DNA Microarrays and Related Genomics Techniques: Design, Analysis, and Interpretation of Experiments
Considered highly exotic tools as recently as the late 1990s, microarrays are now ubiquitous in biological research. Traditional statistical approaches to design and analysis were not developed to handle the high-dimensional, small sample problems posed by microarrays. In just a few short years the number of statistical papers providing approaches
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DNA Microarrays and Related Genomics Techniques: Design, Analysis, and Interpretation of Experiments
Considered highly exotic tools as recently as the late 1990s, microarrays are now ubiquitous in biological research. Traditional statistical approaches to design and analysis were not developed to handle the high-dimensional, small sample problems posed by microarrays. In just a few short years the number of statistical papers providing approaches
84.99 In Stock
DNA Microarrays and Related Genomics Techniques: Design, Analysis, and Interpretation of Experiments

DNA Microarrays and Related Genomics Techniques: Design, Analysis, and Interpretation of Experiments

DNA Microarrays and Related Genomics Techniques: Design, Analysis, and Interpretation of Experiments

DNA Microarrays and Related Genomics Techniques: Design, Analysis, and Interpretation of Experiments

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Overview

Considered highly exotic tools as recently as the late 1990s, microarrays are now ubiquitous in biological research. Traditional statistical approaches to design and analysis were not developed to handle the high-dimensional, small sample problems posed by microarrays. In just a few short years the number of statistical papers providing approaches

Product Details

ISBN-13: 9781040199305
Publisher: CRC Press
Publication date: 11/14/2005
Sold by: Barnes & Noble
Format: eBook
Pages: 392
File size: 5 MB

About the Author

David B. Allison, Grier P. Page, T. Mark Beasley, Jode W. Edwards

Table of Contents

Microarray Platforms and Blood Samples. Normalization of Microarray Data. Microarray Quality Control and Assessment. Epistemological Foundations of Statistical Methods for High-Dimensional Biology. The Role of Sample Size on Measures of Uncertainty and Power. Pooling Biological Samples in Microarray Experiments. Designing Microarrays for the Analysis of Gene Expressions. Overview of Standard Clustering Approaches for Gene Microarray Data Analysis. Cluster Stability. Dimensionality Reduction and Discrimination. Modeling Affymetrix Data at the Probe Level. Parametric Linear Models. The Use of Nonparametric Procedures in the Statistical Analysis of Microarray Data. Bayesian Analysis of Microarray Data. False Discovery Rate and Multiple Comparison Procedures. Using Standards to Facilitate Interoperation of Heterogeneous Microarray Databases and Analytic Tools. Post-Analysis Interpretation: What Do I Do with This Gene List? Combining High Dimensional Biological Data to Study Complex Diseases and Quantitative Traits.
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