Evidence map›Paper›PMID 32074134›Full record

ArticlePloS one2020

StructuRly: A novel shiny app to produce comprehensive, detailed and interactive plots for population genetic analysis.

Nicola G Criscuolo, Claudia Angelini

Erratum issuedAbstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed.

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  9. Contrasting Patterns of Raccoon (Evolutionary applications · 2025
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  12. Genome-wide association study of fiber quality traits in US upland cotton (Gossypium hirsutum L.).TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024
    Article
  13. Article
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  15. Article
  16. Are rabid raccoons (Evolutionary applications · 2023
    Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Nicola G CriscuoloDepartment of Environmental Systems Science, ETH Zürich, Zurich, Switzerland.ORCID 0000-0002-0394-0888
Claudia AngeliniIstituto per le Applicazioni del Calcolo "M. Picone", National Research Council, Naples, Italy.ORCID 0000-0001-8350-8464

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

AlgorithmsComputer GraphicsData Interpretation, StatisticalGenetics, PopulationSoftwareBayes TheoremComputational BiologyHumans

Identifiers

PMID32074134
PMCPMC7029954

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.