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

Area of Science:

• * Integrative Taxonomy and Biodiversity Research
• * Computational Biology and Bioinformatics
• * Evolutionary Biology and Systematics

Background:

• * Robust species diagnoses are critical for biological research, but current methods often lack statistical rigor and are hindered by sampling biases and intraspecific variation.
• * Advanced statistical and visualization tools present a steep learning curve, creating barriers for early-career scientists and researchers in under-resourced regions.
• * Existing limitations impede the accessibility and scientific rigor of species delimitation and taxonomic research.

Purpose of the Study:

• * To develop an accessible R-based Shiny application, GroupStruct2, for democratizing robust statistical analysis and data visualization in species diagnosis.
• * To provide a user-friendly graphical user interface (GUI) that requires no coding experience, facilitating complex analyses for a broader scientific audience.
• * To enhance the rigor and accessibility of taxonomic research, species delimitation, and biodiversity studies.

Main Methods:

• * GroupStruct2 features an intuitive GUI guiding users from data upload and outlier detection to assumption testing and adaptive statistical analyses.
• * The application supports allometric body-size correction and dimension-reduction techniques like Principal Component Analysis (PCA), Discriminant Analysis of Principal Components (DAPC), and Multiple Factor Analysis (MFA).
• * It enables the joint analysis of meristic, morphometric, and categorical trait data within an integrative taxonomic framework, generating publication-ready visualizations via ggplot2.

Main Results:

• * GroupStruct2 successfully integrates diverse statistical analyses and data visualization capabilities into a single, accessible platform.
• * The application demonstrates its utility through empirical datasets, enabling robust analyses and publication-quality visualizations with minimal user input.
• * Empirical examples showcase the tool's effectiveness in conducting statistically sound species diagnoses and generating compelling visualizations.

Conclusions:

• * GroupStruct2 significantly lowers technical barriers to advanced statistical analysis in taxonomy without compromising scientific rigor.
• * The application empowers researchers across all backgrounds and taxonomic groups to perform statistically sound species diagnoses.
• * GroupStruct2 advances the accessibility and scientific rigor of taxonomy, species delimitation, and biodiversity research globally.