Surface protein imputation from single cell transcriptomes by deep neural networks.
other · Level V
Where this comes from
- Record sourced from PubMed, PMID 32005835.
- Also identified by DOI 10.1038/s41467-020-14391-0 and PMC identifier 6994606.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
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.
Medical subject headings
- Cells
- Gene Expression Profiling
- Membrane Proteins
- Single-Cell Analysis
- Transcriptome