The Analysis of Gene Expression Data: Methods and Software / Edition 1

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Overview

This book 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. Chapters are written by the developers of the software. All software packages described are free to academic users. The book includes coverage of various packages that are part of the Bioconductor Project and several related R tools. The materials presented cover a range of software tools designed for varied audiences. Some chapters describe simple menu-driven software in a user-friendly fashion and are designed to be accessible to microarray data analysts without formal quantitative training. Most chapters are directed at microarray data analysts with master's-level training in computer science, biostatistics, or bioinformatics. A minority of more advanced chapters are intended for doctoral students and researchers.
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Editorial Reviews

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"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)

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Product Details

  • ISBN-13: 9780387955773
  • Publisher: Springer New York
  • Publication date: 4/28/2003
  • Series: Statistics for Biology and Health Series
  • Edition description: 2003
  • Edition number: 1
  • Pages: 456
  • Product dimensions: 6.10 (w) x 9.30 (h) x 1.10 (d)

Table of Contents

Preface
Contributors
Color Insert
1 The Analysis of Gene Expression Data: An Overview of Methods and Software 1
2 Visualization and Annotation of Genomic Experiments 46
3 Bioconductor R Packages for Exploratory Analysis and Normalization of cDNA Microarray Data 73
4 An R Package for Analyses of Affymetrix Oligonucleotide Arrays 102
5 DNA-Chip Analyzer (dChip) 120
6 Expression Profiler 142
7 An S-PLUS Library for the Analysis and Visualization of Differential Expression 163
8 DRAGON and DRAGON View: Methods for the Annotation, Analysis, and Visualization of Large-Scale Gene Expression Data 185
9 SNOMAD: Biologist-Friendly Web Tools for the Standardization and NOrmalization of Microarray Data 210
10 Microarray Analysis Using the MicroArray Explorer 229
11 Parametric Empirical Bayes Methods for Microarrays 254
12 SAM Thresholding and False Discovery Rates for Detecting Differential Gene Expression in DNA Microarrays 272
13 Adaptive Gene Picking with Microarray Data: Detecting Important Low Abundance Signals 291
14 MAANOVA: A Software Package for the Analysis of Spotted cDNA Microarray Experiments 313
15 GeneClust 342
16 POE: Statistical Methods for Qualitative Analysis of Gene Expression 362
17 Bayesian Decomposition 388
18 Bayesian Clustering of Gene Expression Dynamics 409
19 Relevance Networks: A First Step Toward Finding Genetic Regulatory Networks Within Microarray Data 428
Index 447
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