Quality control issues and the identification of rare functional variants with next-generation sequencing data.
Quality control issues and the identification of rare functional variants with next-generation sequencing data.
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质量控制问题和使用下一代测序数据鉴定稀有功能变体。
DOI：
10.1002/gepi.20645
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发表时间：
2011
影响因子：
2.1
通讯作者：
Wilson, Alexander F.
中科院分区：
文献类型：
--
作者：
Hemmelmann, Claudia;Daw, E. Warwick;Wilson, Alexander F.
关键词：
由于变异的罕见性，对大量个体的下一代测序在数据准备、质量控制和统计分析方面提出了挑战。遗传分析研讨会17 （GAW17）的数据提供了一个调查现有方法并将这些方法与新方法进行比较的机会。具体来说，GAW17第2组的贡献者调查了现有的和新提出的方法和研究设计策略，以识别罕见变异，预测功能变异和/或检查质量控制。我们介绍了第二组的八篇论文，总结了他们的方法，并讨论了他们的优缺点。在这些研究中，一些小组只使用基因型数据，而另一些小组也使用模拟表型数据。虽然第2组的8个贡献涵盖了识别罕见变异的广泛主题，但根据他们共同的研究兴趣，他们可以分为三大类：变异的功能和质量控制问题，基于家庭的分析，以及不相关个体的关联分析。第一个小组的目标是完全不同的。这些是种群结构分析，使用罕见的变异来预测功能并检查基因型呼叫的准确性。以家庭为基础的分析的目的是选择哪些家庭应该进行测序，并确定高危谱系；关联分析的目的是用基于回归的方法识别变异或基因。然而，在所有三项关联研究中，检测关联的能力都很低。因此，这项工作显示了将罕见变异纳入常见疾病的遗传和统计分析的机会。
Next-generation sequencing of large numbers of individuals presents challenges in data preparation, quality control, and statistical analysis because of the rarity of the variants. The Genetic Analysis Workshop 17 (GAW17) data provide an opportunity to survey existing methods and compare these methods with novel ones. Specifically, the GAW17 Group 2 contributors investigate existing and newly proposed methods and study design strategies to identify rare variants, predict functional variants, and/or examine quality control. We introduce the eight Group 2 papers, summarize their approaches, and discuss their strengths and weaknesses. For these investigations, some groups used only the genotype data, whereas others also used the simulated phenotype data. Although the eight Group 2 contributions covered a wide variety of topics under the general idea of identifying rare variants, they can be grouped into three broad categories according to their common research interests: functionality of variants and quality control issues, family-based analyses, and association analyses of unrelated individuals. The aims of the first subgroup were quite different. These were population structure analyses that used rare variants to predict functionality and examine the accuracy of genotype calls. The aims of the family-based analyses were to select which families should be sequenced and to identify high-risk pedigrees; the aim of the association analyses was to identify variants or genes with regression-based methods. However, power to detect associations was low in all three association studies. Thus this work shows opportunities for incorporating rare variants into the genetic and statistical analyses of common diseases.
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影响因子：
14.9
作者：
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通讯作者：
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