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Protein velocity and acceleration from single-cell multiomics experiments.

Gennady Gorin1, Valentine Svensson2, Lior Pachter3

  • 1Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, USA.

Genome Biology
|February 20, 2020
PubMed
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This study introduces a new RNA velocity method to predict future cell states using simultaneous protein and RNA measurements. The protaccel software enables temporal analysis from single-cell experiments.

Area of Science:

  • Molecular Biology
  • Systems Biology
  • Bioinformatics

Background:

  • Simultaneous quantification of protein and RNA in single cells offers insights into cellular dynamics.
  • Inferring past, present, and future cell states requires advanced analytical methods.

Purpose of the Study:

  • To extend RNA velocity methods for temporal analysis using multimodal single-cell data.
  • To enable the extrapolation of cell states by integrating transcript and protein abundance estimates.

Main Methods:

  • Developed an extension of the RNA velocity method.
  • Leveraged estimates of unprocessed transcript and protein abundances.
  • Applied the model to six diverse single-cell datasets.

Main Results:

Keywords:
BioinformaticsComputational biologyMultiomicsProtein accelerationProtein velocityRNA velocityTranscriptomics

Related Experiment Videos

  • Demonstrated consistent cell landscapes and phase portraits across datasets.
  • Successfully extrapolated cell states using the extended RNA velocity approach.
  • Validated the model's efficacy in multimodal single-cell temporal analysis.

Conclusions:

  • The extended RNA velocity method provides a robust framework for inferring cell states over time.
  • The protaccel Python package facilitates the application of this novel temporal analysis technique.
  • This approach enhances the understanding of cellular dynamics from single experimental snapshots.