Methods in Microarray Normalization discusses the use of early normalization techniques for new profiling methods and includes strategies for assessing the utility of various normalization algorithms.

Methods in Microarray Normalization:

• Explains how pathway analysis, feature selection, and classification results can be used for new profiling techniques
• Reviews the latest advances in peptide, glyco, antibody, expression, and SNP microarrays
• Examines the latest methods for pooling genomic samples to identify disease-specific SNPs
• Illustrates the impact of data normalization on clinical outcomes based on the applications of commercial products such as MammaPrint and OncoTypeDX
• Lists open-source molecular profiling normalization algorithms available and where to access them

Methods in Microarray Normalization provides scientists with a complete resource on the most effective tools available for maximizing microarray data in biochemical research.

Contents

1. A Comprehensive Analysis of the Effect of Microarray Data Preprocessing Methods on Differentially Expressed Transcript Selection
2. Differentiation Detection in Microarray Normalization
3. Preprocessing and Normalization for Affymetrix GeneChip Expression Microarrays
4. Spatial Detrending and Normalization Methods for Two-Channel DNA and Protein Microarray Data
5. A Survey of cDNA Microarray Normalization and a Comparison by k-NN Classification
6. Technical Variation in Modeling the Joint Expression of Several Genes
7. Biological Interpretation for Microarray Normalization Selection
8. Methodology of Functional Analysis for Omics Data Normalization
9. Exon Array Analysis for the Detection of Alternative Splicing
10. Normalization of Array CGH Data
11. SNP Array-Based Analysis for Detection of Chromosomal Aberrations and Copy Number Variations

Index

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