Generation of synthetic scRNA-seq-like transcriptomes using a generative adversarial network from RNA-seq data
Sujit Silas Armstrong Suthahar, Dan Ruan
This paper generates synthetic scRNA-seq-like transcriptomes from bulk RNA-seq data using a cycleGAN approach to bridge the resolution gap between bulk and single-cell transcriptomics.