Interpretable dimensionality reduction of single cell transcriptome data with deep generative models
Although single-cell transcriptome data are increasingly available, their interpretation remains a challenge. Here, the authors present a dimensionality reduction approach that preserves both the local and global neighbourhood structures in the data thus enhancing its interpretability.
Guardado en:
| Autores principales: | , , |
|---|---|
| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2018
|
| Materias: | |
| Acceso en línea: | https://doaj.org/article/374e2f7ee4b743cebc2a0022380ea83b |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|