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. 2013 Jul 29;8(7):e70651.
doi: 10.1371/journal.pone.0070651. Print 2013.

ParallelStructure: a R package to distribute parallel runs of the population genetics program STRUCTURE on multi-core computers

Francois Besnier  1 , Kevin A Glover
Affiliations

ParallelStructure: a R package to distribute parallel runs of the population genetics program STRUCTURE on multi-core computers

Francois Besnier et al. PLoS One. .

Abstract

This software package provides an R-based framework to make use of multi-core computers when running analyses in the population genetics program STRUCTURE. It is especially addressed to those users of STRUCTURE dealing with numerous and repeated data analyses, and who could take advantage of an efficient script to automatically distribute STRUCTURE jobs among multiple processors. It also consists of additional functions to divide analyses among combinations of populations within a single data set without the need to manually produce multiple projects, as it is currently the case in STRUCTURE. The package consists of two main functions: MPI_structure() and parallel_structure() as well as an example data file. We compared the performance in computing time for this example data on two computer architectures and showed that the use of the present functions can result in several-fold improvements in terms of computation time. ParallelStructure is freely available at https://r-forge.r-project.org/projects/parallstructure/.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Gains in job execution time (speed-up) for the example data when running on variable number of processors on two computer architectures.
(a) a Windows 7 laptop PC equipped with a Core i7 2.2GHz quad core processor with 8Gb of RAM and (b) an Apple workstation equipped with an Intel Xeon 2.26GHz double quad core processor with 16GB of RAM. Maximum speed-up is represented by the dashed line (y = x).
See this image and copyright information in PMC

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