SciBet as a portable and fast single cell type identifier
The increasing size of single cell sequencing data sets calls for scalable cell annotation methods. Here, the authors introduce SciBet, which uses a multinomial distribution model and maximum likelihood estimation for fast and accurate single cell identification.
Enregistré dans:
| Auteurs principaux: | , , , , , , , |
|---|---|
| Format: | article |
| Langue: | EN |
| Publié: |
Nature Portfolio
2020
|
| Sujets: | |
| Accès en ligne: | https://doaj.org/article/c160ac1e1a1e4a25b0baef251f5258dd |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
| Résumé: | The increasing size of single cell sequencing data sets calls for scalable cell annotation methods. Here, the authors introduce SciBet, which uses a multinomial distribution model and maximum likelihood estimation for fast and accurate single cell identification. |
|---|