Title |
MICRA: an automatic pipeline for fast characterization of microbial genomes from high-throughput sequencing data
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Published in |
Genome Biology, December 2017
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DOI | 10.1186/s13059-017-1367-z |
Pubmed ID | |
Authors |
Ségolène Caboche, Gaël Even, Alexandre Loywick, Christophe Audebert, David Hot |
Abstract |
The increase in available sequence data has advanced the field of microbiology; however, making sense of these data without bioinformatics skills is still problematic. We describe MICRA, an automatic pipeline, available as a web interface, for microbial identification and characterization through reads analysis. MICRA uses iterative mapping against reference genomes to identify genes and variations. Additional modules allow prediction of antibiotic susceptibility and resistance and comparing the results of several samples. MICRA is fast, producing few false-positive annotations and variant calls compared to current methods, making it a tool of great interest for fully exploiting sequencing data. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United Kingdom | 5 | 19% |
France | 2 | 7% |
United States | 2 | 7% |
Taiwan | 1 | 4% |
Canada | 1 | 4% |
Italy | 1 | 4% |
New Zealand | 1 | 4% |
Spain | 1 | 4% |
Netherlands | 1 | 4% |
Other | 1 | 4% |
Unknown | 11 | 41% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 17 | 63% |
Members of the public | 8 | 30% |
Science communicators (journalists, bloggers, editors) | 2 | 7% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 66 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 18 | 27% |
Student > Ph. D. Student | 11 | 17% |
Professor | 7 | 11% |
Student > Bachelor | 5 | 8% |
Student > Master | 5 | 8% |
Other | 7 | 11% |
Unknown | 13 | 20% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 19 | 29% |
Biochemistry, Genetics and Molecular Biology | 14 | 21% |
Computer Science | 6 | 9% |
Immunology and Microbiology | 4 | 6% |
Veterinary Science and Veterinary Medicine | 2 | 3% |
Other | 6 | 9% |
Unknown | 15 | 23% |