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MACHINE LEARNING

Bayesian deep learning for single-cell analysis

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A recent approach for single-cell RNA-sequencing data uses Bayesian deep learning to correct technical artifacts and enable accurate and multifaceted downstream analyses.

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Fig. 1: scVI is a multifaceted tool for scRNA-seq data processing and analysis.

Kim Caesar/Springer Nature

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Authors and Affiliations

  1. Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Gregory P. Way & Casey S. Greene

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  1. Gregory P. Way
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  2. Casey S. Greene
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Correspondence to Casey S. Greene.

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The authors declare no competing interests.

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Way, G.P., Greene, C.S. Bayesian deep learning for single-cell analysis. Nat Methods 15, 1009–1010 (2018). https://doi.org/10.1038/s41592-018-0230-9

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