Pseudocell Tracer—A method for inferring dynamic trajectories using scRNAseq and its application to B cells undergoing immunoglobulin class switch recombination
Fig 3
Pseudocell Tracer efficiently integrates adjacent biological information and accurately simulates gene expression profiles in pseudocells.
(A) Overview of neural network model combining a supervised autoencoder with a conditional GAN. (B) UMAP visualization of the input and output used in the supervised autoencoder; encoder (top) and decoder (bottom). (C) Scatter plot between observed and predicted expression values on held out cells. r denotes Pearson correlation between ground truth and predicted values. Isotype expression (left) and example CSR genes (right). (D) UMAP visualization applied to cGAN prediction and subsequent output from decoder.