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EasyParallel: A GUI platform for parallelization of STRUCTURE and NEWHYBRIDS analyses.
Zhao, Honggang; Beck, Benjamin; Fuller, Adam; Peatman, Eric.
Afiliación
  • Zhao H; School of Fisheries, Aquaculture, and Aquatic Sciences, Auburn University, Auburn, AL, United States of America.
  • Beck B; Agricultural Research Service, Aquatic Animal Health Research Unit, United States Department of Agriculture, Auburn, AL, United States of America.
  • Fuller A; Agricultural Research Service, Stuttgart National Aquaculture Research Center, United States Department of Agriculture, Stuttgart, AR, United States of America.
  • Peatman E; School of Fisheries, Aquaculture, and Aquatic Sciences, Auburn University, Auburn, AL, United States of America.
PLoS One ; 15(4): e0232110, 2020.
Article en En | MEDLINE | ID: mdl-32330179
ABSTRACT
The software programs STRUCTURE and NEWHYBRIDS are widely used population genetic programs useful in addressing questions related to genetic structure, admixture, and hybridization. These programs usually require a large number of independent runs with many iterations to provide robust data for downstream analyses, thus significantly increasing computation time. Programs such as Structure_threader and parallelnewhybrid were previously developed to address this problem by processing tasks in parallel on a multi-threaded processor; however some programming knowledge (e.g., R, Bash) is required to run these programs. We developed EasyParallel as a community resource to facilitate practical and routine population structure and hybridization analyses. The multi-threaded parallelization of EasyParallel allows processing of large genetic datasets in a very efficient way, with its point-and-click GUI providing ready access to users who have little experience in script programming. Performance evaluation of EasyParallel using simulated datasets showed similar speed-up and parallel execution time when compared to Structure_threader and Parallelnewhybrid. EasyParallel is written in Python 3 and freely available on the GitHub site https//github.com/hzz0024/EasyParallel.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Análisis de Secuencia de ADN / Biología Computacional / Genética de Población Límite: Animals / Humans Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Análisis de Secuencia de ADN / Biología Computacional / Genética de Población Límite: Animals / Humans Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos
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