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'dstidyverse': An Implementation of TidyverseWithin the DataSHIELD Ecosystem
Tim Cadman1,2, Mariska Slofstra1, Demetris Avraam3
1Department of Genetics, Genomics Coordination Center, University Medical Centre, Groningen, The Netherlands.
Background:
DataSHIELD is a mature, R-based federated learning platform that enables multi-site analysis without sharing individual participant data. While DataSHIELD includes many packages for data analysis, it lacks user-friendly data manipulation tools.
Methods:
To address this gap, we developed dsTidyverse, an implementation of selected functions from the popular Tidyverse package within the DataSHIELD client-server architecture. Disclosure checks were implemented to prevent individual-level data leakage.
Results:
This package provides functionality for selecting, renaming, and creating columns; conditional recoding; combining data frames by rows or columns; filtering and arranging rows; grouping and ungrouping data; and converting data frames to tibbles. Through examples, we demonstrate how dsTidyverse simplifies common data manipulation tasks within DataSHIELD.
Conclusions:
By providing additional data manipulation functionality, dsTidyverse improves the user experience and analytical efficiency within DataSHIELD. The package is open-source and freely available on CRAN and GitHub, and welcomes further development: https://github.com/molgenis/ds-tidyverse.
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