Alevin efficiently estimates accurate gene abundances from dscRNA-seq data.
Genome Biol
; 20(1): 65, 2019 03 27.
Article
em En
| MEDLINE
| ID: mdl-30917859
ABSTRACT
We introduce alevin, a fast end-to-end pipeline to process droplet-based single-cell RNA sequencing data, performing cell barcode detection, read mapping, unique molecular identifier (UMI) deduplication, gene count estimation, and cell barcode whitelisting. Alevin's approach to UMI deduplication considers transcript-level constraints on the molecules from which UMIs may have arisen and accounts for both gene-unique reads and reads that multimap between genes. This addresses the inherent bias in existing tools which discard gene-ambiguous reads and improves the accuracy of gene abundance estimates. Alevin is considerably faster, typically eight times, than existing gene quantification approaches, while also using less memory.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Software
/
Análise de Sequência de RNA
/
Análise de Célula Única
Tipo de estudo:
Evaluation_studies
Limite:
Animals
/
Humans
Idioma:
En
Revista:
Genome Biol
Assunto da revista:
BIOLOGIA MOLECULAR
/
GENETICA
Ano de publicação:
2019
Tipo de documento:
Article
País de afiliação:
Estados Unidos