A Novel Abundance-Based Algorithm for Binning Metagenomic Sequences Using l-Tuples

Abstract. Metagenomics is the study of microbial communities sampled directly from their natural environment, without prior culturing. Among the computational tools recently developed for metagenomic sequence analysis, binning tools attempt to classify all (or most) of the sequences in a metagenomic dataset into different bins (i.e., species), based on various DNA composition patterns (e.g., the tetramer frequencies) of various genomes. Composition-based binning methods, however, cannot be used to classify very short fragments, because of the substantial variation of DNA composition patterns within a single genome. We developed a novel approach (AbundanceBin) for metagenomics binning by utilizing the different abundances of species living in the same environment. AbundanceBin is an application of the Lander-Waterman model to metagenomics, which is based on the l-tuple content of the reads. AbundanceBin achieved accurate, unsupervised, clustering of metagenomic sequences into differe...

• Type: Conference
• Year: 2010
• Where: RECOMB
• Authors: Yu-Wei Wu, Yuzhen Ye
• Keywords: Computational Biology, Different Bins, DNA Composition Patterns, Metagenomic, RECOMB 2010