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A novel batch-effect correction method for scRNA-seq data based on Adversarial Information Factorization

Fig 2

Adversarial Information Factorization’s architecture (AIF).

The model comprises three blocks: the CVAE in blue, the GAN network in pink, and the auxiliary network in green. x is the original cell’s gene expression, y is the true batch label, is the latent vector, is the reconstructed cell’s gene expression, , , are the predicted batch labels based on x, and respectively.

Fig 2

doi: https://doi.org/10.1371/journal.pcbi.1011880.g002