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>
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")| 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 | HTML | R Script |
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 | |
| System Requirements | |
| URL | https://www.bioconductor.org/help/workflows/simpleSingleCell/ |
See More
| Suggests | knitr, rmarkdown |
| Linking To | |
| Enhances | |
| 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 [email protected]:packages/simpleSingleCell |
| Package Short Url | https://bioconductor.org/packages/simpleSingleCell/ |
| Package Downloads Report | Download Stats |