Bioconductor - singleCellTK
Bioconductor 3.22
Software Packages
singleCellTK
singleCellTK
This is the
released
version of singleCellTK; for the devel version, see
singleCellTK
Comprehensive and Interactive Analysis of Single Cell RNA-Seq Data
DOI:
10.18129/B9.bioc.singleCellTK
Bioconductor version:
Release (3.22)
The Single Cell Toolkit (SCTK) in the singleCellTK package provides an interface to popular tools for importing, quality control, analysis, and visualization of single cell RNA-seq data. SCTK allows users to seamlessly integrate tools from various packages at different stages of the analysis workflow. A general "a la carte" workflow gives users the ability access to multiple methods for data importing, calculation of general QC metrics, doublet detection, ambient RNA estimation and removal, filtering, normalization, batch correction or integration, dimensionality reduction, 2-D embedding, clustering, marker detection, differential expression, cell type labeling, pathway analysis, and data exporting. Curated workflows can be used to run Seurat and Celda. Streamlined quality control can be performed on the command line using the SCTK-QC pipeline. Users can analyze their data using commands in the R console or by using an interactive Shiny Graphical User Interface (GUI). Specific analyses or entire workflows can be summarized and shared with comprehensive HTML reports generated by Rmarkdown. Additional documentation and vignettes can be found at camplab.net/sctk.
Author:
Yichen Wang [aut]
ORCID: 0000-0003-4347-5199
, Irzam Sarfraz [aut]
ORCID: 0000-0001-8121-792X
, Rui Hong [aut], Yusuke Koga [aut], Salam Alabdullatif [aut], Nida Pervaiz [aut], David Jenkins [aut]
ORCID: 0000-0002-7451-4288
, Vidya Akavoor [aut], Xinyun Cao [aut], Shruthi Bandyadka [aut], Anastasia Leshchyk [aut], Tyler Faits [aut], Mohammed Muzamil Khan [aut], Zhe Wang [aut], W. Evan Johnson [aut]
ORCID: 0000-0002-6247-6595
, Ming Liu [aut], Joshua David Campbell [aut, cre]
ORCID: 0000-0003-0780-8662
Maintainer:
Joshua David Campbell
Citation (from within R, enter
citation("singleCellTK")
):
Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("singleCellTK")
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("singleCellTK")
1. Introduction to singleCellTK
HTML
R Script
Reference Manual
PDF
NEWS
Text
LICENSE
Text
Need some help? Ask on the Bioconductor Support site!
Details
biocViews
Alignment
BatchEffect
Clustering
DataImport
DifferentialExpression
GUI
GeneExpression
ImmunoOncology
Normalization
QualityControl
SingleCell
Software
Version
2.20.1
In Bioconductor since
BioC 3.7 (R-3.5) (8 years)
License
MIT + file
LICENSE
Depends
R (>= 4.0),
SummarizedExperiment
SingleCellExperiment
DelayedArray
Biobase
Imports
ape
anndata
AnnotationHub
batchelor
BiocParallel
celldex
colourpicker
colorspace
cowplot
cluster
ComplexHeatmap
data.table
DelayedMatrixStats
DESeq2
dplyr
DT
ExperimentHub
ensembldb
fields
ggplot2
ggplotify
ggrepel
ggtree
gridExtra
, grid,
GSVA
(>= 1.50.0),
GSVAdata
igraph
KernSmooth
limma
MAST
Matrix
(>= 1.6-1),
matrixStats
, methods,
msigdbr
multtest
plotly
plyr
ROCR
Rtsne
S4Vectors
scater
scMerge
(>= 1.2.0),
scran
Seurat
(>= 3.1.3),
shiny
shinyjs
SingleR
stringr
SoupX
sva
reshape2
shinyalert
circlize
enrichR
(>= 3.2),
celda
shinycssloaders
DropletUtils
scds
(>= 1.2.0),
reticulate
(>= 1.14), tools,
tximport
tidyr
eds
withr
GSEABase
R.utils
zinbwave
scRNAseq
(>= 2.0.2),
TENxPBMCData
yaml
rmarkdown
magrittr
scDblFinder
metap
VAM
(>= 0.5.3),
tibble
rlang
TSCAN
TrajectoryUtils
scuttle
, utils, stats,
zellkonverter
lifecycle
System Requirements
URL
Bug Reports
See More
Suggests
testthat
Rsubread
BiocStyle
knitr
lintr
spelling
org.Mm.eg.db
kableExtra
shinythemes
shinyBS
shinyjqui
shinyWidgets
shinyFiles
BiocGenerics
RColorBrewer
fastmap
(>= 1.1.0),
harmony
SeuratObject
optparse
Linking To
Enhances
Depends On Me
Imports Me
Suggests Me
celda
Links To Me
Build Report
Build Report
Package Archives
Follow
Installation
instructions to use this package in your R session.
Source Package
singleCellTK_2.20.1.tar.gz
Windows Binary (x86_64)
singleCellTK_2.20.1.zip
macOS Binary (x86_64)
singleCellTK_2.20.1.tgz
macOS Binary (arm64)
singleCellTK_2.20.1.tgz
Source Repository
git clone https://git.bioconductor.org/packages/singleCellTK
Source Repository (Developer Access)
git clone git@git.bioconductor.org:packages/singleCellTK
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