Scater: pre-processing, quality control, normalization and visualization of single-cell RNA-seq data in R.
IF: 0
Cited by: 373


Single-cell RNA sequencing (scRNA-seq) is increasingly used to study gene expression at the level of individual cells. However, preparing raw sequence data for further analysis is not a straightforward process. Biases, artifacts and other sources of unwanted variation are present in the data, requiring substantial time and effort to be spent on pre-processing, quality control (QC) and normalization. We have developed the R/Bioconductor package scater to facilitate rigorous pre-processing, quality control, normalization and visualization of scRNA-seq data. The package provides a convenient, flexible workflow to process raw sequencing reads into a high-quality expression dataset ready for downstream analysis. scater provides a rich suite of plotting tools for single-cell data and a flexible data structure that is compatible with existing tools and can be used as infrastructure for future software development. The open-source code, along with installation instructions, vignettes and case studies, is available through Bioconductor at . [email protected] Supplementary data are available at Bioinformatics online.


Gene Expression

MeSH terms

Cell Line
Principal Component Analysis
Programming Languages
Quality Control
Sequence Analysis, RNA
Single-Cell Analysis
Statistics as Topic


McCarthy, Davis J
Campbell, Kieran R
Lun, Aaron T L
Wills, Quin F

Recommend literature

Similar data