Fast and accurate single-cell RNA-seq analysis by clustering of transcript-compatibility counts.
Genome Biol
; 17(1): 112, 2016 05 26.
Article
em En
| MEDLINE
| ID: mdl-27230763
ABSTRACT
Current approaches to single-cell transcriptomic analysis are computationally intensive and require assay-specific modeling, which limits their scope and generality. We propose a novel method that compares and clusters cells based on their transcript-compatibility read counts rather than on the transcript or gene quantifications used in standard analysis pipelines. In the reanalysis of two landmark yet disparate single-cell RNA-seq datasets, we show that our method is up to two orders of magnitude faster than previous approaches, provides accurate and in some cases improved results, and is directly applicable to data from a wide variety of assays.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Análise de Sequência de RNA
/
Perfilação da Expressão Gênica
/
Análise de Célula Única
/
Sequenciamento de Nucleotídeos em Larga Escala
Limite:
Animals
/
Humans
Idioma:
En
Revista:
Genome Biol
Assunto da revista:
BIOLOGIA MOLECULAR
/
GENETICA
Ano de publicação:
2016
Tipo de documento:
Article
País de afiliação:
Estados Unidos