Nucleic Acids Research Advance Access originally published online on June 25, 2007
Nucleic Acids Research 2007 35(14):4629-4639; doi:10.1093/nar/gkm204
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Nucleic Acids Research, 2007, Vol. 35, No. 14 4629-4639
© 2007 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Genomics |
Detecting laterally transferred genes: use of entropic clustering methods and genome position
Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA 15260, USA
*To whom correspondence should be addressed. Tel: +1-412 624 4204; Fax: +1-412 624 4759; Email: bioweb{at}pitt.edu
Received January 17, 2007. Revised March 21, 2007. Accepted March 23, 2007.
Most parametric methods for detecting foreign genes in bacterial genomes use a scoring function that measures the atypicality of a gene with respect to the bulk of the genome. Genes whose features are sufficiently atypical—lying beyond a threshold value—are deemed foreign. Yet these methods fail when the range of features of donor genomes overlaps with that of the recipient genome, leading to misclassification of foreign and native genes; existing parametric methods choose threshold parameters to balance these error rates. To circumvent this problem, we have developed a two-pronged approach to minimize the misclassification of genes. First, beyond classifying genes as merely atypical, a gene clustering method based on Jensen–Shannon entropic divergence identifies classes of foreign genes that are also similar to each other. Second, genome position is used to reassign genes among classes whose composition features overlap. This process minimizes the misclassification of either native or foreign genes that are weakly atypical. The performance of this approach was assessed using artificial chimeric genomes and then applied to the well-characterized Escherichia coli K12 genome. Not only were foreign genes identified with a high degree of accuracy, but genes originating from the same donor organism were effectively grouped.
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