This package is for version 3.10 of Bioconductor; for the stable, up-to-date release version, see singleCellTK.
Bioconductor version: 3.10
Run common single cell analysis directly through your browser including differential expression, downsampling analysis, and clustering.
Author: David Jenkins
Maintainer: David Jenkins <dfj at bu.edu>
Citation (from within R,
enter citation("singleCellTK")
):
To install this package, start R (version "3.6") and enter:
if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("singleCellTK")
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("singleCellTK")
HTML | R Script | 1. Introduction to singleCellTK |
HTML | R Script | 2. Processing and Visualizing Data in the Single Cell Toolkit |
Reference Manual | ||
Text | NEWS | |
Text | LICENSE |
biocViews | Alignment, Clustering, DifferentialExpression, GeneExpression, ImmunoOncology, SingleCell, Software |
Version | 1.6.0 |
In Bioconductor since | BioC 3.7 (R-3.5) (2 years) |
License | MIT + file LICENSE |
Depends | R (>= 3.5), SummarizedExperiment, SingleCellExperiment, DelayedArray, Biobase |
Imports | ape, colourpicker, cluster, ComplexHeatmap, data.table, DESeq2, DT, ggplot2, ggtree, gridExtra, GSVA(>= 1.26.0), GSVAdata, limma, MAST, matrixStats, methods, multtest, plotly, RColorBrewer, Rtsne, S4Vectors, shiny, shinyjs, shinyBS, sva, reshape2, AnnotationDbi, shinyalert, circlize, enrichR, celda, shinycssloaders, shinythemes, umap |
LinkingTo | |
Suggests | testthat, Rsubread, BiocStyle, knitr, lintr, bladderbatch, rmarkdown, org.Mm.eg.db, org.Hs.eg.db, scRNAseq, xtable, spelling, GSEABase |
SystemRequirements | |
Enhances | |
URL | https://compbiomed.github.io/sctk_docs/ |
BugReports | https://github.com/compbiomed/singleCellTK/issues |
Depends On Me | |
Imports Me | |
Suggests Me | |
Links To Me | |
Build Report |
Follow Installation instructions to use this package in your R session.
Source Package | singleCellTK_1.6.0.tar.gz |
Windows Binary | singleCellTK_1.6.0.zip (32- & 64-bit) |
Mac OS X 10.11 (El Capitan) | singleCellTK_1.6.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/singleCellTK |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/singleCellTK |
Package Short Url | https://bioconductor.org/packages/singleCellTK/ |
Package Downloads Report | Download Stats |
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