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2011 | OriginalPaper | Chapter

8. Experimental Designs and ANOVA for Microarray Data

Authors : Richard E. Kennedy, Xiangqin Cui

Published in: Handbook of Statistical Bioinformatics

Publisher: Springer Berlin Heidelberg

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Abstract

Microarray experiments are complex, multistep processes that represent a considerable investment of time and resources. Proper experimental design and analysis are critical to the success of a microarray experiment, and must be considered early in the planning of the experiment. Many aspects of experimental design from low-throughput experiments, such as randomization, replication, and blocking, remain applicable to microarray experiments as well. Similarly, the analysis of variance (ANOVA) remains a valid approach for analyzing data from most microarray experiments. However, the high-dimensional nature of microarrays introduces additional considerations into the design and analysis. This chapter provides an overview of the unique statistical challenges presented by microarrays and describes computational methods for implementing these statistical algorithms.

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Title: Experimental Designs and ANOVA for Microarray Data
Authors: Richard E. Kennedy
Xiangqin Cui
Publisher: Springer Berlin Heidelberg
Book: Handbook of Statistical Bioinformatics
Print ISBN: 978-3-642-16344-9

Electronic ISBN: 978-3-642-16345-6

Copyright Year: 2011
DOI: https://doi.org/10.1007/978-3-642-16345-6_8

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