simpleSingleCell

This package is for version 3.7 of Bioconductor; for the stable, up-to-date release version, see 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>

Citation (from within R, enter citation("simpleSingleCell")):

Installation

To install this package, start R (version "3.5") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("simpleSingleCell")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

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

browseVignettes("simpleSingleCell")
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 HTML R Script

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
System Requirements
URL https://www.bioconductor.org/help/workflows/simpleSingleCell/
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Suggests knitr, rmarkdown
Linking To
Enhances
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package simpleSingleCell_1.2.1.tar.gz
Windows Binary
Mac OS X 10.11 (El Capitan)
Source Repository git clone https://git.bioconductor.org/packages/simpleSingleCell
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/simpleSingleCell
Package Short Url https://bioconductor.org/packages/simpleSingleCell/
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