simpleSingleCell

 

This is the development version of simpleSingleCell; for the stable release version, see simpleSingleCell.

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

Bioconductor version: Development (3.9)

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>

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

Installation

To install this package, start R (version "3.6") and enter:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("simpleSingleCell", version = "3.9")

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. Detecting differential expression
HTML R Script 11. Scalability for big data
HTML R Script 12. Further analysis strategies

Details

biocViews ImmunoOncologyWorkflow, SingleCellWorkflow, Workflow
Version 1.7.13
License Artistic-2.0
Depends
Imports BiocStyle, callr, rmarkdown
LinkingTo
Suggests knitr, BiocParallel, Rtsne, readxl, SingleCellExperiment, scater, org.Mm.eg.db, scran, limma, pheatmap, dynamicTreeCut, cluster, edgeR, TxDb.Mmusculus.UCSC.mm10.ensGene, scRNAseq, DropletUtils, BiocFileCache, BiocNeighbors, TENxBrainData, DelayedMatrixStats
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_1.7.13.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

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