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dc.contributor.author
Criscuolo, Nicola G.
dc.contributor.author
Angelini, Claudia
dc.date.accessioned
2020-06-08T08:23:48Z
dc.date.available
2020-06-07T02:31:12Z
dc.date.available
2020-06-08T08:23:48Z
dc.date.issued
2020-02
dc.identifier.issn
1932-6203
dc.identifier.other
10.1371/journal.pone.0229330
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/418661
dc.identifier.doi
10.3929/ethz-b-000418661
dc.description.abstract
Population genetics focuses on the analysis of genetic differences within and between-group of individuals and the inference of the populations’ structure. These analyses are usually carried out using Bayesian clustering or maximum likelihood estimation algorithms that assign individuals to a given population depending on specific genetic patterns. Although several tools were developed to perform population genetics analysis, their standard graphical outputs may not be sufficiently informative for users lacking interactivity and complete information. StructuRly aims to resolve this problem by offering a complete environment for population analysis. In particular, StructuRly combines the statistical power of the R language with the friendly interfaces implemented using the shiny libraries to provide a novel tool for performing population clustering, evaluating several genetic indexes, and comparing results. Moreover, graphical representations are interactive and can be easily personalized. StructuRly is available either as R package on GitHub, with detailed information for its installation and use and as shinyapps.io servers for those users who are not familiar with R and the RStudio IDE. The application has been tested on Linux, macOS and Windows operative systems and can be launched as a shiny app in every web browser.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
PLOS
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.title
StructuRly: A novel shiny app to produce comprehensive, detailed and interactive plots for population genetic analysis
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 4.0 International
dc.date.published
2020-02-19
ethz.journal.title
PLoS ONE
ethz.journal.volume
15
en_US
ethz.journal.issue
2
en_US
ethz.journal.abbreviated
PLoS ONE
ethz.pages.start
e0229330
en_US
ethz.size
12 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
San Francisco, CA
ethz.publication.status
published
en_US
ethz.date.deposited
2020-06-07T02:31:16Z
ethz.source
WOS
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2020-06-08T08:23:58Z
ethz.rosetta.lastUpdated
2024-02-02T11:02:00Z
ethz.rosetta.versionExported
true
ethz.COinS
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