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Spearheading future omics analyses using dyngen, a multi-modal simulator of single cells
Robrecht Cannoodt1,2,3, Wouter Saelens1,2,4, Louise Deconinck1,2
1Data Mining and Modelling for Biomedicine group, VIB Center for Inflammation Research, Ghent, Belgium.
Nature Communications
|June 25, 2021
Summary
We developed dyngen, a flexible simulation engine for dynamic single-cell processes. It aids computational method development for cell trajectory alignment, network inference, and RNA velocity estimation.
Area of Science:
- Computational Biology
- Systems Biology
- Single-cell Analysis
Background:
- Dynamic cellular processes are complex.
- Current simulation tools lack flexibility.
- Developing robust computational methods is crucial.
Purpose of the Study:
- Introduce dyngen, a novel multi-modal simulation engine.
- Enhance flexibility for single-cell data simulation.
- Facilitate computational method development and benchmarking.
Main Methods:
- Developed dyngen, a multi-modal simulation engine.
- Designed for single-cell resolution of dynamic processes.
- Validated through applications in trajectory alignment, network inference, and RNA velocity estimation.
Main Results:
- dyngen offers greater flexibility than existing engines.
- Demonstrated potential in aligning cell developmental trajectories.
- Showcased utility in cell-specific regulatory network inference and RNA velocity estimation.
Conclusions:
- dyngen advances computational method development for single-cell biology.
- Enables rigorous testing and benchmarking of new algorithms.
- Spurs innovation in analyzing dynamic cellular systems.
