LifestyleUnlocking the Future: Raman2RNA Predicts Single-Cell RNA Expression in Live Cells

Unlocking the Future: Raman2RNA Predicts Single-Cell RNA Expression in Live Cells

Data availability

Raw data for the mouse reprogramming scRNA-seq are available for download from NCBI Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo) under project number: GSE122662. mES cell differentiation scRNA-seq data are available publicly20. All other data are available at google.com/storage/browser/raman2rna”>https://console.cloud.google.com/storage/browser/raman2rna.

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Code availability

Code for R2R are available at https://github.com/kosekijkk/raman2rna. Control software for the multimodal Raman microscope are available at https://github.com/kosekijkk/multimodal-raman-acq.

References

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  3. Schiebinger, G. et al. Optimal-transport analysis of single-cell gene expression identifies developmental trajectories in reprogramming. Cell 176, 928–943.e22 (2019). Article CAS PubMed PubMed Central Article 
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  5. Chen, W. et al. Live-seq enables temporal transcriptomic recording of single cells. Nature https://doi.org/10.1038/s41586-022-05046-9 (2022).

  6. Kobayashi-Kirschvink, K. J. et al. Linear regression links transcriptomic data and cellular Raman spectra.

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