DNA Methylation Microarrays
Experimental Design and Statistical Analysis
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Product details:
- Edition number 1
- Publisher Chapman and Hall
- Date of Publication 21 October 2019
- ISBN 9780367387402
- Binding Paperback
- No. of pages256 pages
- Size 234x156 mm
- Weight 453 g
- Language English 5
Categories
Short description:
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.
MoreLong description:
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.
MoreTable of Contents:
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.
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