LSH-GAN enables in-silico generation of cells for small sample high dimensional scRNA-seq data
oleh: Snehalika Lall, Sumanta Ray, Sanghamitra Bandyopadhyay
| Format: | Article |
|---|---|
| Diterbitkan: | Nature Portfolio 2022-06-01 |
Deskripsi
LSH-GAN is a locality-sensitive hashing based generative adversarial model that can produce realistic cell samples from small sample single-cell scRNA-seq data. The generated cells can be utilized for downstream analysis, like gene selection and cell clustering.