LSH-GAN enables in-silico generation of cells for small sample high dimensional scRNA-seq data

Autor: Snehalika Lall, Sumanta Ray, Sanghamitra Bandyopadhyay
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Communications Biology, Vol 5, Iss 1, Pp 1-9 (2022)
Druh dokumentu: article
ISSN: 2399-3642
DOI: 10.1038/s42003-022-03473-y
Popis: 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.
Databáze: Directory of Open Access Journals
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