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systemPipeR: a multipurpose workflow management system for reproducible data analysis
Le Zhang1, Daniela Cassol1, Brendan Gongol1
1Institute for Integrative Genome Biology, University of California, Riverside, 1207F Genomics Building, Riverside, CA 92521, United States.
Abstract:
Workflow management systems (WMS) are essential for creating and automating multi-step data analyses and ensuring the reproducibility of biological insights. Although numerous WMS solutions exist, few provide deep integration of command-line software with the R and Bioconductor ecosystems, where a substantial portion of statistical modeling and downstream scientific analysis is performed by a large user base. systemPipeR addresses this gap by offering a unified environment that links R-based analytical steps with command-line tools through a standardized workflow specification. It enables the design and execution of reproducible workflows on both local and high-performance computing systems, while allowing users to select the most appropriate R or command-line tool for each analysis step. The latest version introduces a fully redesigned architecture that streamlines workflow construction, execution, monitoring, and reporting. Key enhancements include a flexible workflow management class object, integration of the Common Workflow Language (CWL), formal declaration and standardized execution of both R and command-line steps, utilities for metadata management, and automated generation of scientific and technical reports. Together, these advances establish systemPipeR as a general-purpose R-based WMS for building and executing end-to-end workflows for reproducible analysis of complex data in genomics and other data-intensive fields. The software is distributed as a free open-source Bioconductor package (https://bioconductor.org/packages/systemPipeR).
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