Bilkent University
Department of Computer Engineering


TCF: Tensor clustering framework on multiple-biomarker tensors for sublineage structure analysis of Mycobacterium tuberculosis complex


Cagri Ozcaglar
Rensselaer Polytechnic Institute, Troy, NY, USA

Background: Strains of Mycobacterium tuberculosis complex (MTBC) can be classified into major lineages based on their genotype. Further subdivision of major lineages into sublineages requires multiple biomarkers along with methods to combine and analyze multiple sources of information in one unsupervised learning model. Typically, spacer oligonucleotide type (spoligotype) and mycobacterial interspersed repetitive units (MIRU) are used for TB genotyping and surveillance. Here, we examine the sublineage structure of MTBC strains with multiple biomarkers simultaneously, by employing a tensor clustering framework (TCF) on multiple-biomarker tensors.

Results: Simultaneous analysis of the spoligotype and MIRU type of strains using TCF on multiple-biomarker tensors leads to coherent sublineages of major lineages with clear and distinctive spoligotype and MIRU signatures. Comparison of tensor sublineages with SpolDB4 families either supports tensor sublineages, or suggests subdivision or merging of SpolDB4 families.

Conclusions: TCF on multiple-biomarker tensors achieves simultaneous analysis of multiple biomarkers and suggest a new putative sublineage structure for each major lineage. Analysis of multiple-biomarker tensors gives insight into the sublineage structure of MTBC at the genomic level.

Bio: Cagri Ozcaglar is a Ph.D. candidate in Computer Science department at Rensselaer Polytechnic Institute. He received his B.S. in Computer Science at Bilkent University in 2006, and M.S. in Computer Science at Rensselaer Polytechnic Institute in 2008. His research interests include data mining, machine learning, multiway analysis and bioinformatics. He is currently working on building algorithmic methods for clustering and evolutionary analysis of Mycobacterium tuberculosis complex.


DATE: 03 January, 2012, Tuesday @ 13:40