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bioRxiv · 10.1101/069633

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
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Abstract

MotivationSingle-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.\n\nResultsWe 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.\n\nAvailabilityThe open-source code, along with installation instructions, vignettes and case studies, is available through Bioconductor at http://bioconductor.org/packages/scater.\n\nSupplementary informationSupplementary material is available online at bioRxiv accompanying this manuscript, and all materials required to reproduce the results presented in this paper are available at dx.doi.org/10.5281/zenodo.60139.

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Davis J McCarthy, Kieran R Campbell, Aaron T L Lun, Quin F Wills. 2016-08-15. scater: pre-processing, quality control, normalisation and visualisation of single-cell RNA-seq data in R. https://doi.org/10.1101/069633

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