Classification of Metagenomic Sequences Using Markov Chain Structure

• Activity Number: 254
• Type: Contributed
• Date/Time: Monday, August 10, 2015 : 2:00 PM to 3:50 PM
• Sponsor: Biometrics Section
• Author(s): Chen Gao* and Cui Xinping
• Companies: UC Riverside and UC Riverside
• Keywords: metagenomics ; Markov chain ; classification ; bioinformatics

Abstract

Metagenomics is the study of genomes of multiple species from environmental samples. Successful metagenomic projects provide a deeper insight into the microbial world. The two primary goals of metagenomics are to develop a consensus of what populations of microorganisms are present (a horizontal screen) and then to identify what roles each microorganism has within a specific environment (a vertical characterization). Ideally, we want to identify complete genomic sequences of all organisms present in a sample. Most recently developed binning methods are based on the l-tuples frequencies which ignores the genomes composition patterns. Instead of only considering the frequencies of l-tuples, we incorporate Markov chain structure to improve the classification accuracy.