A sequential naive Bayes classifier for DNA barcodes

作者：Anderson Michael P^*; Dubnicka Suzanne R

来源：Statistical Applications in Genetics and Molecular Biology, 2014, 13(4): 423-434.

DOI：10.1515/sagmb-2013-0025

• Naive Bayes classifier
• DNA barcoding
• phylogenetic analysis
• sequential analysis
• species classification
• species discovery

DNA barcodes are short strands of 255-700 nucleotide bases taken from the cytochrome c oxidase subunit 1 (COI) region of the mitochondrial DNA. It has been proposed that these barcodes may be used as a method of differentiating between biological species. Current methods of species classification utilize distance measures that are heavily dependent on both evolutionary model assumptions as well as a clearly defined "gap" between intra-and interspecies variation. Such distance measures fail to measure classification uncertainty or to indicate how much of the barcode is necessary for classification. We propose a sequential naive Bayes classifier for species classification to address these limitations. The proposed method is shown to provide accurate species-level classification on real and simulated data. The method proposed here quantifies the uncertainty of each classification and addresses how much of the barcode is necessary.

• 出版日期2014-8