Joint analysis of genetic and epigenetic data using a conditional autoregressive model.
Joint analysis of genetic and epigenetic data using a conditional autoregressive model.
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DOI：
10.1186/s12863-018-0641-8
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发表时间：
2018-09-17
期刊：
影响因子：
2.9
通讯作者：
Lu Q
中科院分区：
文献类型：
--
作者：
Shen X;Lu Q
快速发展的高通量技术使得在临床和生物学研究中收集多级组学数据变得具有成本效益。从这些研究中收集的不同类型的组学数据提供了共享和补充信息，并且可以整合到关联分析中，以增强识别新的疾病相关生物标志物的能力。为了模拟遗传标记和 DNA 甲基化对感兴趣表型的联合影响，我们提出了联合条件自回归 (JCAR) 模型。线性得分检验用于假设检验，并且可以使用戴维斯方法获得相应的p值。 JCAR 模型应用于降脂药物和饮食遗传学网络 (GOLDN) 研究的 GAW20 数据。在 JCAR 模型的应用中，我们考虑基线模型和完整模型。在基线模型中，我们考虑 3 种不同的场景：仅包含遗传信息的模型、仅在访视 2 时包含 DNA 甲基化信息的模型以及在访视 2 时同时使用遗传和 DNA 甲基化信息的模型。对于完整模型，我们在访视 2 和访视 4 时均考虑遗传和 DNA 甲基化信息。每个模型都会报告前 10 个重要基因。根据结果，我们发现只要在分析中考虑甲基化信息，MYO3B基因就显着。 JCAR 是遗传和表观遗传数据联合关联分析的有用工具。它易于实现并且计算效率高。它还可以扩展到分析其他类型的组学数据。
Rapidly evolving high-throughput technology has made it cost-effective to collect multilevel omic data in clinical and biological studies. Different types of omic data collected from these studies provide both shared and complementary information, and can be integrated into association analysis to enhance the power of identifying novel disease-associated biomarkers. To model the joint effect of genetic markers and DNA methylation on the phenotype of interest, we propose a joint conditional autoregressive (JCAR) model. A linear score test is used for hypothesis testing and the corresponding p value can be obtained using the Davies method. The JCAR model was applied to the GAW20 data from the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study. In our application of the JCAR model, we consider a baseline model and a full model. In the baseline model, we consider 3 different scenarios: a model with only genetic information, a model with only DNA methylation information at visit 2, and a model using both genetic and DNA methylation information at visit 2. For the full model, we consider both genetic and DNA methylation information at visit 2 and visit 4. The top 10 significant genes are reported for each model. Based on the results, we found that the gene MYO3B was significant as long as the methylation information was considered in the analysis. JCAR is a useful tool for joint association analysis of genetic and epigenetic data. It is easy to implement and is computationally efficient. It can also be extended to analyze other types of omic data.
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