scAEGAN: Unification of single-cell genomics data by adversarial learning of latent space correspondences.

Recent progress in Single-Cell Genomics has produced different library protocols and techniques for molecular profiling. We formulate a unifying, data-driven, integrative, and predictive methodology for different libraries, samples, and paired-unpaired data modalities. Our design of scAEGAN includes...

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Bibliographic Details
Main Authors: Sumeer Ahmad Khan, Robert Lehmann, Xabier Martinez-de-Morentin, Alberto Maillo, Vincenzo Lagani, Narsis A Kiani, David Gomez-Cabrero, Jesper Tegner
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2023-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0281315