Purpose When developing new types of tools for single-cell analyses, there is often a lack of datasets on which to quantitatively assess the performance. Results We developed dyngen, a multi-modality simulator of single cells. In dyngen, the biomolecular state of an in silico changes over time according to a predefined gene regulatory network. We used dyngen to benchmark three emerging ways of analysing single-cell data: RNA velocity, cell-specific network inference and trajectory alignment methods. Conclusion dyngen lays the foundations for benchmarking a wide variety of computational single-cell tools and can be used to help kick-start the development of future types of analyses.
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- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
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