仍然是一项具有挑战性的任务，需要进一步开发和改进数据收集，管理，分析和计算。
Next-generation sequencing technology allows investigation of both common and rare variants in humans. Exomes are sequenced on the population level or in families to further study the genetics of human diseases. Genetic Analysis Workshop 17 (GAW17) provided exomic data from the 1000 Genomes Project and simulated phenotypes. These data enabled evaluations of existing and newly developed statistical methods for rare variant sequence analysis for which standard statistical methods fail because of the rareness of the alleles. Various alternative approaches have been proposed that overcome the rareness problem by combining multiple rare variants within a gene. These approaches are termed collapsing methods, and our GAW17 group focused on studying the performance of existing and novel collapsing methods using rare variants. All tested methods performed similarly, as measured by type I error and power. Inflated type I error fractions were consistently observed and might be caused by gametic phase disequilibrium between causal and noncausal rare variants in this relatively small sample as well as by population stratification. Incorporating prior knowledge, such as appropriate covariates and information on functionality of SNPs, increased the power of detecting associated genes. Overall, collapsing rare variants can increase the power of identifying disease-associated genes. However, studying genetic associations of rare variants remains a challenging task that requires further development and improvement in data collection, management, analysis, and computation.
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影响因子：
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