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.

Submitted: June 8, 2004 · Accepted: May 28, 2005 · Published: July 12, 2005

Recommended Citation

Purdom, Elizabeth and Holmes, Susan P. (2005) "Error Distribution for Gene Expression Data," Statistical Applications in Genetics and Molecular Biology: Vol. 4 : Iss. 1, Article 16.
Available at: http://www.bepress.com/sagmb/vol4/iss1/art16