singleCellTK

This is the released version of singleCellTK; for the devel version, see singleCellTK.

Comprehensive and Interactive Analysis of Single Cell RNA-Seq Data

Bioconductor version: Release (3.20)

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] , Irzam Sarfraz [aut] , Rui Hong [aut], Yusuke Koga [aut], Salam Alabdullatif [aut], Nida Pervaiz [aut], David Jenkins [aut] , 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] , Ming Liu [aut], Joshua David Campbell [aut, cre]

Maintainer: Joshua David Campbell <camp at bu.edu>

Citation (from within R, enter citation("singleCellTK")):

Installation

To install this package, start R (version "4.4") 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	2.16.0
In Bioconductor since	BioC 3.7 (R-3.5) (6.5 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
System Requirements
URL	https://www.camplab.net/sctk/
Bug Reports	https://github.com/compbiomed/singleCellTK/issues

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_2.16.0.tar.gz
Windows Binary (x86_64)	singleCellTK_2.16.0.zip (64-bit only)
macOS Binary (x86_64)	singleCellTK_2.16.0.tgz
macOS Binary (arm64)	singleCellTK_2.15.2.tgz
Source Repository	git clone https://git.bioconductor.org/packages/singleCellTK
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/singleCellTK
Bioc Package Browser	https://code.bioconductor.org/browse/singleCellTK/
Package Short Url	https://bioconductor.org/packages/singleCellTK/
Package Downloads Report	Download Stats