Research

P-value based visualization of codon usage data

Peter Meinicke¹ , Thomas Brodag² , Wolfgang Florian Fricke³ and Stephan Waack²

¹  Abteilung Bioinformatik, Institut für Mikrobiologie und Genetik, Georg-August-Universität Göttingen, Goldschmidtstr. 1, 37077 Göttingen, Germany

²  Institut für Numerische und Angewandte Mathematik, Universität Göttingen, Lotzestr. 16, 37083 Göttingen, Germany

³  Göttingen Genomics Laboratory, Universität Göttingen, Grisebachstr. 8, 37077 Göttingen, Germany

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Algorithms for Molecular Biology 2006, 1:10doi:10.1186/1748-7188-1-10

Published:	29 June 2006

Abstract

Two important and not yet solved problems in bacterial genome research are the identification of horizontally transferred genes and the prediction of gene expression levels. Both problems can be addressed by multivariate analysis of codon usage data. In particular dimensionality reduction methods for visualization of multivariate data have shown to be effective tools for codon usage analysis. We here propose a multidimensional scaling approach using a novel similarity measure for codon usage tables. Our probabilistic similarity measure is based on P-values derived from the well-known chi-square test for comparison of two distributions. Experimental results on four microbial genomes indicate that the new method is well-suited for the analysis of horizontal gene transfer and translational selection. As compared with the widely-used correspondence analysis, our method did not suffer from outlier sensitivity and showed a better clustering of putative alien genes in most cases.