title: Rank and order: evaluating the performance of SNPs for individual assignment in a non-model organism.
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.
authors.affiliation: School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA, USA.
authors.forename: Caroline G
authors.initials: CG
authors.lastname: Storer
authors.forename: Carita E
authors.initials: CE
authors.lastname: Pascal
authors.forename: Steven B
authors.initials: SB
authors.lastname: Roberts
authors.forename: William D
authors.initials: WD
authors.lastname: Templin
authors.forename: Lisa W
authors.initials: LW
authors.lastname: Seeb
authors.forename: James E
authors.initials: JE
authors.lastname: Seeb
mesh_terms: D000413:Alaska; D000818:Animals; D056426:Genetic Loci / Q000235:genetics; D005843:Geography; D006579:Heterozygote; D023421:Models, Animal; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D025341:Principal Component Analysis; D011336:Probability; D015203:Reproducibility of Results; D012474:Salmon / Q000235:genetics*; D018401:Sample Size; D013048:Specimen Handling; D018709:Statistics, Nonparametric