Pathway-based approaches for sequencing-based genome-wide association studies.
Pathway-based approaches for sequencing-based genome-wide association studies.
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DOI：
10.1002/gepi.21728
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发表时间：
2013-07
影响因子：
2.1
通讯作者：
Zhi, Degui
中科院分区：
文献类型：
--
作者：
Wu, Guodong;Zhi, Degui
关键词：
为了分析复杂的性状与测序数据的关联，目前大多数研究测试基因或基因组区域中变异的聚集效应。虽然基于基因的测试即使对于中等大小的样本也没有足够的功效，但基于途径的分析结合了生物途径中多个基因的联合收割机信息，并可能提供额外的见解。然而，大多数现有的通路关联方法最初是为全基因组关联研究（GWAS）设计的，并且没有针对测序数据进行全面评估。此外，基于区域的罕见变异关联方法，虽然通过将其区域定义扩展到基因集而可能适用于基于路径的分析，但从未经过严格测试。在基于外显子组的研究背景下，我们使用模拟和真实的数据集来评估基于路径的关联测试。我们的模拟策略采用了全基因组遗传模型，将总遗传效应分层分布到通路、基因和个体变异中，从而可以对基于通路的方法进行评估，并对潜在的遗传结构进行现实的可量化假设。结果表明，虽然没有单一的基于路径的关联方法在所有模拟场景中提供上级性能，但使用来自单标记测试的统计数据而没有基因水平崩溃的GSEA方法的修改（WKS-变体方法）始终是强大的。有趣的是，直接应用罕见变异关联测试（例如，SKAT）的途径分析提供了类似的权力，但其结果是敏感的遗传结构的假设。我们将途径关联分析应用于慢性阻塞性肺病（COPD）的外显子组测序数据，发现WKS-Variant方法证实了之前发表的相关基因。
For analyzing complex trait association with sequencing data, most current studies test aggregated effects of variants in a gene or genomic region. While gene-based tests have insufficient power even for moderately sized samples, pathway-based analyses combine information across multiple genes in biological pathways and may offer additional insight. However, most existing pathway association methods are originally designed for genome-wide association studies (GWAS), and are not comprehensively evaluated for sequencing data. Moreover, region-based rare variant association methods, although potentially applicable to pathway-based analysis by extending their region definition to gene sets, have never been rigorously tested. In the context of exome-based studies, we use simulated and real data sets to evaluate pathway-based association tests. Our simulation strategy adopts a genome-wide genetic model that distributes total genetic effects hierarchically into pathways, genes, and individual variants, allowing the evaluation of pathway-based methods with realistic quantifiable assumptions on the underlying genetic architectures. The results show that, while no single pathway-based association method offers superior performance in all simulated scenarios, a modification of GSEA approach using statistics from single-marker tests without gene-level collapsing (WKS-Variant method) is consistently powerful. Interestingly, directly applying rare variant association tests (e.g., SKAT) to pathway analysis offers a similar power, but its results are sensitive to assumptions of genetic architecture. We applied pathway association analysis to an exome sequencing data of the chronic obstructive pulmonary disease (COPD), and found that the WKS-Variant method confirms associated genes previously published.
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DOI：
10.1183/09031936.00120408
发表时间：
2009-07
期刊：
The European respiratory journal
影响因子：
--
作者：
Hansel NN;Gao L;Rafaels NM;Mathias RA;Neptune ER;Tankersley C;Grant AV;Connett J;Beaty TH;Wise RA;Barnes KC
通讯作者：
Barnes KC
影响因子：
10
作者：
He JQ;Foreman MG;Shumansky K;Zhang X;Akhabir L;Sin DD;Man SF;DeMeo DL;Litonjua AA;Silverman EK;Connett JE;Anthonisen NR;Wise RA;Paré PD;Sandford AJ
通讯作者：
Sandford AJ
DOI：
10.1073/pnas.0812824106
发表时间：
2009-03-10
影响因子：
11.1
作者：
Kryukov, Gregory V.;Shpunt, Alexander;Sunyaev, Shamil R.
通讯作者：
Sunyaev, Shamil R.
影响因子：
30.8
作者：
Li, Yingrui;Vinckenbosch, Nicolas;Wang, Jun
通讯作者：
Wang, Jun
影响因子：
6.4
作者：
Czene, K;Lichtenstein, P;Hemminki, K
通讯作者：
Hemminki, K