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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Genetic fingerprinting of salmon louse (Lepeophtheirus salmonis) populations in the North-East Atlantic using a random forest classification approach
|
|---|---|
| Published in |
Scientific Reports, January 2018
|
| DOI | 10.1038/s41598-018-19323-z |
| Pubmed ID | |
| Authors |
A. Jacobs, M. De Noia, K. Praebel, Ø. Kanstad-Hanssen, M. Paterno, D. Jackson, P. McGinnity, A. Sturm, K. R. Elmer, M. S. Llewellyn |
| Abstract |
Caligid sea lice represent a significant threat to salmonid aquaculture worldwide. Population genetic analyses have consistently shown minimal population genetic structure in North Atlantic Lepeophtheirus salmonis, frustrating efforts to track louse populations and improve targeted control measures. The aim of this study was to test the power of reduced representation library sequencing (IIb-RAD sequencing) coupled with random forest machine learning algorithms to define markers for fine-scale discrimination of louse populations. We identified 1286 robustly supported SNPs among four L. salmonis populations from Ireland, Scotland and Northern Norway. Only weak global structure was observed based on the full SNP dataset. The application of a random forest machine-learning algorithm identified 98 discriminatory SNPs that dramatically improved population assignment, increased global genetic structure and resulted in significant genetic population differentiation. A large proportion of SNPs found to be under directional selection were also identified to be highly discriminatory. Our data suggest that it is possible to discriminate between nearby L. salmonis populations given suitable marker selection approaches, and that such differences might have an adaptive basis. We discuss these data in light of sea lice adaption to anthropogenic and environmental pressures as well as novel approaches to track and predict sea louse dispersal. |
X Demographics
The data shown below were collected from the profiles of 20 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 5 | 25% |
| United States | 2 | 10% |
| Chile | 1 | 5% |
| Canada | 1 | 5% |
| Ireland | 1 | 5% |
| Norway | 1 | 5% |
| Germany | 1 | 5% |
| Unknown | 8 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 11 | 55% |
| Scientists | 9 | 45% |
Mendeley readers
The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 81 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 22 | 27% |
| Student > Master | 14 | 17% |
| Researcher | 12 | 15% |
| Student > Bachelor | 7 | 9% |
| Other | 3 | 4% |
| Other | 10 | 12% |
| Unknown | 13 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 32 | 40% |
| Biochemistry, Genetics and Molecular Biology | 11 | 14% |
| Environmental Science | 6 | 7% |
| Unspecified | 3 | 4% |
| Neuroscience | 2 | 2% |
| Other | 7 | 9% |
| Unknown | 20 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 September 2018.
All research outputs
#2,676,215
of 23,577,761 outputs
Outputs from Scientific Reports
#22,818
of 127,567 outputs
Outputs of similar age
#62,394
of 444,090 outputs
Outputs of similar age from Scientific Reports
#739
of 4,003 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 127,567 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.4. This one has done well, scoring higher than 82% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 444,090 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 4,003 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.