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

• 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
• DOI: 10.1371/journal.pone.0232110

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.