Presents practical approaches for the analysis of data from gene expression microarrays. Each chapter describes the conceptual and methodological underpinning for a statistical tool and its implementation in software. Methods cover all aspects of statistical analysis of microarrays, from annotation and filtering to clustering and classification.
From the reviews: "This useful book about methods and software for microarray data analysis is written by the developers. The goal of the book is to provide guidance to practitioners in the techniques of analysis and programs. The book combines the advantages of both a tutorial in methods and catalogue for software. Procedures are described and their implementations illustrated. All of the software described is freely available to academic users...The table of contents indicates the encyclopedic coverage, spanning a very broad spectrum of methods. The collection is introduced with an informative overview. While the authors acknowledge the formative stage of current work, they have provided a useful guide to the here and now." ISI Short Book Reviews, Vol. 23/3, August 2003 "The opening chapter contributed by the editors is an excellent overview of the field and the threads that make it up...There is a definite hands-on character to all the presentations. Generally, each contributor selected a different but interesting set of data to demonstrate the approach." Journal of Statsitical Software, April 2005 "The editors state that the goal of this book is 'to provide guidance to practitioners in deciding which statistical approaches and packages may be indicated for their projects ! . All chapters contain clear directions for installing and using the presented packages. ! For the practitioner of microarray data analysis, this book contains a wealth of readily available tools. For the statistician who wants to get acquainted with this rapidly evolving area, the book offers a glimpse of current problems and methods ! ." (Ricardo A. Maronna, Statistical Papers, Vol. 45 (2), 2004) "This volume provides a summary of many of the issues and software that are available. ! This is a welcome volume. The first chapter provides a wonderful introduction to the field. The later chapters are more specialised. These chapters are good references to the individual programs and methods and can be used to find links to the major software for microarray analysis." (Peter A. Lachenbruch, ISCB Newsletter, Issue 38, December, 2004) "This useful book about methods and software for microarray data analysis is written by the developers. The goal of the book is to provide guidance to practitioners in the techniques of analysis and programs. The book combines the advantages of both a tutorial in methods and catalogue for software. Procedures are described and their implementations illustrated. ! While the authors acknowledge the formative stage of current work, they have provided a useful guide to the here and now." (D. F. Andrews, Short Book Reviews, Vol. 23 (2), 2003) "This book is a collection of papers on statistical techniques for gene expression data. ! The book is well written and I enjoyed reading the book. ! The chapters that discuss the same statistical topics often have different approaches or focuses on the type of arrays. This makes it worthwhile to read the sections on a particular topic in all chapters. I recommend this book to anyone who is interested in or performing the analysis of microarray data." (dr E. R. van den Heuvel, Kwantitatieve Methoden, April, 2004) "Gene expression microarray technology was introduced in 1995, but it is only in 1998 that the scientific community started using this tool ! . Writing a book on such a novel subject matter ! is not a simple task. ! 'The Analysis of Gene Expression Data: Methods and Software' appears as a successful attempt. ! this book succeeds in the not trivial task of providing an informative, accessible, overall picture of the contributions of statisticians to the analysis of microarray data." (Chiara Sabatti, Statistics in Medicine, Vol. 23, 2004)
Introduction.- Visualization and annotation of genomic experiments.- Bioconductor R packages for exploratory data analysis and normalization of cDNA microarray data.- An R package for analyses of affymetrix oligonucleotide arrays.- DNA-Chip analyzer (d-Chip).- Expression Profiler.- An S-Plus library for the analysis of microarray data.- DRAGON and DRAGON View: Methods for the annotation, analysis, and visualization of large-scale gene expression data.- SNOMAD: User-friendly web tools for the standardization and normalization of microarry data.- Microarray analysis using the MicroArray Explorer.- Parametric empirical Bayes methods for microarrays.- SAM thresholding and false discovery rates for detecting differential gene expression in DNA microarrays.- Adaptive gene picking with microarray data: Detecting important low abundance signals.-MAANOVA: A software package for the analysis of spotted cDNA microarray experiments.- GeneClust.- POE Statistical Tools for molecular profiling.- Bayesian decomposition.- Cluster analysis of gene expression dynamics.- Relevance networks: A first step towards finding genetic regulatory networks within microarray data.
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