StrAuto: automation and parallelization of STRUCTURE analysis

BMC Bioinformatics

Software

Kevin J. Emerson¹  Vikram E. Chhatre² 

[1] Department of Biology, St. Mary’s College of Maryland, St. Mary’s City, Maryland, USA;Department of Plant Biology, University of Vermont, Burlington, Vermont, USA;Current Address: Wyoming INBRE Bioinformatics Core, Department of Molecular Biology, University of Wyoming, Laramie, Wyoming, USA;

关键词: STRUCTURE analysis;    Parallelization;    Population genomics;   

DOI  :  10.1186/s12859-017-1593-0

 received in 2016-10-08, accepted in 2017-03-10,  发布年份 2017

来源: Springer

【 摘 要 】

BackgroundPopulation structure inference using the software STRUCTURE has become an integral part of population genetic studies covering a broad spectrum of taxa including humans. The ever-expanding size of genetic data sets poses computational challenges for this analysis. Although at least one tool currently implements parallel computing to reduce computational overload of this analysis, it does not fully automate the use of replicate STRUCTURE analysis runs required for downstream inference of optimal K. There is pressing need for a tool that can deploy population structure analysis on high performance computing clusters.ResultsWe present an updated version of the popular Python program StrAuto, to streamline population structure analysis using parallel computing. StrAuto implements a pipeline that combines STRUCTURE analysis with the Evanno ΔK analysis and visualization of results using STRUCTURE HARVESTER. Using benchmarking tests, we demonstrate that StrAuto significantly reduces the computational time needed to perform iterative STRUCTURE analysis by distributing runs over two or more processors.ConclusionStrAuto is the first tool to integrate STRUCTURE analysis with post-processing using a pipeline approach in addition to implementing parallel computation – a set up ideal for deployment on computing clusters. StrAuto is distributed under the GNU GPL (General Public License) and available to download from http://strauto.popgen.org.

【 授权许可】

CC BY   
© The Author(s) 2017