Meta-Analysis of Multiple Regression Models and Rare Variant Gene-Gene Interaction Analysis for Next Generation Sequencing Data

该项目有两个主要目标，都与基因-基因相互作用有关。第一个目标是为多元回归分析提供一个元分析框架。默认的应用程序是交互分析。第二个主要目标是开发方法和提供分析软件，用于对从下一代测序研究中获得的罕见变异进行基于集合的相互作用分析。因此，需要扩展标准GWAS荟萃分析框架。最近描述了回归斜率的合成，并应继续进行遗传研究。应提供为多元回归模型设计的荟萃分析工具。该方法取决于参数协方差矩阵的可用性。应通过扩展现有的工具来支持该框架，以提供这些矩阵。应研究荟萃分析方法的统计学特性。一个国际数据分析项目已提上日程，罕见变异和遗传相互作用是复杂疾病缺失的广义遗传性的潜在解释。因此，将这两种想法整合到联合分析框架中是一个简单的想法。我们的目标是解决不可避免的高维问题和计算挑战。现有的基于集合的方法，包括负荷检验以及回归或方差分量检验，应扩展到基因对的分析。应研究模拟相互作用项的非负荷试验。我们最近提出了一个单自由度的超乘法检验，以提高基于集合的稀有变异相互作用分析的功效。所有测试均应在允许全基因组应用的独立工具中实施。应通过模拟研究比较不同方法的功效。

The project has two major aims, both relating to gene-gene interaction. The first goal is to provide a meta-analysis framework for multiple regression analysis. The default application will be interaction analysis. The second major goal is to develop methods and provide analysis software for set-based interaction analysis of rare variants obtained from Next Generation Sequencing studies.Models for interaction analysis are typically defined by more than one parameter. Hence, extension of the standard GWAS meta-analysis framework is needed. Synthesis of regression slopes has recently been described and shall be carried over to genetic studies. A meta-analysis tool designed for multiple regression models shall be provided. The methodology depends on the availability of parameter covariance matrices. The framework shall be supported by extending existing own tools to provide these matrices. The statistical properties of the meta-analysis method shall be investigated. An international data analysis project is on the agenda.Rare variants and genetic interaction are potential explanations of the missing, broad-sense heritability of complex diseases. Therefore, it is a straightforward idea to integrate both ideas into a joint analysis framework. Our aim is to tackle the inevitably occurring high-dimensionality problem and computational challenges. Existing set-based methods, including burden tests as well as regression or variance component tests, shall be extended to the analysis of pairs of genes. Non-burden tests that model interaction terms shall be investigated. A one-degree-of-freedom test for supra-multiplicativity, recently proposed by us, shall be applied to improve power of set-based rare variant interaction analysis. All tests shall be implemented in a stand-alone tool that allows Genome-wide application. The power of different approaches shall be compared via a simulation study.