该协议详细介绍了通常在病例对照关联研究期间进行的数据质量评估和控制的步骤。所描述的步骤包括鉴定和去除DNA样品和引入偏倚的标记。这些关键步骤对于病例对照研究的成功至关重要,并且在进行统计学关联测试之前是必要的。我们描述如何使用PLINK,处理SNP数据的工具,对每个个体和每个SNP的失败率进行评估,并评估个体之间的相关性程度。我们还详细介绍了其他质量控制程序,包括使用SMARTPCA软件识别祖先离群值。选择这些平台是因为它们对用户友好,广泛使用,计算效率高。这里不讨论使用病例对照数据检测和建立疾病关联所需的步骤。在我们的早期方案中已经讨论了病例对照研究中有关研究设计和标记选择的问题。这个协议,这是我们实验室经常使用的,大约需要8小时才能完成。
This protocol details the steps for data quality assessment and control that are typically carried out during
case-control association studies. The steps described involve the identification and removal of DNA samples and markers that introduce bias. These critical steps are paramount to the success of a
case-control study and are necessary before statistically testing for association. We describe how to use PLINK, a tool for handling SNP data, to perform assessments of failure rate per individual and per SNP and to assess the degree of relatedness between individuals. We also detail other quality-control procedures, including the use of SMARTPCA software for the identification of ancestral outliers. These platforms were selected because they are user-friendly, widely used and computationally efficient. Steps needed to detect and establish a disease association using
case-control data are not discussed here. Issues concerning study design and marker selection in
case-control studies have been discussed in our earlier protocols. This protocol, which is routinely used in our labs, should take approximately 8 h to complete.