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'dstidyverse': An Implementation of TidyverseWithin the DataSHIELD Ecosystem.

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Area of Science:

  • Bioinformatics
  • Data Science
  • Computational Biology

Background:

  • DataSHIELD is an established R-based federated learning platform for multi-site analysis without data sharing.
  • Existing DataSHIELD packages lack user-friendly data manipulation capabilities.

Purpose of the Study:

  • To introduce dsTidyverse, a package that integrates Tidyverse functionalities into DataSHIELD.
  • To enhance data manipulation within the DataSHIELD client-server architecture.

Main Methods:

  • Implemented selected Tidyverse functions within DataSHIELD's architecture.
  • Integrated disclosure checks to prevent individual-level data leakage.

Main Results:

  • dsTidyverse offers tools for column selection, renaming, creation, conditional recoding, data frame combination, row filtering/arranging, and grouping.
  • Demonstrated simplified data manipulation tasks within DataSHIELD using dsTidyverse examples.

Conclusions:

  • dsTidyverse enhances user experience and analytical efficiency in DataSHIELD.
  • The open-source package is available on CRAN and GitHub, encouraging further development.