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2013 IEEE International Conference on Bioinformatics and Biomedicine (2009)
Washington, D.C., USA
Nov. 1, 2009 to Nov. 4, 2009
ISBN: 978-0-7695-3885-3
pp: 338-343
ABSTRACT
Abstract—We present a novel Bayesian network (BN) to classify strains of Mycobacterium tuberculosis Complex (MTBC) into six major genetic lineages using mycobacterial interspersed repetitive units (MIRUs), a high-throughput biomarker. MTBC is the causative agent of tuberculosis (TB), which remains one of the leading causes of disease and morbidity world-wide. DNA fingerprinting methods such as MIRU are key components of modern TB control and tracking. The BN achieves high accuracy on four large MTBC genotype collections consisting of over 4700 distinct 12-loci MIRU genotypes. The BN captures distinct MIRU signatures associated with each lineage, explaining the excellent performance of the BN. The errors in the BN support the need for additional biomarkers such as the expanded 24-loci MIRU used in CDC genotyping labs since May 2009. The conditional independence assumption of each locus given the lineage makes the BN easily extensible to additional MIRU loci and other biomarkers.
INDEX TERMS
tuberculosis, MIRU-VNTR, Bayesian network, lineages
CITATION
Kristin P. Bennett, Amina Shabbeer, Minoo Aminian, "Determination of Major Lineages of Mycobacterium tuberculosis Complex Using Mycobacterial Interspersed Repetitive Units", 2013 IEEE International Conference on Bioinformatics and Biomedicine, vol. 00, no. , pp. 338-343, 2009, doi:10.1109/BIBM.2009.86
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