Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
BioMediTech Institute, Tampere University, Tampere, Finland.
Methods Mol Biol. 2022;2401:79-100. doi: 10.1007/978-1-0716-1839-4_7.
DNA microarray data preprocessing is of utmost importance in the analytical path starting from the experimental design and leading to a reliable biological interpretation. In fact, when all relevant aspects regarding the experimental plan have been considered, the following steps from data quality check to differential analysis will lead to robust, trustworthy results. In this chapter, all the relevant aspects and considerations about microarray preprocessing will be discussed. Preprocessing steps are organized in an orderly manner, from experimental design to quality check and batch effect removal, including the most common visualization methods. Furthermore, we will discuss data representation and differential testing methods with a focus on the most common microarray technologies, such as gene expression and DNA methylation.
DNA 微阵列数据预处理在从实验设计开始并导致可靠的生物学解释的分析路径中至关重要。事实上,当考虑了实验计划的所有相关方面时,从数据质量检查到差异分析的以下步骤将导致稳健、值得信赖的结果。在本章中,将讨论微阵列预处理的所有相关方面和注意事项。预处理步骤按顺序组织,从实验设计到质量检查和批次效应去除,包括最常见的可视化方法。此外,我们将讨论数据表示和差异测试方法,重点介绍最常见的微阵列技术,如基因表达和 DNA 甲基化。