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Surface protein imputation from single cell transcriptomes by deep neural networks

Author

Listed:
  • Zilu Zhou

    (University of Pennsylvania
    University of Pennsylvania)

  • Chengzhong Ye

    (Tsinghua University)

  • Jingshu Wang

    (The University of Chicago)

  • Nancy R. Zhang

    (University of Pennsylvania)

Abstract

While single cell RNA sequencing (scRNA-seq) is invaluable for studying cell populations, cell-surface proteins are often integral markers of cellular function and serve as primary targets for therapeutic intervention. Here we propose a transfer learning framework, single cell Transcriptome to Protein prediction with deep neural network (cTP-net), to impute surface protein abundances from scRNA-seq data by learning from existing single-cell multi-omic resources.

Suggested Citation

  • Zilu Zhou & Chengzhong Ye & Jingshu Wang & Nancy R. Zhang, 2020. "Surface protein imputation from single cell transcriptomes by deep neural networks," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-14391-0
    DOI: 10.1038/s41467-020-14391-0
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    Cited by:

    1. Daniel P. Arnold & Yaxin Xu & Sho C. Takatori, 2023. "Antibody binding reports spatial heterogeneities in cell membrane organization," Nature Communications, Nature, vol. 14(1), pages 1-13, December.

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