Scater: pre-processing, quality control, normalization and visualization of single-cell RNA-seq data in R
AuthorMcCarthy, DJ; Campbell, KR; Lun, ATL; Wills, QF
PublisherOXFORD UNIV PRESS
University of Melbourne Author/sMcCarthy, Davis
AffiliationSchool of Mathematics and Statistics
Document TypeJournal Article
CitationsMcCarthy, D. J., Campbell, K. R., Lun, A. T. L. & Wills, Q. F. (2017). Scater: pre-processing, quality control, normalization and visualization of single-cell RNA-seq data in R. BIOINFORMATICS, 33 (8), pp.1179-1186. https://doi.org/10.1093/bioinformatics/btw777.
Access StatusOpen Access
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: email@example.com. Supplementary information: Supplementary data are available at Bioinformatics online.
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