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

Autor: Benjamin H. Beck, Eric Peatman, Honggang Zhao, Adam Fuller
Jazyk: angličtina
Rok vydání: 2020
Předmět:
0106 biological sciences
0301 basic medicine
Man-Computer Interface
Computer science
Molecular biology
Parallel computing
01 natural sciences
Computer Architecture
User-Computer Interface
Software
Sequencing techniques
Graphical User Interfaces
DNA sequencing
computer.programming_language
education.field_of_study
Multidisciplinary
Data Processing
Simulation and Modeling
Genomics
Engineering and Technology
Medicine
Information Technology
Transcriptome Analysis
Algorithms
Research Article
Next-Generation Sequencing
Computer and Information Sciences
Computation
Operating Systems
Science
Population
010603 evolutionary biology
Execution time
Computer Software
03 medical and health sciences
Genetics
Animals
Humans
education
Evolutionary Biology
Population Biology
business.industry
Biology and Life Sciences
Computational Biology
Sequence Analysis
DNA
Python (programming language)
Genome Analysis
Research and analysis methods
030104 developmental biology
Molecular biology techniques
Genetics
Population
Human Factors Engineering
Programming Languages
business
computer
Population Genetics
User Interfaces
Zdroj: PLoS ONE, Vol 15, Iss 4, p e0232110 (2020)
PLoS ONE
ISSN: 1932-6203
Popis: 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.
Databáze: OpenAIRE
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