Abstract
We have developed an empirical Bayes methodology for gene expression data to account for replicate arrays, multiple conditions, and a range of modeling assumptions. The methodology is implemented in an R library called EBarrays. Functions in the library calculate posterior probabilities of patterns of differential expression across multiple conditions. This chapter provides an overview of the methodology and its implementation in EBarrays.
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© 2003 Springer-Verlag New York, Inc.
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Newton, M.A., Kendziorski, C. (2003). Parametric Empirical Bayes Methods for Microarrays. In: Parmigiani, G., Garrett, E.S., Irizarry, R.A., Zeger, S.L. (eds) The Analysis of Gene Expression Data. Statistics for Biology and Health. Springer, New York, NY. https://doi.org/10.1007/0-387-21679-0_11
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DOI: https://doi.org/10.1007/0-387-21679-0_11
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-95577-3
Online ISBN: 978-0-387-21679-9
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