Flow Cytometry Data Analysis
Basic Concepts and Statistics
£44.99
- Author: James V. Watson, University of Cambridge
- Date Published: September 2005
- availability: Available
- format: Paperback
- isbn: 9780521019705
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Flow cytometry is now well established in research laboratories and is gaining increasing use in clinical medicine and pathology. The technique enables multiple simultaneous light scatter and fluorescence measurements to be made at the individual cell level at very rapid rates and results in very large quantities of data being collected. Data, however, is just a series of numbers which have to be converted to information which, in turn, must be shown to have meaning. This is the most important single aspect of flow cytometry but it has received relatively little attention. One of the frequently voiced advantages of the technology is that it produces 'good statistics' because large numbers of cells have been analysed. However, it is not very often that confidence limits are placed on results, hence the reader has little or no feel for the inherent variability in the information produced. This book covers very basic number handling techniques, regression analysis, probability functions, statistical tests and methods of analysing dynamic processes. All those who use flow cytometry in their research will find this book an invaluable guide to interpreting the data produced by flow cytometers.
Read more- An excellent reminder for all who wish to be reminded of basic statistical procedures and principles in relation to flow cytometry
- Of interest to a wide variety of individuals - students, laboratory technicians and professionals
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×Product details
- Date Published: September 2005
- format: Paperback
- isbn: 9780521019705
- length: 300 pages
- dimensions: 230 x 155 x 19 mm
- weight: 0.483kg
- contains: 139 b/w illus. 41 tables
- availability: Available
Table of Contents
1. Introduction
2. Fundamental concepts
3. Probability functions
4. Significance testing and fit criteria
5. Regression analysis
6. Flow cytometric sources of variation
7. Immunofluorescence data
8. DNA histogram analysis
9. Cell cycle kinetics
10. Dynamic cellular events
11. Multi-variant analysis primer
12. Epilogue
Appendices
References
Index.
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