Metagenomics Binning of Long Reads Using Read-Overlap Graphs

Abstract

Metagenomics sequencing enables the direct study of microbial communities revealing important information such as taxonomy and relative abundance of species. Metagenomics binning facilitates the separation of these genetic materials into different taxonomic groups. Moving from second-generation sequencing to third-generation sequencing techniques enables the binning of reads before assembly thanks to the increased read lengths. The limited number of long-read binning tools that exist, still suffer from unreliable coverage estimation for individual long reads and face challenges in recovering low-abundance species. In this paper, we present a novel binning approach to bin long reads using the read-overlap graph. The read-overlap graph (1) enables a fast and reliable estimation of the coverage of individual long reads; (2) allows to incorporate the overlapping information between reads into the binning process; (3) facilitates a more uniform sampling of long reads across species of varying abundances. Experimental results show that our new binning approach produces better binning results of long reads and results in better assemblies especially for recovering low abundant species. The source code and a functional Google Colab Notebook are available at https://www.github.com/anuradhawick/oblr.