Illustrating results with examples based on real data, this book presents the statistical methods and tools to analyze DNA methylation microarray data. It describes wet-bench technologies that produce the data for analysis, explains how to preprocess the data to remove systematic artifacts resulting from measurement imperfections, and explores differential methylation and genomic tiling arrays. The authors show how cluster and network analyses can link the functions and roles of unannotated DNA elements with known ones. They also survey the open source software, public databases, and other online resources available for microarray research. An accompanying CD-ROM contains files of plots and many color images.

Preface. Applied Statistics. DNA Methylation Microarrays and Quality Control. Experimental Design. Data Normalization. Significant Differential Methylation. High-Density Genomic Tiling Arrays. Cluster Analysis. Statistical Classification. Interdependency Network of DNA Methylation. Time Series Experiment. Online Annotations. Public Microarray Data Repositories. Open Source Software for Microarray Data Analysis. References. Index.