Beta-Poisson model for single-cell RNA-seq data analyses.
Bioinformatics
; 32(14): 2128-35, 2016 07 15.
Article
en En
| MEDLINE
| ID: mdl-27153638
ABSTRACT
MOTIVATION Single-cell RNA-sequencing technology allows detection of gene expression at the single-cell level. One typical feature of the data is a bimodality in the cellular distribution even for highly expressed genes, primarily caused by a proportion of non-expressing cells. The standard and the over-dispersed gamma-Poisson models that are commonly used in bulk-cell RNA-sequencing are not able to capture this property. RESULTS:
We introduce a beta-Poisson mixture model that can capture the bimodality of the single-cell gene expression distribution. We further integrate the model into the generalized linear model framework in order to perform differential expression analyses. The whole analytical procedure is called BPSC. The results from several real single-cell RNA-seq datasets indicate that â¼90% of the transcripts are well characterized by the beta-Poisson model; the model-fit from BPSC is better than the fit of the standard gamma-Poisson model in > 80% of the transcripts. Moreover, in differential expression analyses of simulated and real datasets, BPSC performs well against edgeR, a conventional method widely used in bulk-cell RNA-sequencing data, and against scde and MAST, two recent methods specifically designed for single-cell RNA-seq data. AVAILABILITY AND IMPLEMENTATION An R package BPSC for model fitting and differential expression analyses of single-cell RNA-seq data is available under GPL-3 license at https//github.com/nghiavtr/BPSC CONTACT yudi.pawitan@ki.se or mattias.rantalainen@ki.se SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Texto completo:
1
Bases de datos:
MEDLINE
Asunto principal:
Análisis de Secuencia de ARN
/
Perfilación de la Expresión Génica
/
Análisis de la Célula Individual
Idioma:
En
Revista:
Bioinformatics
Asunto de la revista:
INFORMATICA MEDICA
Año:
2016
Tipo del documento:
Article
País de afiliación:
Suecia