scAEGAN: Unification of Single-Cell Genomics Data by Adversarial Learning of Latent Space Correspondences
Sameer Ahmad Khan, Robert Lehmann, Xabier Martinez‐de‐Morentin, Albert Malillo Ruiz, Vincenzo Lagani, Narsis A. Kiani, David Gómez-Cabrero, Jesper N. Tegner
scAEGAN unifies single-cell genomics data by adversarial learning of latent space correspondences, outperforming existing methods in integration and prediction tasks.
PLoS ONE · Feb 3, 2023Peer-reviewedBioinformatics