Literature DB >> 31975164

Exploring Population Structure with Admixture Models and Principal Component Analysis.

Chi-Chun Liu1, Suyash Shringarpure2, Kenneth Lange3,4,5, John Novembre6.   

Abstract

Population structure is a commonplace feature of genetic variation data, and it has importance in numerous application areas, including evolutionary genetics, conservation genetics, and human genetics. Understanding the structure in a sample is necessary before more sophisticated analyses are undertaken. Here we provide a protocol for running principal component analysis (PCA) and admixture proportion inference-two of the most commonly used approaches in describing population structure. Along with hands-on examples with CEPH-Human Genome Diversity Panel and pragmatic caveats, readers will learn to analyze and visualize population structure on their own data.

Entities:  

Keywords:  Admixture; Population stratification; Population structure; Principal component analysis

Mesh:

Year:  2020        PMID: 31975164      PMCID: PMC8722024          DOI: 10.1007/978-1-0716-0199-0_4

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  26 in total

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Journal:  Science       Date:  2002-04-12       Impact factor: 47.728

2.  Synthetic maps of human gene frequencies in Europeans.

Authors:  P Menozzi; A Piazza; L Cavalli-Sforza
Journal:  Science       Date:  1978-09-01       Impact factor: 47.728

3.  Clumpak: a program for identifying clustering modes and packaging population structure inferences across K.

Authors:  Naama M Kopelman; Jonathan Mayzel; Mattias Jakobsson; Noah A Rosenberg; Itay Mayrose
Journal:  Mol Ecol Resour       Date:  2015-02-27       Impact factor: 7.090

4.  Inferring weak population structure with the assistance of sample group information.

Authors:  Melissa J Hubisz; Daniel Falush; Matthew Stephens; Jonathan K Pritchard
Journal:  Mol Ecol Resour       Date:  2009-04-01       Impact factor: 7.090

Review 5.  Recent advances in the study of fine-scale population structure in humans.

Authors:  John Novembre; Benjamin M Peter
Journal:  Curr Opin Genet Dev       Date:  2016-09-20       Impact factor: 5.578

6.  Worldwide human relationships inferred from genome-wide patterns of variation.

Authors:  Jun Z Li; Devin M Absher; Hua Tang; Audrey M Southwick; Amanda M Casto; Sohini Ramachandran; Howard M Cann; Gregory S Barsh; Marcus Feldman; Luigi L Cavalli-Sforza; Richard M Myers
Journal:  Science       Date:  2008-02-22       Impact factor: 47.728

Review 7.  Genetics in geographically structured populations: defining, estimating and interpreting F(ST).

Authors:  Kent E Holsinger; Bruce S Weir
Journal:  Nat Rev Genet       Date:  2009-09       Impact factor: 53.242

8.  Analysis of population structure: a unifying framework and novel methods based on sparse factor analysis.

Authors:  Barbara E Engelhardt; Matthew Stephens
Journal:  PLoS Genet       Date:  2010-09-16       Impact factor: 5.917

9.  Enhancements to the ADMIXTURE algorithm for individual ancestry estimation.

Authors:  David H Alexander; Kenneth Lange
Journal:  BMC Bioinformatics       Date:  2011-06-18       Impact factor: 3.307

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Authors:  Christopher C Chang; Carson C Chow; Laurent Cam Tellier; Shashaank Vattikuti; Shaun M Purcell; James J Lee
Journal:  Gigascience       Date:  2015-02-25       Impact factor: 6.524

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  4 in total

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Journal:  BMC Plant Biol       Date:  2022-01-27       Impact factor: 4.215

2.  Multiple evolutionary origins of glyphosate resistance in Lolium multiflorum.

Authors:  Caio A C G Brunharo; Matthew A Streisfeld
Journal:  Evol Appl       Date:  2022-02-08       Impact factor: 5.183

3.  First Glimpse into the Genomic Characterization of People from the Imperial Roman Community of Casal Bertone (Rome, First-Third Centuries AD).

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4.  The recombination landscapes of spiny lizards (genus Sceloporus).

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  4 in total

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