ArticleBMC bioinformatics2017
StrAuto: automation and parallelization of STRUCTURE analysis.
Article in BMC bioinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 75 papers.
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Who cites it
75 citing papers in PubMed, 200 citations in OpenAlex.
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15 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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 Δ K 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 .
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.