Struct-f4: a Rcpp package for ancestry profile and population structure inference from f(4)-statistics

SUMMARY: Visualization and inference of population structure is increasingly important for fundamental and applied research. Here, we present Struct-f4, providing automated solutions to characterize and summarize the genetic ancestry profile of individuals, assess their genetic affinities, identify...

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Detalles Bibliográficos
Autores principales: Librado, Pablo, Orlando, Ludovic
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Applications Note
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8963280/
https://www.ncbi.nlm.nih.gov/pubmed/35080599
http://dx.doi.org/10.1093/bioinformatics/btac046
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author Librado, Pablo
Orlando, Ludovic
author_facet Librado, Pablo
Orlando, Ludovic
author_sort Librado, Pablo
collection PubMed
description SUMMARY: Visualization and inference of population structure is increasingly important for fundamental and applied research. Here, we present Struct-f4, providing automated solutions to characterize and summarize the genetic ancestry profile of individuals, assess their genetic affinities, identify admixture sources and quantify admixture levels. AVAILABILITY AND IMPLEMENTATION: Struct-f4 is written in Rcpp and relies on f(4)-statistics and Markov Chain Monte Carlo (MCMC) optimization. It is freely available under GNU General Public License in Bitbucket (https://bitbucket.org/plibradosanz/structf4/). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-89632802022-03-29 Struct-f4: a Rcpp package for ancestry profile and population structure inference from f(4)-statistics Librado, Pablo Orlando, Ludovic Bioinformatics Applications Note SUMMARY: Visualization and inference of population structure is increasingly important for fundamental and applied research. Here, we present Struct-f4, providing automated solutions to characterize and summarize the genetic ancestry profile of individuals, assess their genetic affinities, identify admixture sources and quantify admixture levels. AVAILABILITY AND IMPLEMENTATION: Struct-f4 is written in Rcpp and relies on f(4)-statistics and Markov Chain Monte Carlo (MCMC) optimization. It is freely available under GNU General Public License in Bitbucket (https://bitbucket.org/plibradosanz/structf4/). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2022-01-26 /pmc/articles/PMC8963280/ /pubmed/35080599 http://dx.doi.org/10.1093/bioinformatics/btac046 Text en © The Author(s) 2022. Published by Oxford University Press. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Applications Note
Librado, Pablo
Orlando, Ludovic
Struct-f4: a Rcpp package for ancestry profile and population structure inference from f(4)-statistics
title Struct-f4: a Rcpp package for ancestry profile and population structure inference from f(4)-statistics
title_full Struct-f4: a Rcpp package for ancestry profile and population structure inference from f(4)-statistics
title_fullStr Struct-f4: a Rcpp package for ancestry profile and population structure inference from f(4)-statistics
title_full_unstemmed Struct-f4: a Rcpp package for ancestry profile and population structure inference from f(4)-statistics
title_short Struct-f4: a Rcpp package for ancestry profile and population structure inference from f(4)-statistics
title_sort struct-f4: a rcpp package for ancestry profile and population structure inference from f(4)-statistics
topic Applications Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8963280/
https://www.ncbi.nlm.nih.gov/pubmed/35080599
http://dx.doi.org/10.1093/bioinformatics/btac046
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