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snpAIMeR: R package for evaluating ancestry informative marker contributions in non-model population diagnostics.
Vertacnik, Kim L; Vernygora, Oksana V; Dupuis, Julian R.
Afiliación
  • Vertacnik KL; Department of Entomology, University of Kentucky, Lexington, KY 40546, United States.
  • Vernygora OV; Department of Entomology, University of Kentucky, Lexington, KY 40546, United States.
  • Dupuis JR; Department of Entomology, University of Kentucky, Lexington, KY 40546, United States.
Bioinformatics ; 40(6)2024 06 03.
Article en En | MEDLINE | ID: mdl-38885407
ABSTRACT
MOTIVATION Single nucleotide polymorphism (SNP) markers are increasingly popular for population genomics and inferring ancestry for individuals of unknown origin. Because large SNP datasets are impractical for rapid and routine analysis, diagnostics rely on panels of highly informative markers. Strategies exist for selecting these markers, however, resources for efficiently evaluating their performance are limited for non-model systems.

RESULTS:

snpAIMeR is a user-friendly R package that evaluates the efficacy of genomic markers for the cluster assignment of unknown individuals. It is intended to help minimize panel size and genotyping effort by determining the informativeness of candidate diagnostic markers. Provided genotype data from individuals of known origin, it uses leave-one-out cross-validation to determine population assignment rates for individual markers and marker combinations. AVAILABILITY AND IMPLEMENTATION snpAIMeR is available on CRAN (https//CRAN.R-project.org/package=snpAIMeR).
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Polimorfismo de Nucleótido Simple Límite: Humans Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Polimorfismo de Nucleótido Simple Límite: Humans Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos