| Title |
The PhyloPythiaS Web Server for Taxonomic Assignment of Metagenome Sequences
|
|---|---|
| Published in |
PLOS ONE, June 2012
|
| DOI | 10.1371/journal.pone.0038581 |
| Pubmed ID | |
| Authors |
Kaustubh Raosaheb Patil, Linus Roune, Alice Carolyn McHardy |
| Abstract |
Metagenome sequencing is becoming common and there is an increasing need for easily accessible tools for data analysis. An essential step is the taxonomic classification of sequence fragments. We describe a web server for the taxonomic assignment of metagenome sequences with PhyloPythiaS. PhyloPythiaS is a fast and accurate sequence composition-based classifier that utilizes the hierarchical relationships between clades. Taxonomic assignments with the web server can be made with a generic model, or with sample-specific models that users can specify and create. Several interactive visualization modes and multiple download formats allow quick and convenient analysis and downstream processing of taxonomic assignments. Here, we demonstrate usage of our web server by taxonomic assignment of metagenome samples from an acidophilic biofilm community of an acid mine and of a microbial community from cow rumen. |
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X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Cameroon | 1 | 50% |
| United States | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 100% |
Mendeley demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 8 | 4% |
| Brazil | 4 | 2% |
| Germany | 3 | 2% |
| United Kingdom | 2 | 1% |
| Netherlands | 1 | <1% |
| Japan | 1 | <1% |
| Finland | 1 | <1% |
| Spain | 1 | <1% |
| Estonia | 1 | <1% |
| Other | 1 | <1% |
| Unknown | 162 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 51 | 28% |
| Student > Master | 33 | 18% |
| Researcher | 32 | 17% |
| Student > Doctoral Student | 13 | 7% |
| Student > Bachelor | 11 | 6% |
| Other | 29 | 16% |
| Unknown | 16 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 96 | 52% |
| Biochemistry, Genetics and Molecular Biology | 22 | 12% |
| Computer Science | 17 | 9% |
| Environmental Science | 8 | 4% |
| Immunology and Microbiology | 5 | 3% |
| Other | 17 | 9% |
| Unknown | 20 | 11% |