DNA Microarrays and Related Genomics Techniques (eBook, PDF)

Design, Analysis, and Interpretation of Experiments
Redaktion: Allison, David B.; Edwards, Jode W.; Beasley, T. Mark; Page, Grier P.

• Format: PDF

Produktbeschreibung

With contributions from distinguished experts in the field, DNA Microarrays and Related Genomics Techniques parallels the steps in conducting and analyzing a microarray experiment from conception to interpretation. This book explores critical aspects of designing a microarray experiment, including power and sample size. It assesses the validity of statistical methods and describes how to ensure the quality and integrity of data. In addition, the text discusses new methods for interpreting microarray data and examines the various issues associated with analysis. It also addresses the movement to make large high-dimensional datasets public for further analysis, and the associated methods.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 392
• Erscheinungstermin: 14. November 2005
• Englisch
• ISBN-13: 9781420028799
• Artikelnr.: 52956315

Autorenporträt

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

Inhaltsangabe

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.