DNA Microaray Technology and Data Analysis in Cancer Research 1st Edition by Shaoguang Li, Dongguang Li 9812790453 9789812790453

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ISBN 10:  9812790453 

ISBN 13: 9789812790453

Author:  Shaoguang Li, Dongguang Li 

DNA microarray technology has become a useful technique in gene expression analysis for the development of new diagnostic tools and for the identification of disease genes and therapeutic targets for human cancers. Appropriate control for DNA microarray experiment and reliable analysis of the array data are key to performing the assay and utilizing the data correctly. The most difficult challenge has been the lack of a powerful method to analyze the data for all genes (more than 30,000 genes) simultaneously and to use the microarray data in a decision-making process. In this book, the authors describe DNA microarray technology and data analysis by pointing out current advantages and disadvantages of the technique and available analytical methods. Crucially, new ideas and analytical methods based on the authors’ own experience in DNA microarray study and analysis are introduced. It is believed that this new way of interpreting and analyzing microarray data will bring us closer to success in decision-making using the information obtained through the DNA microarray technology.

DNA Microaray Technology and Data Analysis in Cancer Research 1st Table of contents:

Chapter 1 DNA Microarray Technology
1.1. Experimental Procedure
1.2. Experimental Design
1.3. Quality Control
1.4. Interpretation of DNA Microarray Data
1.5. Advantages and Disadvantages
Chapter 2 Applications of DNA Microarray Technology in Cancer Research
2.1 Solid Tumors
2.2 Blood Cancers
2.3. Our DNA Microarray Study Using Mouse Model of BCR-ABL-Induced Leukemia
2.3.1. Leukemia mouse model study
2.3.1.1. Rationale
2.3.1.2. Experimental design
2.3.1.3. Results
2.3.2. Cell line study
Chapter 3 Current Analytical Methods of DNA Microarray Data
3.1. Experimental Design
3.2. Method
3.2.1. Robust multi-chip averaging (RMA)
3.2.2. iterPLIER
3.3 Quality Control Diagnostics
3.3.1. Saturation
3.3.1.1. Raw intensities for arrays containing a saturated probe
3.3.2. Transformed intensities across arrays
3.3.3. Normalized intensities across arrays
3.3.4. Scatterplot of normalized intensities
3.3.5. Average MA plot of normalized intensities
3.4. Statistical Analysis
3.4.1. Analysis of variance (ANOVA) model
3.4.2. Contrasts
3.4.2.1. Fs permutation p-value distribution
3.4.2.2. p- and q-value summary
3.4.2.3. Volcano plot
3.5. Coefficient of Variation Analysis
Chapter 4 A Novel Method for DNA Microarray Data Analysis: SDL Global Optimization Method
4.1. Research Subjects
4.2. Experimental Design
4.2.1. Rationale
4.3. Fold Change Analysis
4.4. More Information on SDL Global Optimization
4.4.1. Genetic algorithms (GAs)
4.4.2. SDL global optimization algorithms
Chapter 5 Applications of the SDL Global Optimization Method in DNA Microarray Data Analysis
5.1. Leukemia Cell Line Study
5.1.1. Introduction
5.1.2. Datasets
5.1.3. Analysis strategies
5.1.3.1. Data sorting based on 20 chromosome groups (Fig. 5.1)
5.1.3.2. Dynamics of gene expression
5.1.3.3. Absolute difference between P190 and P210 (Fig. 5.3)
5.1.3.4. Prefiltering process (gene selection)
5.1.3.5. Grouping genes based on the deviations
5.1.3.6. Analyzing the selected 8832 genes
5.1.3.7. The second sharp jump of deviations
5.1.3.8. Top 13 genes which are most differentially expressed across P190 and P210
5.1.4. Discussion and conclusion
5.2. Analyses of Publicly Available Human Microarray Data
5.2.1. Introduction
5.2.2. Datasets
5.2.2.1. Colon data
5.2.2.2. Leukemia data
5.3. Overall Methodology
5.3.1. Orthogonal arrays (OAs) and sampling procedure
5.3.2. Objective function
5.3.3. Search space reduction for global search
5.3.4. Mathematical form of SDL optimization
5.3.4.1. Definition of local minima
5.3.4.2. Definition of global minima
5.3.4.3. How to find the global minima
5.3.5. Multi-subset class predictor
5.3.6. Validation (predicting through a voting mechanism)
5.4. Experimental Results
5.5. Discussion
5.6. Conclusion
Chapter 6 General Discussion and Future Directions
References

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Tags: DNA Microaray, Technology, Data Analysis, Cancer Research, Shaoguang Li, Dongguang Li