DNA Methylation Microarrays - Experimental Design and Statistical Analysis

Wang, Sun-Chong & Petronis, Arturas

ISBN 10: 1420067273 / ISBN 13: 9781420067279

Published by CRC Press, Boca Raton, Florida, 2008

About this Item

Hardcover, 230 pages, many b/w illustrations. There is a compact plastic disc with digital data at rear inside cover "After introducing basic statistics, the disc describes wet-bench technologies that produce the data for analysis and explains how to preprocess the data to remove systemic artifacts resulting from measurement imperfections". "Explores well-established statistical methods, such as linear and Markov models, clustering, and t, f, and permutation tests.".

Seller Inventory # 135635

Bibliographic Details

• Title: DNA Methylation Microarrays - Experimental Design and Statistical Analysis
• Publisher: CRC Press, Boca Raton, Florida
• Publication Date: 2008
• Language: English
• ISBN 10: 1420067273
• ISBN 13: 9781420067279
• Binding: Hardcover
• Illustrator: many b/w illustrations
• Edition: 1st edition.
• Condition: fine
• Dust Jacket Condition: no jacket

About this title

Synopsis

Providing an interface between dry-bench bioinformaticians and wet-lab biologists, DNA Methylation Microarrays: Experimental Design and Statistical Analysis presents the statistical methods and tools to analyze high-throughput epigenomic data, in particular, DNA methylation microarray data. Since these microarrays share the same underlying principles as gene expression microarrays, many of the analyses in the text also apply to microarray-based gene expression and histone modification (ChIP-on-chip) studies.

After introducing basic statistics, the book 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. It then explores differential methylation and genomic tiling arrays. Focusing on exploratory data analysis, the next several chapters show how cluster and network analyses can link the functions and roles of unannotated DNA elements with known ones. The book concludes by surveying the open source software (R and Bioconductor), public databases, and other online resources available for microarray research.

Requiring only limited knowledge of statistics and programming, this book helps readers gain a solid understanding of the methodological foundations of DNA microarray analysis.

About the Author

Sun-Chong Wang, Art Petronis