GroupStruct2: A User-Friendly Graphical User Interface for Statistical and Visual Support in Species Diagnosis.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος:	GroupStruct2: A User-Friendly Graphical User Interface for Statistical and Visual Support in Species Diagnosis.
Συγγραφείς:	Chan KO; Department of Integrative Biology; MSU Museum; Ecology, Evolution, and Behavior Program; Michigan State University, 288 Farm Lane, East Lansing, MI 48824, USA., Grismer LL; Herpetology Laboratory, Department of Biology, La Sierra University, 4500 Riverwalk Parkway, Riverside, CA 92505, USA.; Department of Herpetology, San Diego Natural History Museum, PO Box 121390, San Diego, CA 92112, USA.
Πηγή:	Systematic biology [Syst Biol] 2026 Jun 12; Vol. 75 (4), pp. 814-823.
Τύπος έκδοσης:	Journal Article
Γλώσσα:	English
Στοιχεία περιοδικού:	Publisher: Oxford University Press Country of Publication: England NLM ID: 9302532 Publication Model: Print Cited Medium: Internet ISSN: 1076-836X (Electronic) Linking ISSN: 10635157 NLM ISO Abbreviation: Syst Biol Subsets: MEDLINE
Imprint Name(s):	Publication: 2009- : Oxford : Oxford University Press Original Publication: Washington, D.C., USA : Society of Systematic Biologists, [1992-
Ιατρικοί όροι (MeSH):	Classification/methods , User-Computer Interface , Software* , Computer Graphics*
Περίληψη:	Statistically defensible species diagnoses are essential for producing robust taxonomies, which underpin much of biological research. Yet, most species descriptions remain largely descriptive, often lack rigorous statistical validation, and suffer from confounding factors stemming from sampling bias, geographic variation, and intraspecific diversity. These limitations are further compounded by the steep learning curve of advanced statistical and data visualization tools, which poses a major barrier for early-career scientists and researchers in under-resourced regions who may lack programming experience or access to expert support. To address these challenges, we developed GroupStruct2, a powerful yet accessible R-based Shiny application that democratizes robust statistical analysis and data visualization for species diagnosis across any taxonomic group. GroupStruct2 is implemented through a user-friendly graphical user interface (GUI) that requires no coding experience. The user-friendly interface intuitively guides users through a comprehensive workflow, from raw data upload and outlier detection to assumption testing, adaptive statistical analyses, and the generation of highly customizable, publication-ready visualizations based on the ggplot2 architecture. It supports allometric body-size correction and widely used dimension-reduction techniques, including Principal Component Analysis (PCA), Discriminant Analysis of Principal Components (DAPC), and, critically, Multiple Factor Analysis (MFA), which enables the joint analysis of meristic, morphometric, and categorical trait data within a single integrative taxonomic framework. We showcase GroupStruct2's capabilities using two empirical data sets, demonstrating how to conduct robust statistical analyses and produce publication-quality visualizations in just a few clicks. By lowering technical barriers without compromising analytical rigor, GroupStruct2 empowers researchers of all backgrounds working on any taxonomic group to conduct statistically sound and produce visually compelling species diagnoses, thereby advancing both the accessibility and the scientific rigor of taxonomy, species delimitation, and biodiversity research. (© The Author(s) 2025. Published by Oxford University Press on behalf of the Society of Systematic Biologists.)
Contributed Indexing:	Keywords: GUI; R; morphology; shiny application; species delimitation; statistics; taxonomy
Entry Date(s):	Date Created: 20251222 Date Completed: 20260612 Latest Revision: 20260726
Update Code:	20260726
PubMed Central ID:	PMC13291812
DOI:	10.1093/sysbio/syaf090
PMID:	41427886
Βάση Δεδομένων:	MEDLINE

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Περιγραφή
ISSN:	1076-836X
DOI:	10.1093/sysbio/syaf090