simpleSingleCell
This is the released version of simpleSingleCell; for the devel version, see simpleSingleCell.
A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor
Bioconductor version: Release (3.23)
Once a proud workflow package, this is now a shell of its former self. Almost all of its content has been cannibalized for use in the "Orchestrating Single-Cell Analyses with Bioconductor" book at https://osca.bioconductor.org. Most vignettes here are retained as reminders of the glory that once was, also providing redirection for existing external links to the relevant OSCA book chapters.
Author: Aaron Lun [aut, cre], Davis McCarthy [aut], John Marioni [aut]
Maintainer: Aaron Lun <infinite.monkeys.with.keyboards at gmail.com>
citation("simpleSingleCell")):
Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, Bravo HC, Davis S, Gatto L, Girke T, Gottardo R, Hahne F, Hansen KD, Irizarry RA, Lawrence M, Love MI, MacDonald J, Obenchain V, Oleś AK, Pagès H, Reyes A, Shannon P, Smyth GK, Tenenbaum D, Waldron L, Morgan M (2015). "Orchestrating high-throughput genomic analysis with Bioconductor." Nature Methods, 12(2), 115–121. doi:10.1038/nmeth.3252.
Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JYH, Zhang J (2004). "Bioconductor: open software development for computational biology and bioinformatics." Genome Biology, 5(10), R80. doi:10.1186/gb-2004-5-10-r80.
Installation
To install this package, start R (version "4.6") 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 | |
| 02. Read count data | HTML | |
| 03. UMI count data | HTML | |
| 04. Droplet-based data | HTML | |
| 05. Correcting batch effects | HTML | |
| 06. Quality control details | HTML | |
| 07. Spike-in normalization | HTML | |
| 08. Detecting doublets | HTML | |
| 09. Advanced variance modelling | HTML | |
| 10. Detecting differential expression | HTML | |
| 11. Advanced batch correction | HTML | |
| 12. Scalability for big data | HTML | |
| 13. Further analysis strategies | HTML | R Script |
Details
| biocViews | ImmunoOncologyWorkflow, SingleCellWorkflow, Workflow |
| Version | 1.36.0 |
| License | Artistic-2.0 |
| Depends | |
| Imports | utils, methods, knitr, callr, rmarkdown, CodeDepends, BiocStyle |
| System Requirements | |
| URL | https://www.bioconductor.org/help/workflows/simpleSingleCell/ |
See More
| Suggests | readxl, R.utils, SingleCellExperiment, scater, scran, limma, BiocFileCache, org.Mm.eg.db |
| 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_1.36.0.tar.gz |
| Windows Binary (x86_64) | |
| macOS Binary (big-sur-x86_64) | |
| macOS Binary (sonoma-arm64) | |
| 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/ |
| Package Downloads Report | Download Stats |