Benchmarking computational methods for metagenomes

They are everywhere, but invisible to the naked eye. Microbes are the unseen, influential forces behind the regulation of key environmental processes such as the carbon cycle, yet most of them remain unknown. For more than a decade, the U.S. Department of Energy Joint Genome Institute (DOE JGI), a DOE Office of Science User Facility, has been enabling researchers to study uncultured microbes unable to grow in the lab, using state-of-the-art approaches such as high-throughput genomic sequencing of environmental communities (“metagenomics”) and the development of computational tools to uncover and characterize microbial communities from the environment. To tackle assembling metagenomes into a set of overlapping DNA segments that together represent a consensus region of DNA or contigs, then binning these contigs into genome bins, and finally conducting taxonomic profiling of genome bins, analysts around the world have developed an array of different computational tools, however until now there was a lack of consensus on how to evaluate their performance.