Table Of Contents:
Introduction
Bioinformatics - an emerging discipline
The building blocks of genomic information
Expression of genetic information
The need for microarrays
Summary
Microarrays
Microarrays - tools for gene expression analysis
Fabrication of microarrays
Applications of microarrays
Challenges in using microarrays in gene expression studies
Sources of variability
Summary
Image processing
Introduction
Basic elements of digital imaging
Microarray image processing
Image processing of cDNA microarrays
Summary
Elements of statistics
Introduction
Some basic terms
Elementary statistics
Probabilities
Bayes' theorem
Probability distributions
Central limit theorem
Are replicates useful?
Summary
Solved problems
Exercises
Statistical hypothesis testing
Introduction
The framework
Hypothesis testing and significance
"I do not believe God does not exist"
An algorithm for hypothesis testing
Errors in hypothesis testing
Summary
Solved problems
Classical approaches to data analysis
Introduction
Tests involving a single sample
Tests involving two samples
Summary
Exercises
Analysis of Variance - ANOVA
Introduction
One-way ANOVA
Two-way ANOVA
Quality control
Summary
Exercises
Experiment design
The concept of experiment design
Comparing varieties
Improving the production process
Principles of experimental design
Guidelines for experimental design
A short synthesis of statistical experiment designs
Some microarray specific experiment designs
Summary
Multiple comparisons
Introduction
The problem of multiple comparisons
A more precise argument
Corrections for multiple comparisons
Summary
Analysis and visualization tools
Introduction
Box plots
Gene pies
Scatter plots
Histograms
Time Series
Principal component analysis (PCA)
Summary
Cluster analysis
Introduction
Metric distances
Clustering algorithms
Summary
Data pre-processing and normalization
Introduction
General pre-processing techniques
Normalization issues specific to cDNA data
Normalization issues specific to Affymetrix data
Other approaches to the normalization of Affymetrix data
Useful pre-processing and normalization sequences
Summary
Appendix
Methods for selecting differentially regulated genes
Introduction
Criteria
Fold change
Unusual ratio
Hypothesis testing, corrections for multiple comparisons and resampling
Description
Characteristics
ANOVA
Noise sampling
Model based maximum likelihood estimation methods
Affymetrix comparison calls
Other methods
Summary
Functional analysis and biological interpretation of microarray data
Introduction
The Gene Ontology
Other related resources
Mapping lists of differentially regulated genes into biological knowledge
Onto-Express
Summary
Focused microarrays - comparison and selection
Introduction
Criteria for array selection
Onto-Compare
Some comparisons
Summary
Commercial applications
Introduction
Significance testing among groups using GeneSight
Statistical analysis of microarray data using S-PLUS and Insightful ArrayAnalyzer
SAS software for genomics
The road ahead
References