Title |
Mash: fast genome and metagenome distance estimation using MinHash
|
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Published in |
Genome Biology, June 2016
|
DOI | 10.1186/s13059-016-0997-x |
Pubmed ID | |
Authors |
Brian D. Ondov, Todd J. Treangen, Páll Melsted, Adam B. Mallonee, Nicholas H. Bergman, Sergey Koren, Adam M. Phillippy |
Abstract |
Mash extends the MinHash dimensionality-reduction technique to include a pairwise mutation distance and P value significance test, enabling the efficient clustering and search of massive sequence collections. Mash reduces large sequences and sequence sets to small, representative sketches, from which global mutation distances can be rapidly estimated. We demonstrate several use cases, including the clustering of all 54,118 NCBI RefSeq genomes in 33 CPU h; real-time database search using assembled or unassembled Illumina, Pacific Biosciences, and Oxford Nanopore data; and the scalable clustering of hundreds of metagenomic samples by composition. Mash is freely released under a BSD license ( https://github.com/marbl/mash ). |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 45 | 31% |
United Kingdom | 13 | 9% |
Germany | 5 | 3% |
France | 5 | 3% |
Netherlands | 4 | 3% |
Canada | 4 | 3% |
Spain | 3 | 2% |
China | 2 | 1% |
Sweden | 2 | 1% |
Other | 20 | 14% |
Unknown | 40 | 28% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 92 | 64% |
Members of the public | 50 | 35% |
Science communicators (journalists, bloggers, editors) | 1 | <1% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 14 | <1% |
United Kingdom | 6 | <1% |
Germany | 5 | <1% |
Canada | 5 | <1% |
Brazil | 3 | <1% |
France | 3 | <1% |
Sweden | 2 | <1% |
Norway | 2 | <1% |
India | 1 | <1% |
Other | 8 | <1% |
Unknown | 1733 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 402 | 23% |
Researcher | 325 | 18% |
Student > Master | 231 | 13% |
Student > Bachelor | 180 | 10% |
Student > Doctoral Student | 77 | 4% |
Other | 211 | 12% |
Unknown | 356 | 20% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 479 | 27% |
Biochemistry, Genetics and Molecular Biology | 433 | 24% |
Computer Science | 146 | 8% |
Immunology and Microbiology | 95 | 5% |
Environmental Science | 42 | 2% |
Other | 161 | 9% |
Unknown | 426 | 24% |