Interest in microarrays has increased considerably in the last ten years. This increase in the use of microarray technology has led to the need for good standards of microarray experimental notation, data representation, and the introduction of standard experimental controls, as well as standard dat
Statistics for microarrays: design, analysis, and inference
โ Scribed by Ernst Wit
- Publisher
- Wiley
- Year
- 2004
- Tongue
- English
- Leaves
- 268
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
Interest in microarrays has increased considerably in the last ten years. This increase in the use of microarray technology has led to the need for good standards of microarray experimental notation, data representation, and the introduction of standard experimental controls, as well as standard data normalization and analysis techniques. Statistics for Microarrays: Design, Analysis and Inference is the first book that presents a coherent and systematic overview of statistical methods in all stages in the process of analysing microarray data โ from getting good data to obtaining meaningful results.
- Provides an overview of statistics for microarrays, including experimental design, data preparation, image analysis, normalization, quality control, and statistical inference.
- Features many examples throughout using real data from microarray experiments.
- Computational techniques are integrated into the text.
- Takes a very practical approach, suitable for statistically-minded biologists.
- Supported by a Website featuring colour images, software, and data sets.
Primarily aimed at statistically-minded biologists, bioinformaticians, biostatisticians, and computer scientists working with microarray data, the book is also suitable for postgraduate students of bioinformatics.
โฆ Table of Contents
Front......Page 1
Contents......Page 5
Preface......Page 9
1 Preliminaries......Page 11
Part I: Getting good data......Page 23
2 Set-up of a microarray experiment......Page 24
3 Statistical design of microarrays......Page 31
4 Normalization......Page 65
5 Quality assessment......Page 110
6 Microarray myths: data......Page 132
Part II: Getting good answers......Page 142
7 Microarray discoveries......Page 143
8 Differential expression......Page 182
9 Predicting outcomes with gene expression profiles......Page 216
10 Microarray myths: inference......Page 251
Bibliography......Page 254
Index......Page 262
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