PT  - JOURNAL ARTICLE
AU  - Andries J. van der Walt
AU  - Marc W. Van Goethem
AU  - Jean-Baptiste Ramond
AU  - Thulani P. Makhalanyane
AU  - Oleg Reva
AU  - Don A. Cowan
TI  - Assembling metagenomes, one community at a time
AID  - 10.1101/120154
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 120154
4099  - http://biorxiv.org/content/early/2017/06/06/120154.short
4100  - http://biorxiv.org/content/early/2017/06/06/120154.full
AB  - Background Metagenomics allows unprecedented access to uncultured environmental microorganisms. The analysis of metagenomic sequences facilitates gene prediction and annotation, and enables the assembly of draft genomes, including uncultured members of a community. However, while several platforms have been developed for this critical step, there is currently no clear framework for the assembly of metagenomic sequence data.Results To assist with selection of an appropriate metagenome assembler we evaluated the capabilities of nine prominent assembly tools on nine publicly-available environmental metagenomes, as well as three simulated datasets. Overall, we found that SPAdes provided the largest contigs and highest N50 values across 6 of the 9 environmental datasets, followed by MEGAHIT and metaSPAdes. MEGAHIT emerged as a computationally inexpensive alternative to SPAdes, assembling the most complex dataset using less than 500 GB of RAM and within 10 hours.Conclusions We found that assembler choice ultimately depends on the scientific question, the available resources and the bioinformatic competence of the researcher. We provide a concise workflow for the selection of the best assembly tool.