snpAIMeR: R package for evaluating ancestry informative marker contributions in non-model population diagnostics

Kim L. Vertacnik; Oksana V. Vernygora; Julian R. Dupuis

doi:10.1093/bioinformatics/btae377

snpAIMeR: R package for evaluating ancestry informative marker contributions in non-model population diagnostics

Kim L. Vertacnik
, Oksana V. Vernygora
, Julian R. Dupuis

Research output: Contribution to journal › Article › peer-review

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.

Original language	English
Article number	btae377
Journal	Bioinformatics
Volume	40
Issue number	6
DOIs	https://doi.org/10.1093/bioinformatics/btae377
State	Published - Jun 1 2024

Bibliographical note

Publisher Copyright:
© 2024 The Author(s). Published by Oxford University Press.

Funding

This work has been supported by the United States Department of Agriculture-National Institute of Food and Agriculture-Agriculture and Food Research Initiative [2020–67013-30978]; United States Department of Agriculture-Animal and Plant Health Inspection Service-Plant Protection Act [AP20PPQS&T00C154, AP21PPQS&T00C063, AP22PPQS&T00C070]; and United States Department of Agriculture Hatch Grant [KY008091].

Funders	Funder number
United States Department of Agriculture-Animal and Plant Health Inspection Service-Plant Protection Act	T00C154, T00C063, T00C070
U.S. Department of Agriculture	KY008091
U.S. Department of Agriculture
United States Department of Agriculture National Institute of Food and Agriculture, Agriculture and Food Research Initiative CARE	2020–67013-30978

ASJC Scopus subject areas

Statistics and Probability
Biochemistry
Molecular Biology
Computer Science Applications
Computational Theory and Mathematics
Computational Mathematics

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10.1093/bioinformatics/btae377

Cite this

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title = "snpAIMeR: R package for evaluating ancestry informative marker contributions in non-model population diagnostics",

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.",

author = "Vertacnik, \{Kim L.\} and Vernygora, \{Oksana V.\} and Dupuis, \{Julian R.\}",

note = "Publisher Copyright: {\textcopyright} 2024 The Author(s). Published by Oxford University Press.",

year = "2024",

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doi = "10.1093/bioinformatics/btae377",

language = "English",

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AB - 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.

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snpAIMeR: R package for evaluating ancestry informative marker contributions in non-model population diagnostics

Abstract

Bibliographical note

Funding

ASJC Scopus subject areas

Access to Document

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