singleCellTK
This package is for version 3.17 of Bioconductor; for the stable, up-to-date release version, see singleCellTK.
Comprehensive and Interactive Analysis of Single Cell RNA-Seq Data
Bioconductor version: 3.17
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, cre] , 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] , Joshua David Campbell [aut]
Maintainer: Yichen Wang <wangych at bu.edu>
citation("singleCellTK")
):
Installation
To install this package, start R (version "4.3") 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 | ||
NEWS | Text | |
LICENSE | Text |
Details
biocViews | Alignment, BatchEffect, Clustering, DataImport, DifferentialExpression, GUI, GeneExpression, ImmunoOncology, Normalization, QualityControl, SingleCell, Software |
Version | 2.10.0 |
In Bioconductor since | BioC 3.7 (R-3.5) (6 years) |
License | MIT + file LICENSE |
Depends | R (>= 4.0), SummarizedExperiment, SingleCellExperiment, DelayedArray, Biobase |
Imports | ape, AnnotationHub, batchelor, BiocParallel, celldex, colourpicker, colorspace, cowplot, cluster, ComplexHeatmap, data.table, DelayedMatrixStats, DESeq2, dplyr, DT, ExperimentHub, ensembldb, fields, ggplot2, ggplotify, ggrepel, ggtree, gridExtra, GSVA(>= 1.26.0), GSVAdata, igraph, KernSmooth, limma, MAST, Matrix (>= 1.5-3), matrixStats, methods, msigdbr, multtest, plotly, plyr, ROCR, Rtsne, S4Vectors, scater, scMerge(>= 1.2.0), scran, Seurat (>= 3.1.3), shiny, shinyjs, SingleR, SoupX, sva, reshape2, shinyalert, circlize, enrichR, celda, shinycssloaders, DropletUtils, scds(>= 1.2.0), reticulate (>= 1.14), tools, tximport, 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 |
See More
Suggests | testthat, Rsubread, BiocStyle, knitr, lintr, spelling, org.Mm.eg.db, stringr, kableExtra, shinythemes, shinyBS, shinyjqui, shinyWidgets, shinyFiles, BiocGenerics, RColorBrewer, fastmap (>= 1.1.0), harmony |
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_2.10.0.tar.gz |
Windows Binary | singleCellTK_2.10.0.zip |
macOS Binary (x86_64) | singleCellTK_2.10.0.tgz |
macOS Binary (arm64) | singleCellTK_2.10.0.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 |
Old Source Packages for BioC 3.17 | Source Archive |