A Beginner S Guide to Microarrays

By: Eric M. Blalock

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Hardcover | 31 July 2003

At a Glance

Hardcover
368 Pages

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23.5 x 15.88 x 1.91

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Microarray technology is more accessible than ever, and an ever-widening field of scientists is using this technology. However, the manufacture, experimental design, and analysis of microarrays are not always straightforward, and researchers new to the field run into technical and theoretical roadblocks that can hinder progress with this powerful new technology.
A Beginner's Guide to Microarrays addresses two audiences - the core facility manager who produces, hybridizes, and scans arrays, and the basic research scientist who will be performing the analysis and interpreting the results. User friendly coverage and detailed protocols are provided for the technical steps and procedures involved in many facets of microarray technology, including:

-Cleaning and coating glass slides,
-Designing oligonucleotide probes,
-Constructing arrays for the detection and quantification of different bacterial species,
-Preparing spotting solutions,
-Troubleshooting spotting problems,
-Setting up and running a core facility,
-Normalizing background signal and controlling for systematic variance,
-Designing experiments for maximum effect,
-Analyzing data with statistical procedures,
-Clustering data with machine-learning protocols.

This book is addressed to researchers using microarrays for the first time. One faces a myriad of problems at the outset of such a task, and there is no need to 'reinvent the wheel' for each scientist that runs into these problems. Knowing the strengths and weaknesses of microarrays before research begins can save time, money, and resources.

Industry Reviews

From the reviews: "The book offers a broad coverage of many of the most important aspects of microarray technology ! . Despite the wide field broached by this book, one of its chief successes lies with the fact that in each chapter the authors provide a clear review of every step of the technique, including both its potential and pitfalls. This allows all readers, especially beginners, to understand the development and impact of this important technique. ! Readers will find this beginner's guide book very informative ! ." (Guillermina Lopez-Bendito, Journal of Chemical Neuroanatomy, Vol. 30, 2005)

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Preface	p. xv
	p. 1
Slide Coating and Dnaimmobilization Chemistries	p. 1
Introduction	p. 1
Glass Properties	p. 1
Glass Cleaning	p. 3
Slide Coating Chemistries	p. 9
Dnaimmobilization Chemistries	p. 11
Surface Analysis Methods	p. 32
Summary	p. 36
References	p. 36
	p. 43
Diagnostic Oligonucleotide Microarrays for Microbiology	p. 43
Introduction	p. 44
Scheme of the Experimental Approach	p. 46
Sources of Variation	p. 46
Establishment of a Sequence Database	p. 47
Oligo Length and Melting Temperature (TM); Designing Oligo Sets Tuned to Work Together	p. 52
Oligo Set Design	p. 53
Choice of Oligo/Surface Binding Chemistry	p. 63
Array Printing	p. 65
Target Preparation	p. 66
Hybridisation	p. 73
Scanning	p. 74
Dataanalysis	p. 77
Applications in Microbial Identification	p. 78
Acknowledgements	p. 82
Links Related to Diagnostic Microbial Microarrays	p. 82
Reference List	p. 84
	p. 93
Printing Technologies and Microarray Manufacturing Techniques: Making the Perfect Microarray	p. 93
Introduction	p. 93
Microarray Manufacturing	p. 94
Comparing Printing Technologies	p. 108
Conclusions	p. 120
Acknowledgments	p. 121
Reference List	p. 121
	p. 123
Arrays for the Masses-Setting Up a Microarray Core Facility	p. 123
Preface	p. 123
Introduction	p. 124
Hedco/Oregon Cancer Institute Spotted Microarray Core at Ohsu	p. 126
Core Set-Up	p. 128
Array Printing	p. 129
The Printer	p. 130
Slides	p. 133
Amplification	p. 135
Printing the Array	p. 136
Hybridization	p. 139
Scanner	p. 142
Other Equipment	p. 145
Conclusion	p. 147
References	p. 148
	p. 151
Microarray Data Normalization: The Art and Science of Overcoming Technical Variance to Maximize the Detection of Biologic Variance	p. 151
Normalization: Correcting for Technical Variance in Order to Study Biological Variation	p. 151
Single Channel Data Normalizations	p. 156
Normalizations of Two-Channel Data	p. 161
The Role of Experimental Design in the Removal of Technical Variance	p. 167
Gene-Specific Normalizations and Clustering	p. 173
References	p. 176
	p. 179
Experimental Design and Data Analysis	p. 179
Introduction	p. 179
Measuring RNA	p. 180
Fold Change Significance	p. 182
Variance	p. 187
Experimental Design	p. 189
Variance and Fold-Change	p. 195
Affymetrix Data	p. 201
Working with More than Two Groups	p. 215
Functional Grouping	p. 226
Using Excel	p. 235
Acknowledgements	p. 236
References	p. 237
	p. 243
Microarray Experiment Design and Statistical Analysis	p. 243
Introduction	p. 243
Designing a Microarray Experiment	p. 245
General Procedures for Statistical Analysis of Microarray Data	p. 248
Multiple Hypothesis Testing in Microarray Experiments	p. 249
Methods Based on P Value Adjustment	p. 252
Analysis of Variance	p. 263
Summary of the Chapter	p. 272
Some Useful Online Sources for Microarray Analysis	p. 272
References	p. 274
	p. 277
Strategies for Clustering, Classifying, Integrating, Standardizing and Visualizing Microarray Gene Expression Data	p. 277
Introduction	p. 277
Microarray Gene Expression Matrix	p. 280
Distance Functions	p. 284
Unsupervised Analysis and Clustering of Microarray Data	p. 288
Methods for Validating Unsupervised Analysis	p. 299
Supervised Microarray Data Analysis	p. 303
Nearest Neighbors	p. 306
Support Vector Machines	p. 307
Methods to Improve Classifier Performance	p. 312
Genetic and Biochemical Networks	p. 314
Additional Methods for Microarray Data Analysis	p. 315
Microarray Data Visualization	p. 317
Microarray Data Standardization and Integration	p. 319
Microarray Gene Expression Markup Language (Mage-ML)	p. 322
Microarray Data Repositories	p. 324
Challenges in Microarray Gene Expression Data Analysis	p. 326
Conclusions	p. 328
References	p. 329
Index	p. 341
Table of Contents provided by Ingram. All Rights Reserved.

A Beginner S Guide to Microarrays

At a Glance

Hardcover

Industry Reviews

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