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Basics of Multivariate Analysis in Neuroimaging Data
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MVApp-Multivariate Analysis Application for Streamlined Data Analysis and Curation.

Magdalena M Julkowska1, Stephanie Saade2, Gaurav Agarwal3

  • 1Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal 23955-6900, Kingdom of Saudi Arabia magalena.julkowska@kaust.edu.sa.

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Summary
This summary is machine-generated.

Experimental biologists can now analyze complex phenotyping data more easily with MVApp, an open-source platform for multivariate analysis. This tool enhances data curation, analysis, and visualization, improving genotype-to-phenotype insights.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Plant Sciences

Background:

  • Modern phenotyping generates large, complex datasets.
  • Analyzing this data is challenging for biologists lacking data science expertise.
  • Ensuring data transparency, accessibility, and reproducibility is crucial for publication.

Purpose of the Study:

  • To introduce MVApp, an open-source online platform for multivariate analysis.
  • To provide a user-friendly pipeline for advanced phenotyping data curation, analysis, and visualization.
  • To enhance statistical literacy and streamline data management for experimental biologists.

Main Methods:

  • Development of an open-source, web-based platform (MVApp).
  • Integration of existing R-packages with enhanced functionalities.
  • Implementation of tools for data curation, multivariate analysis, clustering, and quantile regression.
  • Focus on modular design for flexible analysis of diverse data structures.

Main Results:

  • MVApp offers an interactive pipeline for comprehensive phenotypic data analysis.
  • The platform enhances the interpretability of results through advanced visualization.
  • It supports underexplored analytical methods like clustering and quantile regression.
  • MVApp facilitates findable, accessible, interoperable, and reproducible (FAIR) data practices.

Conclusions:

  • MVApp addresses the need for streamlined, user-friendly phenotyping data analysis.
  • The platform empowers biologists to extract deeper genotype-to-phenotype insights.
  • MVApp promotes data transparency, reproducibility, and statistical literacy in the scientific community.