Title |
Standardized benchmarking in the quest for orthologs
|
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Published in |
Nature Methods, April 2016
|
DOI | 10.1038/nmeth.3830 |
Pubmed ID | |
Authors |
Adrian M Altenhoff, Brigitte Boeckmann, Salvador Capella-Gutierrez, Daniel A Dalquen, Todd DeLuca, Kristoffer Forslund, Jaime Huerta-Cepas, Benjamin Linard, Cécile Pereira, Leszek P Pryszcz, Fabian Schreiber, Alan Sousa da Silva, Damian Szklarczyk, Clément-Marie Train, Peer Bork, Odile Lecompte, Christian von Mering, Ioannis Xenarios, Kimmen Sjölander, Lars Juhl Jensen, Maria J Martin, Matthieu Muffato, Toni Gabaldón, Suzanna E Lewis, Paul D Thomas, Erik Sonnhammer, Christophe Dessimoz |
Abstract |
Achieving high accuracy in orthology inference is essential for many comparative, evolutionary and functional genomic analyses, yet the true evolutionary history of genes is generally unknown and orthologs are used for very different applications across phyla, requiring different precision-recall trade-offs. As a result, it is difficult to assess the performance of orthology inference methods. Here, we present a community effort to establish standards and an automated web-based service to facilitate orthology benchmarking. Using this service, we characterize 15 well-established inference methods and resources on a battery of 20 different benchmarks. Standardized benchmarking provides a way for users to identify the most effective methods for the problem at hand, sets a minimum requirement for new tools and resources, and guides the development of more accurate orthology inference methods. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 9 | 16% |
Switzerland | 5 | 9% |
Germany | 4 | 7% |
United Kingdom | 4 | 7% |
Spain | 4 | 7% |
Japan | 3 | 5% |
France | 2 | 4% |
Taiwan | 1 | 2% |
Denmark | 1 | 2% |
Other | 4 | 7% |
Unknown | 19 | 34% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 29 | 52% |
Members of the public | 26 | 46% |
Science communicators (journalists, bloggers, editors) | 1 | 2% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 4 | <1% |
Spain | 4 | <1% |
Germany | 3 | <1% |
Switzerland | 2 | <1% |
United Kingdom | 2 | <1% |
France | 1 | <1% |
Czechia | 1 | <1% |
Canada | 1 | <1% |
Finland | 1 | <1% |
Other | 4 | <1% |
Unknown | 386 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 102 | 25% |
Student > Ph. D. Student | 98 | 24% |
Student > Master | 48 | 12% |
Student > Bachelor | 35 | 9% |
Professor | 19 | 5% |
Other | 60 | 15% |
Unknown | 47 | 11% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 174 | 43% |
Biochemistry, Genetics and Molecular Biology | 109 | 27% |
Computer Science | 28 | 7% |
Immunology and Microbiology | 8 | 2% |
Environmental Science | 6 | 1% |
Other | 21 | 5% |
Unknown | 63 | 15% |