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Scater: pre-processing, quality control, normalization and visualization of single-cell RNA-seq data in R

2016· article· en· 2,053 citations· W2951158909 on OpenAlex· 10.1093/bioinformatics/btw777

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Abstract

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.

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The record

Venue
Bioinformatics
Topic
Single-cell and spatial transcriptomics
Field
Biochemistry, Genetics and Molecular Biology
Canadian institutions
Funders
National Health and Medical Research CouncilMedical Research Council CanadaCancer Research UKMedical Research CouncilEuropean Molecular Biology Laboratory
Keywords
Normalization (sociology)VisualizationComputer scienceRNA-SeqSoftwareComputational biologyData miningBiologyTranscriptomeGeneticsGene expressionProgramming languageGene
Has abstract in OpenAlex
yes