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 BioconductorBioconductor version: Release (3.21)
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 (from within R, entercitation("simpleSingleCell")
): Installation
To install this package, start R (version "4.5") 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.
DocumentationTo 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 See More Package Archives
Follow Installation instructions to use this package in your R session.
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