Analyzing Microarray Gene Expression Data (Wiley Series in Probability and Statistics) [Hardcover]

Geoffrey J. McLachlan (Author), Kim-Anh Do (Author), Christophe Ambroise (Author)

Book Description

Publication Date: August 4, 2004 | ISBN-10: 0471226165 | ISBN-13: 978-0471226161 | Edition: 1

A multi-discipline, hands-on guide to microarray analysis of biological processes

Analyzing Microarray Gene Expression Data provides a comprehensive review of available methodologies for the analysis of data derived from the latest DNA microarray technologies. Designed for biostatisticians entering the field of microarray analysis as well as biologists seeking to more effectively analyze their own experimental data, the text features a unique interdisciplinary approach and a combined academic and practical perspective that offers readers the most complete and applied coverage of the subject matter to date.

Following a basic overview of the biological and technical principles behind microarray experimentation, the text provides a look at some of the most effective tools and procedures for achieving optimum reliability and reproducibility of research results, including:

• An in-depth account of the detection of genes that are differentially expressed across a number of classes of tissues
• Extensive coverage of both cluster analysis and discriminant analysis of microarray data and the growing applications of both methodologies
• A model-based approach to cluster analysis, with emphasis on the use of the EMMIX-GENE procedure for the clustering of tissue samples
• The latest data cleaning and normalization procedures
• The uses of microarray expression data for providing important prognostic information on the outcome of disease

Editorial Reviews

Review

"…well written, logically organized…useful to those unfamiliar with the microarray literature…" (Journal of the American Statistical Association, December 2005)

“….would serve as a very good resource for a graduate topics seminar in advanced applied statistics.” (Short Book Reviews, Vol.25, No.1, April 2005)

"For the intended audience of biostatisticians and biologists…this book will be an asset." (E-STREAMS, February 2005)

"I liked this book…expands on both the tools and applications of microarray data analysis…" (Technometrics, February 2005)

From the Back Cover

A multi-discipline, hands-on guide to microarray analysis of biological processes

Analyzing Microarray Gene Expression Data provides a comprehensive review of available methodologies for the analysis of data derived from the latest DNA microarray technologies. Designed for biostatisticians entering the field of microarray analysis as well as biologists seeking to more effectively analyze their own experimental data, the text features a unique interdisciplinary approach and a combined academic and practical perspective that offers readers the most complete and applied coverage of the subject matter to date.

Following a basic overview of the biological and technical principles behind microarray experimentation, the text provides a look at some of the most effective tools and procedures for achieving optimum reliability and reproducibility of research results, including:

• An in-depth account of the detection of genes that are differentially expressed across a number of classes of tissues
• Extensive coverage of both cluster analysis and discriminant analysis of microarray data and the growing applications of both methodologies
• A model-based approach to cluster analysis, with emphasis on the use of the EMMIX-GENE procedure for the clustering of tissue samples
• The latest data cleaning and normalization procedures
• The uses of microarray expression data for providing important prognostic information on the outcome of disease

See all Editorial Reviews

Product Details

• Hardcover: 368 pages
• Publisher: Wiley-Interscience; 1 edition (August 4, 2004)
• Language: English
• ISBN-10: 0471226165
• ISBN-13: 978-0471226161
• Product Dimensions: 9.6 x 6.4 x 0.9 inches
• Shipping Weight: 1.4 pounds (View shipping rates and policies)
• Average Customer Review: 4.0 out of 5 stars  See all reviews (1 customer review)
• Amazon Best Sellers Rank: #1,731,098 in Books (See Top 100 in Books)

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Most Helpful Customer Reviews

3 of 3 people found the following review helpful:

4.0 out of 5 stars The statistics of Gene expression data from microarrays, February 25, 2010

By 

Michael R. Chernick "statman31147" (Holland PA) - See all my reviews
(REAL NAME)   

This review is from: Analyzing Microarray Gene Expression Data (Wiley Series in Probability and Statistics) (Hardcover)

McLachlan is a very well-known statistician who specializes in classification, pattern recognition and mixture distribution models. I was surprised to see him write a book on microarray data. But I shouldn't have been. It turns out that in addition to data processing and statistical design, cluster analysis and classification are important aspects of the identification of genes that are really expressing themselves in an array.

The book is designed for researchers who need to know a little about statistics and its role in analysis of microarray data and for statisticians who may know little or nothing about genes and microarrays. The purpose of Chapter 1 is to acquaint the statistician with the historical development of microarrays and to provide a brief tutorial to make the rest of the book more easily understood.

Chapter 2 explains why microarray data needs preprocessing (cleaning and normalization) For the researcher with little familiarity with statistics important concepts and techniques are discussed in detail. The key examples are multiplicity, principal component analysis, clustering, discriminant analysis, mixture distributions, determining number of mixtures, cross-validation, classification trees, bootstrap, and selection bias.

As with other books that Mclachlan authors or coauthors the book is very well-organized and well-written. It is a great resource for me and I am sure many other statisticians like me who work in medical research.