Illustrating results with examples based on real firsthand 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, and explains how to preprocess the data to remove systematic artifacts resulting from measurement imperfections.
Written from the perspective of an analyst who interacts closely with biology colleagues who have only minimal knowledge of statistics and programming, DNA Methylation Microarrays provides a solid understanding of methodological foundations and enables critical thinking for advanced studies. Using graphics to illustrate the results, the book presents examples based on real biological data from a variety of cellular samples with array hybridizations performed in the laboratory. It covers quality control, experimental design, normalization, significant differential methylation, clustering, dependence networks, and online annotations.
I found the book to be very informative and a timely introduction to the issues related to designing and analyzing array-based methylation experiments. ? it provides a solid grounding and serves as a good reference book for any statistician venturing into this field.
-Sarah Bujac, Pharmaceutical Statistics, 2011, 10
?a useful presentation of four detailed, well-written parts concerning techniques in the analysis of high throughput epigenomic data ? a consistent and self-contained overview on important fundamental and modern procedures used by researchers in biology, bioinformatics, experimental designs ?The book is of great interest to research workers who use the above-mentioned procedures in experimental design and deep analysis of epigenomic data with sound statistics.
-Cryssoula Ganatsiou, Zentralblatt MATH 1172
?This book is a helpful guide for researchers and students with an interest in performing genomic studies using high-throughput microarrays. ? A wide range of useful data analysis tools are covered ? Other strengths throughout the book include the discussion of experimental design, the mention of software for certain analyses, and the inclusion of more advanced methods such as wavelets and genetic algorithms. ? Overall, this book gives a nice summary of methods used for the analysis of hybridization-based microarray data. ?
-Biometrics, March 2009
