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PANE：基于非负最小二乘法和主成分分析对古代基因型数据进行快速可靠的祖先重建。

PANE: fast and reliable ancestral reconstruction on ancient genotype data with non-negative least square and principal component analysis.

作者信息

de Gennaro Luciana, Molinaro Ludovica, Raveane Alessandro, Santonastaso Federica, Saponetti Sandro Sublimi, Massi Michela Carlotta, Pagani Luca, Metspalu Mait, Hellenthal Garrett, Kivisild Toomas, Ventura Mario, Montinaro Francesco

机构信息

Department of Biosciences, Biotechnology and Environment, University of Bari, Bari, Italy.

Department of Human Genetics, KU Leuven, Leuven, Belgium.

出版信息

Genome Biol. 2025 Feb 11;26(1):29. doi: 10.1186/s13059-025-03491-z.

DOI:10.1186/s13059-025-03491-z
PMID:39934833
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11818073/
Abstract

The history of human populations has been strongly shaped by admixture events, contributing to patterns of observed genetic diversity across populations. In this study, we introduce the Principal component Ancestry proportions using NNLS Estimation (PANE) method that leverages principal component analysis and non-negative least squares to assess the ancestral compositions of admixed individuals given a large set of populations. Our results show its ability to reliably estimate ancestry across several scenarios, even those with a significant proportion of missing genotypes, in a fraction of the time required when using other tools.

摘要

人类群体的历史受到混合事件的强烈影响，这促成了各群体间观察到的遗传多样性模式。在本研究中，我们引入了使用非负最小二乘法估计的主成分祖先比例（PANE）方法，该方法利用主成分分析和非负最小二乘法，在给定大量群体的情况下评估混合个体的祖先组成。我们的结果表明，在使用其他工具所需时间的一小部分内，它能够在多种情况下可靠地估计祖先，即使是在存在相当比例缺失基因型的情况下。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10f5/11818073/a85933ddfc57/13059_2025_3491_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10f5/11818073/f319e0ca04ea/13059_2025_3491_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10f5/11818073/56fc756089b7/13059_2025_3491_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10f5/11818073/0874751dae01/13059_2025_3491_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10f5/11818073/cadaf28300d1/13059_2025_3491_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10f5/11818073/03267936f11a/13059_2025_3491_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10f5/11818073/a85933ddfc57/13059_2025_3491_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10f5/11818073/f319e0ca04ea/13059_2025_3491_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10f5/11818073/c9b50aa1de6c/13059_2025_3491_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10f5/11818073/56fc756089b7/13059_2025_3491_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10f5/11818073/0874751dae01/13059_2025_3491_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10f5/11818073/cadaf28300d1/13059_2025_3491_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10f5/11818073/03267936f11a/13059_2025_3491_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10f5/11818073/a85933ddfc57/13059_2025_3491_Fig7_HTML.jpg

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