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Rank and Order: Evaluating the Performance of SNPs for Individual Assignment in a Non-Model Organism

Overview of attention for article published in PLOS ONE, November 2012
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Title
Rank and Order: Evaluating the Performance of SNPs for Individual Assignment in a Non-Model Organism
Published in
PLOS ONE, November 2012
DOI 10.1371/journal.pone.0049018
Pubmed ID
Authors

Caroline G. Storer, Carita E. Pascal, Steven B. Roberts, William D. Templin, Lisa W. Seeb, James E. Seeb

Abstract

Single nucleotide polymorphisms (SNPs) are valuable tools for ecological and evolutionary studies. In non-model species, the use of SNPs has been limited by the number of markers available. However, new technologies and decreasing technology costs have facilitated the discovery of a constantly increasing number of SNPs. With hundreds or thousands of SNPs potentially available, there is interest in comparing and developing methods for evaluating SNPs to create panels of high-throughput assays that are customized for performance, research questions, and resources. Here we use five different methods to rank 43 new SNPs and 71 previously published SNPs for sockeye salmon: F(ST), informativeness (I(n)), average contribution to principal components (LC), and the locus-ranking programs BELS and WHICHLOCI. We then tested the performance of these different ranking methods by creating 48- and 96-SNP panels of the top-ranked loci for each method and used empirical and simulated data to obtain the probability of assigning individuals to the correct population using each panel. All 96-SNP panels performed similarly and better than the 48-SNP panels except for the 96-SNP BELS panel. Among the 48-SNP panels, panels created from F(ST), I(n), and LC ranks performed better than panels formed using the top-ranked loci from the programs BELS and WHICHLOCI. The application of ranking methods to optimize panel performance will become more important as more high-throughput assays become available.

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Mendeley readers

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The data shown below were compiled from readership statistics for 94 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Portugal 2 2%
United States 2 2%
Chile 1 1%
Germany 1 1%
Canada 1 1%
Israel 1 1%
Unknown 86 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 21%
Researcher 18 19%
Student > Master 14 15%
Student > Bachelor 8 9%
Other 6 6%
Other 22 23%
Unknown 6 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 56 60%
Biochemistry, Genetics and Molecular Biology 13 14%
Environmental Science 6 6%
Veterinary Science and Veterinary Medicine 1 1%
Business, Management and Accounting 1 1%
Other 5 5%
Unknown 12 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 28 November 2012.
All research outputs
#18,321,703
of 22,687,320 outputs
Outputs from PLOS ONE
#153,900
of 193,653 outputs
Outputs of similar age
#214,039
of 275,819 outputs
Outputs of similar age from PLOS ONE
#3,419
of 4,682 outputs
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