LSH-GAN enables in-silico generation of cells for small sample high dimensional scRNA-seq data
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A new method, LSH-GAN, has been developed for generating cells in silico, which can be used for small sample high dimensional single-cell RNA sequencing data. This approach utilizes generative adversarial networks to produce realistic data. The method appears to enable the augmentation of single-cell RNA-seq data.