This package is for version 3.9 of Bioconductor; for the stable, up-to-date release version, see simpleSingleCell.
Bioconductor version: 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, cell cycle phase identification, doublet detection and batch correction. Procedures to detect highly variable genes, significantly correlated genes and subpopulation-specific marker genes are also shown. These analyses are demonstrated on publicly available scRNA-seq data sets from a variety of protocols including SMART-seq2 and 10X Genomics.
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")
):
To install this package, start R (version "3.6") 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.
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 |
biocViews | ImmunoOncologyWorkflow, SingleCellWorkflow, Workflow |
Version | 1.8.0 |
License | Artistic-2.0 |
Depends | |
Imports | BiocStyle, callr, rmarkdown |
LinkingTo | |
Suggests | knitr, readxl, R.utils, Matrix, SingleCellExperiment, scater, scran, DropletUtils, org.Hs.eg.db, org.Mm.eg.db, EnsDb.Hsapiens.v86, TxDb.Mmusculus.UCSC.mm10.ensGene, dynamicTreeCut, cluster, igraph, Rtsne, pheatmap, limma, edgeR, BiocParallel, BiocFileCache, BiocNeighbors, BiocSingular, batchelor, scRNAseq, TENxBrainData |
SystemRequirements | |
Enhances | |
URL | https://www.bioconductor.org/help/workflows/simpleSingleCell/ |
Depends On Me | |
Imports Me | |
Suggests Me | |
Links To Me |
Follow Installation instructions to use this package in your R session.
Source Package | simpleSingleCell_1.8.0.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 | https://bioconductor.org/packages/simpleSingleCell/ |
Package Downloads Report | Download Stats |
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