Journal
NATURE COMMUNICATIONS
Volume 12, Issue 1, Pages -Publisher
NATURE PORTFOLIO
DOI: 10.1038/s41467-021-24152-2
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Funding
- Chan Zuckerberg Initiative DAF, an advised fund of Silicon Valley Community Foundation [2020-218899]
- Flemish Government
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dyngen is a multi-modal simulation engine that allows the study of dynamic cellular processes at single-cell resolution, offering more flexibility than current single-cell simulation engines. It has demonstrated potential in spearheading computational methods for aligning cell developmental trajectories, cell-specific regulatory network inference, and estimation of RNA velocity.
We present dyngen, a multi-modal simulation engine for studying dynamic cellular processes at single-cell resolution. dyngen is more flexible than current single-cell simulation engines, and allows better method development and benchmarking, thereby stimulating development and testing of computational methods. We demonstrate its potential for spearheading computational methods on three applications: aligning cell developmental trajectories, cell-specific regulatory network inference and estimation of RNA velocity. To benchmark single cell bioinformatics tools, data simulators can provide a robust ground truth. Here the authors present dyngen, a multi-modal simulator, and apply it to aligning cell developmental trajectories, cell-specific regulatory network inference and estimation of RNA velocity.
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