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SUMO: an R package for simulating multi-omics data for methods development and testing
Bernard Isekah Osang'ir1,2, Surya Gupta1, Ziv Shkedy2
1Microbiology Unit, Nuclear Medical Applications, Belgian Nuclear Research Centre, SCK CEN, Boeretang 190, Mol, 2400, Belgium.
Motivation:
Insights from integrative multi-omics analyses have fueled demand for innovative computational methods and tools in multi-omics research. However, the scarcity of multi-omics datasets with user-defined signal structures hinders the evaluation of these newly developed tools. SUMO (SimUlating Multi-Omics), an open-source R package, was developed to address this gap by enabling the generation of high-quality factor analysis-based datasets with full control over the dataset's structure such as latent structures, noise, and complexity. Users can configure datasets with distinct and/or shared non-overlapping latent factors, enabling flexible and precise control over the signal structures. Consequently, SUMO allows reproducible testing and validation of methods, fostering methodological innovation.
Availability And Implementation:
The SUMO R package is freely available and accessible on the Comprehensive R Archive Network https://doi.org/10.32614/CRAN.package.SUMO and on GitHub https://github.com/lucp12891/SUMO.git under CC-BY 4.0 license.
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