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: | Chenwei Li, Baolin Liu, Boxi Kang, Zedao Liu, Yedan Liu, Changya Chen, Xianwen Ren, Zemin Zhang |
---|---|
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!
|
Documents similaires
-
Author Correction: SciBet as a portable and fast single cell type identifier
par: Chenwei Li, et autres
Publié: (2021) -
An entropy-based metric for assessing the purity of single cell populations
par: Baolin Liu, et autres
Publié: (2020) -
SciELO Chile
par: Caro Letelier,Jorge
Publié: (2007) -
“Betting on nature” or “betting on others”: anti-coordination induces uniquely high levels of entropy
par: Gabriele Chierchia, et autres
Publié: (2018) -
Uncertainty Quantification in Brain Stimulation using UncertainSCI
par: Jess Tate, et autres
Publié: (2021)