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EasyParallel: A GUI platform for parallelization of STRUCTURE and NEWHYBRIDS analyses

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  • Honggang Zhao
  • Benjamin Beck
  • Adam Fuller
  • Eric Peatman

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.

Suggested Citation

  • Honggang Zhao & Benjamin Beck & Adam Fuller & Eric Peatman, 2020. "EasyParallel: A GUI platform for parallelization of STRUCTURE and NEWHYBRIDS analyses," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-7, April.
    • Handle: RePEc:plo:pone00:0232110
    DOI: 10.1371/journal.pone.0232110
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