Kernel density estimation of allele frequency including undetected alleles.


Journal

PeerJ
ISSN: 2167-8359
Titre abrégé: PeerJ
Pays: United States
ID NLM: 101603425

Informations de publication

Date de publication:
2024
Historique:
received: 24 11 2023
accepted: 25 03 2024
medline: 26 4 2024
pubmed: 26 4 2024
entrez: 26 4 2024
Statut: epublish

Résumé

Whereas undetected species contribute to estimation of species diversity, undetected alleles have not been used to estimated genetic diversity. Although random sampling guarantees unbiased estimation of allele frequency and genetic diversity measures, using undetected alleles may provide biased but more precise estimators useful for conservation. We newly devised kernel density estimation (KDE) for allele frequency including undetected alleles and tested it in estimation of allele frequency and nucleotide diversity using population generated by coalescent simulation as well as well as real population data. Contrary to expectations, nucleotide diversity estimated by KDE had worse bias and accuracy. Allele frequency estimated by KDE was also worse except when the sample size was small. These might be due to finity of population and/or the curse of dimensionality. In conclusion, KDE of allele frequency does not contribute to genetic diversity estimation.

Identifiants

pubmed: 38666077
doi: 10.7717/peerj.17248
pii: 17248
pmc: PMC11044881
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e17248

Informations de copyright

© 2024 Aoki and Fukasawa.

Déclaration de conflit d'intérêts

The authors declare that they have no competing interests.

Auteurs

Satoshi Aoki (S)

Biodiversity Division, National Institute for Environmental Studies, Tsukuba, Ibaraki, Japan.

Keita Fukasawa (K)

Biodiversity Division, National Institute for Environmental Studies, Tsukuba, Ibaraki, Japan.

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