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

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 down...

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Bibliographic Details
Published in:PloS one Vol. 15; no. 4; p. e0232110
Main Authors: Zhao, Honggang, Beck, Benjamin, Fuller, Adam, Peatman, Eric
Format: Journal Article
Language:English
Published: United States Public Library of Science 24.04.2020
Public Library of Science (PLoS)
Subjects:
Agricultural research
Aquaculture
Aquatic sciences
Biology and Life Sciences
Computer and Information Sciences
Computer simulation
Data analysis
Datasets
Design
Engineering and Technology
Fisheries
Genetic programs
Genetic structure
Graphical user interface
Human error
Hybridization
Linux
Microprocessors
Operating systems
Parallel processing
Performance evaluation
Population
Population genetics
Population structure
Portable computers
Research and analysis methods
Semiconductor industry
Software
Structure (Literature)
Time
User interface
United States
United States > US
ISSN:1932-6203, 1932-6203
Online Access:Get full text
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Summary: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.
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Competing Interests: The authors have declared that no competing interests exist.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0232110