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Spearheading future omics analyses using dyngen, a multi-modal simulator of single cells

Author

Listed:
  • Robrecht Cannoodt

    (VIB Center for Inflammation Research
    Ghent University
    Data Intuitive)

  • Wouter Saelens

    (VIB Center for Inflammation Research
    Ghent University
    École Polytechnique Fédérale de Lausanne (EPFL))

  • Louise Deconinck

    (VIB Center for Inflammation Research
    Ghent University)

  • Yvan Saeys

    (VIB Center for Inflammation Research
    Ghent University)

Abstract

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.

Suggested Citation

  • Robrecht Cannoodt & Wouter Saelens & Louise Deconinck & Yvan Saeys, 2021. "Spearheading future omics analyses using dyngen, a multi-modal simulator of single cells," Nature Communications, Nature, vol. 12(1), pages 1-9, December.
    • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-24152-2
    DOI: 10.1038/s41467-021-24152-2
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    Cited by:

    1. Reiichi Sugihara & Yuki Kato & Tomoya Mori & Yukio Kawahara, 2022. "Alignment of single-cell trajectory trees with CAPITAL," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    2. Yue Cao & Pengyi Yang & Jean Yee Hwa Yang, 2021. "A benchmark study of simulation methods for single-cell RNA sequencing data," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
    3. Xin Tang & Jiawei Zhang & Yichun He & Xinhe Zhang & Zuwan Lin & Sebastian Partarrieu & Emma Bou Hanna & Zhaolin Ren & Hao Shen & Yuhong Yang & Xiao Wang & Na Li & Jie Ding & Jia Liu, 2023. "Explainable multi-task learning for multi-modality biological data analysis," Nature Communications, Nature, vol. 14(1), pages 1-19, December.

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