Metagenomic binning through low-density hashing.

ABSTRACT:

Motivation

Vastly greater quantities of microbial genome data are being generated where environmental samples mix together the DNA from many different species. Here, we present Opal for metagenomic binning, the task of identifying the origin species of DNA sequencing reads. We introduce 'low-density' locality sensitive hashing to bioinformatics, with the addition of Gallager codes for even coverage, enabling quick and accurate metagenomic binning.

Results

On public benchmarks, Opal halves the error on precision/recall (F1-score) as compared with both alignment-based and alignment-free methods for species classification. We demonstrate even more marked improvement at higher taxonomic levels, allowing for the discovery of novel lineages. Furthermore, the innovation of low-dens

SUBMITTER: Luo Y 

PROVIDER: S-EPMC6330020 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature