Di-codon Usage for Gene Classification

Authors:
Minh N. Nguyen;Jianmin Ma;Gary B. Fogel;Jagath C. Rajapakse
Affiliations:
BioInfomatics Institute, Singapore;BioInfomatics Institute, Singapore;Natural Selection Inc. San Diego, USA;BioInformatics Research Centre, Nanyang Technological University, Singapore and Singapore-MIT Alliance, Singapore and Department of Biological Engineering, Massachusettes Institutes of Technology, ...
Venue:
PRIB '09 Proceedings of the 4th IAPR International Conference on Pattern Recognition in Bioinformatics
Year:
2009

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Abstract

Classification of genes into biologically related groups facilitates inference of their functions. Codon usage bias has been described previously as a potential feature for gene classification. In this paper, we demonstrate that di-codon usage can further improve classification of genes. By using both codon and di-codon features, we achieve near perfect accuracies for the classification of HLA molecules into major classes and sub-classes. The method is illustrated on 1,841 HLA sequences which are classified into two major classes, HLA-I and HLA-II. Major classes are further classified into sub-groups. A binary SVM using di-codon usage patterns achieved 99.95% accuracy in the classification of HLA genes into major HLA classes; and multi-class SVM achieved accuracy rates of 99.82% and 99.03% for sub-class classification of HLA-I and HLA-II genes, respectively. Furthermore, by combining codon and di-codon usages, the prediction accuracies reached 100%, 99.82%, and 99.84% for HLA major class classification, and for sub-class classification of HLA-I and HLA-II genes, respectively.