simpleSingleCell

 

This package is for version 3.8 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: 3.8

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 <infinite.monkeys.with.keyboards at gmail.com>

Installation

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

if (!requireNamespace("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")

 

HTML	R Script	01. Introduction
HTML	R Script	02. Read count data
HTML	R Script	03. UMI count data
HTML	R Script	04. Droplet-based data
HTML	R Script	05. Correcting batch effects
HTML	R Script	06. Quality control details
HTML	R Script	07. Spike-in normalization
HTML	R Script	08. Detecting doublets
HTML	R Script	09. Advanced variance modelling
HTML	R Script	10. Scalability for big data
HTML	R Script	11. Further analysis strategies

Details

biocViews	ImmunoOncologyWorkflow, SingleCellWorkflow, Workflow
Version	1.4.1
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, BiocFileCache, BiocNeighbors, TENxBrainData
Imports
LinkingTo
Suggests	knitr, rmarkdown
SystemRequirements
Enhances
URL	https://www.bioconductor.org/help/workflows/simpleSingleCell/
Depends On Me
Imports Me
Suggests Me
Links To Me

Package Archives

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

Source Package	simpleSingleCell_1.4.1.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	http://bioconductor.org/packages/simpleSingleCell/
Package Downloads Report	Download Stats