Meta-tools for metagenomics: integrating tools for next-generation analysis
Recovering and analysing microbial genomes from metagenomes depends on a growing set of specialised software, but mixing and matching these tools together into “meta” workflows can push the boundaries of analysis even further. Here I describe the metagenomics tool ecosystem developed in the Woodcroft lab, spanning a complete analysis pipeline: community profiling, coverage estimation, metagenomic binning, genome clustering and variant calling. Building on these “baseline” tools, we have developed higher-level “meta” workflows that orchestrate multiple tools into complete pipelines—Aviary, which integrates assembly, binning, and annotation into a single reproducible workflow, and Bin Chicken, which is built on top of Aviary and SingleM to predict, ahead of time, which sample combinations are most likely to yield novel genomes. This provides the benefit of targeted co-assembly without the prohibitive expense of assembling and binning every candidate set, and has been used to recover more than 140,000 novel microbial species. I will use Bin Chicken as a case study to describe how integrating existing tools accelerated development and resolved key performance bottlenecks.
Bio
Dr Samuel Aroney is an early-career researcher working at the Centre for Microbiome Research at QUT. After completing a PhD at the University of Oxford on the motility and chemotaxis of nitrogen-fixing rhizobia, he moved into large-scale metagenomics, developing three widely used bioinformatic tools: SingleM, Bin Chicken and CoverM. SingleM and its companion web resource Sandpiper profile microbial community composition at scale, now covering over 900,000 global metagenomic samples. Bin Chicken, an efficient genome-recovery framework, has been used to recover more than 140,000 novel microbial species and expand the known bacterial tree by roughly 25%. CoverM provides fast, robust coverage and abundance calculation for genomes and contigs. He has applied these tools to genome recovery and subsequent analysis for the NSF-funded EMERGE project, studying how climate change is reshaping Arctic permafrost wetland microbiomes and their methane emissions.
