TY  - JOUR
AU  - McCarthy, DJ
AU  - Campbell, KR
AU  - Lun, ATL
AU  - Wills, QF
Y2  - 2020/12/10
Y1  - 2017/04/15
SN  - 1367-4803
UR  - http://hdl.handle.net/11343/253455
AB  - Motivation: 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. Results: 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. Availability and Implementation: The open-source code, along with installation instructions, vignettes and case studies, is available through Bioconductor at http://bioconductor.org/packages/scater . Contact: davis@ebi.ac.uk. Supplementary information: Supplementary data are available at Bioinformatics online.
LA  - English
PB  - OXFORD UNIV PRESS
T1  - Scater: pre-processing, quality control, normalization and visualization of single-cell RNA-seq data in R
DO  - 10.1093/bioinformatics/btw777
IS  - Bioinformatics
VL  - 33
IS  - 8
SP  - 1179-1186
L1  - /bitstream/handle/11343/253455/PMC5408845.pdf?sequence=1&isAllowed=y
ER  -