Surface protein imputation from single cell transcriptomes by deep neural networks

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 c ell T ranscriptome to P rotein prediction with deep neural net work (cTP-net), to impute surface protein abundances from scRNA-seq data by learning from existing single-cell multi-omic resources.