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BIOINFORMATICS
2010

Analyzing taxonomic classification using extensible Markov models

13 years 11 months ago
Analyzing taxonomic classification using extensible Markov models
Motivation: As next generation sequencing is rapidly adding new genomes, their correct placement in the taxonomy needs verification. However, the current methods for confirming classification of a taxon or suggesting revision for a potential misplacement relies on computationally intense multi-sequence alignment followed by an iterative adjustment of the distance matrix. Due to intra-heterogeneity issues with the 16S rRNA marker, no classifier is available for sub-genus level that could readily suggest a classification for a novel 16S rRNA sequence. Metagenomics further complicates the issue by generating fragmented 16S rRNA sequences. This paper proposes a novel alignment-free method for representing the microbial profiles using Extensible Markov Models (EMM) with an extended Karlin-Altschul statistical framework similar to the classic alignment paradigm. We propose a Log Odds (LOD) score classifier based on Gumbel difference distribution that confirms correct classifications with st...
Rao M. Kotamarti, Michael Hahsler, Douglas Raiford
Added 08 Dec 2010
Updated 08 Dec 2010
Type Journal
Year 2010
Where BIOINFORMATICS
Authors Rao M. Kotamarti, Michael Hahsler, Douglas Raiford, Monnie McGee, Margaret H. Dunham
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