Book contents
- Frontmatter
- Contents
- Foreword
- Preface
- Acknowledgments
- MICROARRAY BIOINFORMATICS
- 1 Microarrays: Making Them and Using Them
- 2 Sequence Databases for Microarrays
- 3 Computer Design of Oligonucleotide Probes
- 4 Image Processing
- 5 Normalisation
- 6 Measuring and Quantifying Microarray Variability
- 7 Analysis of Differentially Expressed Genes
- 8 Analysis of Relationships Between Genes, Tissues or Treatments
- 9 Classification of Tissues and Samples
- 10 Experimental Design
- 11 Data Standards, Storage and Sharing
- Appendix: MIAME Glossary
- Index
- Plate section
7 - Analysis of Differentially Expressed Genes
Published online by Cambridge University Press: 15 January 2010
- Frontmatter
- Contents
- Foreword
- Preface
- Acknowledgments
- MICROARRAY BIOINFORMATICS
- 1 Microarrays: Making Them and Using Them
- 2 Sequence Databases for Microarrays
- 3 Computer Design of Oligonucleotide Probes
- 4 Image Processing
- 5 Normalisation
- 6 Measuring and Quantifying Microarray Variability
- 7 Analysis of Differentially Expressed Genes
- 8 Analysis of Relationships Between Genes, Tissues or Treatments
- 9 Classification of Tissues and Samples
- 10 Experimental Design
- 11 Data Standards, Storage and Sharing
- Appendix: MIAME Glossary
- Index
- Plate section
Summary
INTRODUCTION
Data analysis is seen as the largest and possibly the most important area of microarray bioinformatics. Reflecting this, there are three chapters in this book describing data analysis methods, which themselves answer three sets of scientific questions that are asked of microarray data:
Which genes are differentially expressed in one set of samples relative to another?
What are the relationships between the genes or samples being measured?
Is it possible to classify samples based on gene expression measurements?
In this chapter, we describe the methods for the first of these questions: the search for up- or down-regulated genes; Chapters 8 and 9 answer the other two questions. This chapter covers a variety of techniques, drawn from both classical statistics and more modern theory, to give a detailed account of how to analyze DNA microarray data for differentially expressed genes. We start the chapter with three examples to illustrate what we mean by the identification of differentially expressed genes.
EXAMPLE 7.1 DATA SET 7A
Samples are taken from 20 breast cancer patients, before and after a 16-week course of doxorubicin chemotherapy, and analyzed using microarrays. We wish to identify genes that are up- or down-regulated in breast cancer following that treatment.
EXAMPLE 7.2 DATA SET 7B
Bone marrow samples are taken from 27 patients suffering from acute lymphoblastic leukemia (ALL) and 11 patients suffering from acute myeloid leukemia (AML) and analyzed using Affy metrix arrays. We wish to identify the genes that are up- or downregulated in ALL relative to AML.
- Type
- Chapter
- Information
- Microarray Bioinformatics , pp. 110 - 138Publisher: Cambridge University PressPrint publication year: 2003
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