Error Distribution for Gene Expression Data

Purdom Elizabeth and Holmes Susan P
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Purdom Elizabeth: Stanford University
Holmes Susan P: Stanford University

Statistical Applications in Genetics and Molecular Biology, 2005, vol. 4, issue 1, 35

Abstract: We present a new instance of Laplace's second Law of Errors and show how it can be used in the analysis of data from microarray experiments. This error distribution is shown to fit microarray expression data much better than a normal distribution. The use of this distribution in a parametric bootstrap leads to more powerful tests as we show that the t-test is conservative in this setting. We propose a biological explanations for this distribution based on the Pareto distribution of the variables used to compute the log ratios.

Keywords: Assymetric Laplace; Gene Expression; Error Distribution; Laplace (search for similar items in EconPapers)
Date: 2005
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Citations: View citations in EconPapers (16)

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DOI: 10.2202/1544-6115.1070

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