Recommendations for utilizing and reporting population genetic analyses: the reproducibility of genetic clustering using the program STRUCTURE

Title
Recommendations for utilizing and reporting population genetic analyses: the reproducibility of genetic clustering using the program STRUCTURE
Publication Date
2012
Author(s)
Gilbert, Kimberly J
Andrew, Rose
( author )
OrcID: https://orcid.org/0000-0003-0099-8336
Email: randre20@une.edu.au
UNE Id une-id:randre20
Vines, Timothy H
Bock, Dan G
Franklin, Michelle T
Kane, Nolan C
Moore, Jean-Sebastien
Moyers, Brook T
Renaut, Sebastien
Rennison, Diana J
Veen, Thor
Type of document
Journal Article
Language
en
Entity Type
Publication
Publisher
Blackwell Publishing Ltd
Place of publication
United Kingdom
DOI
10.1111/j.1365-294X.2012.05754.x
UNE publication id
une:15904
Abstract
Reproducibility is the benchmark for results and conclusions drawn from scientific studies, but systematic studies on the reproducibility of scientific results are surprisingly rare. Moreover, many modern statistical methods make use of 'random walk' model fitting procedures, and these are inherently stochastic in their output. Does the combination of these statistical procedures and current standards of data archiving and method reporting permit the reproduction of the authors' results? To test this, we reanalysed data sets gathered from papers using the software package STRUCTURE to identify genetically similar clusters of individuals. We find that reproducing STRUCTURE results can be difficult despite the straightforward requirements of the program. Our results indicate that 30% of analyses were unable to reproduce the same number of population clusters. To improve this, we make recommendations for future use of the software and for reporting STRUCTURE analyses and results in published works.
Link
Citation
Molecular Ecology, 21(20), p. 4925-4930
ISSN
1365-294X
0962-1083
Start page
4925
End page
4930

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