Workflow Package: simpleSingleCell

A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor

Bioconductor version: 3.7

This workflow implements a low-level analysis pipeline for scRNA-seq data using scran, scater and other Bioconductor packages. It describes how to perform quality control on the libraries, normalization of cell-specific biases, basic data exploration and cell cycle phase identification. Procedures to detect highly variable genes, significantly correlated genes and subpopulation-specific marker genes are also shown. These analyses are demonstrated on a range of publicly available scRNA-seq data sets.

Author: Aaron Lun [aut, cre], Davis McCarthy [aut], John Marioni [aut]

Maintainer: Aaron Lun <alun at wehi.edu.au>

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("simpleSingleCell")

Documentation

To view available workflows for the version of this package installed in your system, start R and enter:

browseVignettes("simpleSingleCell")

 

HTML	R Script	Analyzing droplet-based scRNA-seq data
HTML	R Script	Analyzing scRNA-seq read count data
HTML	R Script	Analyzing scRNA-seq UMI count data
HTML	R Script	Correcting batch effects in scRNA-seq data
HTML	R Script	Further strategies for analyzing scRNA-seq data
HTML	R Script	Workflows for analyzing single-cell RNA-seq data with R/Bioconductor

Details

biocViews	SingleCellWorkflow, Workflow
Version	1.2.1
License	Artistic-2.0
Depends	R (>= 3.3.0), BiocStyle, knitr, BiocParallel, Rtsne, mvoutlier, destiny, readxl, gdata, SingleCellExperiment, scater, org.Mm.eg.db, scran, limma, pheatmap, dynamicTreeCut, cluster, edgeR, TxDb.Mmusculus.UCSC.mm10.ensGene, scRNAseq, DropletUtils
Imports
LinkingTo
Suggests	knitr, rmarkdown
SystemRequirements
Enhances
URL	https://www.bioconductor.org/help/workflows/simpleSingleCell/
Depends On Me
Imports Me
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Build Report