Biophysical modeling with variational autoencoders for bimodal, single-cell RNA sequencing data.
Nat Methods
; 21(8): 1466-1469, 2024 Aug.
Article
em En
| MEDLINE
| ID: mdl-39054391
ABSTRACT
Here we present biVI, which combines the variational autoencoder framework of scVI with biophysical models describing the transcription and splicing kinetics of RNA molecules. We demonstrate on simulated and experimental single-cell RNA sequencing data that biVI retains the variational autoencoder's ability to capture cell type structure in a low-dimensional space while further enabling genome-wide exploration of the biophysical mechanisms, such as system burst sizes and degradation rates, that underlie observations.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Análise de Sequência de RNA
/
Análise de Célula Única
Limite:
Humans
Idioma:
En
Revista:
Nat Methods
Assunto da revista:
TECNICAS E PROCEDIMENTOS DE LABORATORIO
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
Estados Unidos