
Microarray Technology in Practice
1st Edition
Description
Using chips composed of thousands of spots, each with the capability of holding DNA molecules corresponding to a given gene, DNA microarray technology has enabled researchers to measure simultaneously gene expression across the genome. As with other large-scale genomics approaches, microarray technologies are broadly applicable across disciplines of life and biomedical sciences, but remain daunting to many researchers. This guide is designed to demystify the technology and inform more biologists about this critically important experimental technique.
Key Features
- Cohesive overview of the technology and available platforms, followed by detailed discussion of experimental design and analysis of microarray experiments
- Up-to-date description of normalization methods and current methods for sample amplification and labeling
- Deep focus on oligonucleotide design, printing, labeling and hybridization, data acquisition, normalization, and meta-analysis
- Additional uses of microarray technology such as ChIP (chromatin immunoprecipitation) with hybridization to DNA arrays, microarray-based comparative genomic hybridization (CGH), and cell and tissue arrays
Readership
Life science professionals and graduate students
Table of Contents
Contents
- What are microarrays? A. The basics
Designing and producing a microarray A. Platform options B. Oligonucleotide design C. Whole genome or boutique arrays D. The problems of multiple testing E. Array layout F. Quality assessment
Sample collection and labelling A. RNA extraction B. Quality assessment C. Direct labelling techniques D. Indirect labelling techniques E. End labelling techniques F. Amplification techniques G. Hybridization
Data acquisition A. Scanners B. Image acquisition C. Multiple scans and data merging D. Finding spots E. Background measurement G. Quality control basics
Experimental Design and Data Normalisation A. Experimental design B. Why normalize? C. Unwanted signal variation D. Common normalization approaches E. Data transformation F. Dealing with ‘S’-shaped trends G. Replicates and spatial detrending H. Normalization of single channel arrays
Meta analysis A. Data filtering B. Screening for differentially expressed genes C. Hierarchical clustering D. Other clustering techniques E. Components analysis F. Prediction tools
Data annotation, storage and submission A. Functional data annotation
B. Microarray databases C. Public repositoriesApplications in health & disease A. Mal
Details
- No. of pages:
- 464
- Language:
- English
- Copyright:
- © Academic Press 2009
- Published:
- 6th October 2008
- Imprint:
- Academic Press
- eBook ISBN:
- 9780080919768
- Paperback ISBN:
- 9780123725165
About the Author
Steve Russell
Affiliations and Expertise
University of Cambridge, UK
Lisa Meadows
Affiliations and Expertise
University of Cambridge, London UK
Roslin Russell
Affiliations and Expertise
University of Cambridge, London UK