Title |
Assembling metagenomes, one community at a time
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Published in |
BMC Genomics, July 2017
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DOI | 10.1186/s12864-017-3918-9 |
Pubmed ID | |
Authors |
Andries Johannes van der Walt, Marc Warwick van Goethem, Jean-Baptiste Ramond, Thulani Peter Makhalanyane, Oleg Reva, Don Arthur Cowan |
Abstract |
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. 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. 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. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 9 | 19% |
France | 3 | 6% |
United Kingdom | 3 | 6% |
South Africa | 3 | 6% |
Canada | 2 | 4% |
Chile | 1 | 2% |
Portugal | 1 | 2% |
Mexico | 1 | 2% |
Spain | 1 | 2% |
Other | 9 | 19% |
Unknown | 15 | 31% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 32 | 67% |
Members of the public | 16 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 4 | 1% |
Australia | 2 | <1% |
Netherlands | 1 | <1% |
Denmark | 1 | <1% |
United Kingdom | 1 | <1% |
Unknown | 381 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 89 | 23% |
Researcher | 75 | 19% |
Student > Master | 64 | 16% |
Student > Bachelor | 35 | 9% |
Student > Doctoral Student | 14 | 4% |
Other | 47 | 12% |
Unknown | 66 | 17% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 120 | 31% |
Biochemistry, Genetics and Molecular Biology | 89 | 23% |
Environmental Science | 29 | 7% |
Immunology and Microbiology | 26 | 7% |
Computer Science | 14 | 4% |
Other | 35 | 9% |
Unknown | 77 | 20% |