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scater: pre-processing, quality control, normalisation and visualisation of single-cell RNA-seq data in R

Davis J. McCarthy, Kieran R. Campbell, Aaron T. L. Lun, Quin F. Wills
doi: https://doi.org/10.1101/069633
Davis J. McCarthy
1European Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI), Hinxton CB10 1SD, United Kingdom;
2Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, United Kingdom;
5St Vincent’s Institute of Medical Research, 41 Victoria Parade, Fitzroy Victoria 3065, Australia;
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Kieran R. Campbell
2Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, United Kingdom;
4Department of Physiology, Anatomy and Genetics, University of Oxford, South Parks Road, Oxford OX1 3QX, United Kingdom;
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Aaron T. L. Lun
6CRUK Cambridge Institute, University of Cambridge, Robinson Way, Cambridge CB2 0RE, United Kingdom.
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Quin F. Wills
2Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, United Kingdom;
3Weatherall Institute for Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford OX3 9DS, United Kingdom;
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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 normalisation.

Results We have developed the R/Bioconductor package scater to facilitate rigorous pre-processing, quality control, normalisation and visualisation 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 The open-source code, along with installation instructions, vignettes and case studies, is available through Bioconductor at http://bioconductor.org/packages/scater.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted August 15, 2016.
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scater: pre-processing, quality control, normalisation and visualisation of single-cell RNA-seq data in R
Davis J. McCarthy, Kieran R. Campbell, Aaron T. L. Lun, Quin F. Wills
bioRxiv 069633; doi: https://doi.org/10.1101/069633
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scater: pre-processing, quality control, normalisation and visualisation of single-cell RNA-seq data in R
Davis J. McCarthy, Kieran R. Campbell, Aaron T. L. Lun, Quin F. Wills
bioRxiv 069633; doi: https://doi.org/10.1101/069633

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