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Statistical Applications in Genetics and Molecular Biology

Editor-in-Chief: Stumpf, Michael P.H.

6 Issues per year


IMPACT FACTOR 2013: 1.055
Rank 48 out of 119 in category Statistics & Probability in the 2013 Thomson Reuters Journal Citation Report/Science Edition

SCImago Journal Rank (SJR): 0.875
Source Normalized Impact per Paper (SNIP): 0.540

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Error Distribution for Gene Expression Data

Elizabeth Purdom1 / Susan P Holmes2

1Stanford University

2Stanford University

Citation Information: Statistical Applications in Genetics and Molecular Biology. Volume 4, Issue 1, ISSN (Online) 1544-6115, DOI: 10.2202/1544-6115.1070, July 2005

Publication History

Published Online:
2005-07-12

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

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