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Protocol to analyze population structure and migration history based on human genome variation data

We describe a protocol to integrate genome variation data from different datasets and explore the population structure and migration history of human populations. This protocol provides semi-automated scripts to perform and visualize the effect of variant filtering strategy on eliminating batch effe...

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Detalles Bibliográficos
Autores principales: Zhao, Zicheng, Wang, Yinan, Zhang, Zhe, Li, Shuai Cheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9758492/
https://www.ncbi.nlm.nih.gov/pubmed/36520631
http://dx.doi.org/10.1016/j.xpro.2022.101928
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author Zhao, Zicheng
Wang, Yinan
Zhang, Zhe
Li, Shuai Cheng
author_facet Zhao, Zicheng
Wang, Yinan
Zhang, Zhe
Li, Shuai Cheng
author_sort Zhao, Zicheng
collection PubMed
description We describe a protocol to integrate genome variation data from different datasets and explore the population structure and migration history of human populations. This protocol provides semi-automated scripts to perform and visualize the effect of variant filtering strategy on eliminating batch effects, principal component analysis, ancestry component analysis, historical population effective size inference, and migration and isolation analysis based on independent biallelic SNPs, genotype likelihoods, and haplotypes. The protocol can be adapted to variation data from other sources. For complete details on the use and execution of this protocol, please refer to Zhang et al. (2022).(1)
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spelling pubmed-97584922022-12-18 Protocol to analyze population structure and migration history based on human genome variation data Zhao, Zicheng Wang, Yinan Zhang, Zhe Li, Shuai Cheng STAR Protoc Protocol We describe a protocol to integrate genome variation data from different datasets and explore the population structure and migration history of human populations. This protocol provides semi-automated scripts to perform and visualize the effect of variant filtering strategy on eliminating batch effects, principal component analysis, ancestry component analysis, historical population effective size inference, and migration and isolation analysis based on independent biallelic SNPs, genotype likelihoods, and haplotypes. The protocol can be adapted to variation data from other sources. For complete details on the use and execution of this protocol, please refer to Zhang et al. (2022).(1) Elsevier 2022-12-13 /pmc/articles/PMC9758492/ /pubmed/36520631 http://dx.doi.org/10.1016/j.xpro.2022.101928 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Protocol
Zhao, Zicheng
Wang, Yinan
Zhang, Zhe
Li, Shuai Cheng
Protocol to analyze population structure and migration history based on human genome variation data
title Protocol to analyze population structure and migration history based on human genome variation data
title_full Protocol to analyze population structure and migration history based on human genome variation data
title_fullStr Protocol to analyze population structure and migration history based on human genome variation data
title_full_unstemmed Protocol to analyze population structure and migration history based on human genome variation data
title_short Protocol to analyze population structure and migration history based on human genome variation data
title_sort protocol to analyze population structure and migration history based on human genome variation data
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9758492/
https://www.ncbi.nlm.nih.gov/pubmed/36520631
http://dx.doi.org/10.1016/j.xpro.2022.101928
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