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dyngen: a multi-modal simulator for spearheading new single-cell omics analyses

View ORCID ProfileRobrecht Cannoodt, View ORCID ProfileWouter Saelens, View ORCID ProfileLouise Deconinck, View ORCID ProfileYvan Saeys
doi: https://doi.org/10.1101/2020.02.06.936971
Robrecht Cannoodt
1Ghent University
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  • For correspondence: robrecht.cannoodt@gmail.com
Wouter Saelens
1Ghent University
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Louise Deconinck
1Ghent University
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Yvan Saeys
1Ghent University
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Abstract

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.

Footnotes

  • Added notification that the results of Figure 4A are currently being revised.

  • https://github.com/dynverse/dyngen_manuscript

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted February 27, 2020.
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dyngen: a multi-modal simulator for spearheading new single-cell omics analyses
Robrecht Cannoodt, Wouter Saelens, Louise Deconinck, Yvan Saeys
bioRxiv 2020.02.06.936971; doi: https://doi.org/10.1101/2020.02.06.936971
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dyngen: a multi-modal simulator for spearheading new single-cell omics analyses
Robrecht Cannoodt, Wouter Saelens, Louise Deconinck, Yvan Saeys
bioRxiv 2020.02.06.936971; doi: https://doi.org/10.1101/2020.02.06.936971

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