Determining population structure from k-mer frequencies

This study shows that PCA, together with the clustering algorithm, is able to detect population structure from k-mer frequencies and can separate samples of admixed and non-admixed origin. Using k-mer frequencies to determine population structure has the potential to avoid some challenges of existing methods and may even improve on estimates from small samples.

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Publication Details

Journal
PeerJ
Published
2025-03-05
DOI
https://doi.org/10.7717/peerj.18939
Primary Topic
Genetic Mapping and Diversity in Plants and Animals
Type
article
Field-Weighted Citation Impact
0.00
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article

Determining population structure from k-mer frequencies

Yana Hrytsenko, Rachel S. Schwartz, Noah M. Daniels
PeerJ
Genetic Mapping and Diversity in Plants and Animals
article

Determining population structure from k-mer frequencies

Yana Hrytsenko, Rachel S. Schwartz, Noah M. Daniels
article en

Abstract

This study shows that PCA, together with the clustering algorithm, is able to detect population structure from k-mer frequencies and can separate samples of admixed and non-admixed origin. Using k-mer frequencies to determine population structure has the potential to avoid some challenges of existing methods and may even improve on estimates from small samples.

PeerJVol. 13
University of Rhode Island (US)
Openalex Percentile: Top 95%
Genetic Mapping and Diversity in Plants and Animals
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