singleCellTK

DOI:10.18129/B9.bioc.singleCellTK

This is thedevelopmentversion of singleCellTK; for the stable release version, seesingleCellTK.

Comprehensive and Interactive Analysis of Single Cell RNA-Seq Data

Bioconductor version: Development (3.16)

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], 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

Citation (from within R, entercitation("singleCellTK")):

Installation

To install this package, start R (version "4.2") and enter:

if (!require("BiocManager", quietly = TRUE)) install.packages("BiocManager") # The following initializes usage of Bioc devel BiocManager::install(version='devel') BiocManager::install("singleCellTK")

For older versions of R, please refer to the appropriateBioconductor release.

Documentation

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
PDF Reference Manual
Text NEWS
Text LICENSE

Details

biocViews Alignment,BatchEffect,Clustering,DataImport,DifferentialExpression,GUI,GeneExpression,ImmunoOncology,Normalization,QualityControl,SingleCell,Software
Version 2.7.0
In Bioconductor since BioC 3.7 (R-3.5) (4.5 years)
License MIT + fileLICENSE
Depends R (>= 4.0),SummarizedExperiment,SingleCellExperiment,DelayedArray,Biobase
Imports ape,batchelor,BiocParallel,celldex,colourpicker,colorspace,cowplot,集群,ComplexHeatmap,data.table,DelayedMatrixStats,DESeq2,dplyr,DT,ExperimentHub,fields,ggplot2,ggplotify,ggrepel,ggtree,gridExtra,GSVA(>= 1.26.0),GSVAdata,igraph,KernSmooth,limma,MAST,Matrix,matrixStats, methods,msigdbr,multtest,plotly,plyr,ROCR,Rtsne,S4Vectors,scater,scMerge(>= 1.2.0),scran,Seurat(>= 3.1.3),史ny,史nyjs,SingleR,SoupX,sva,reshape2,史nyalert,circlize,enrichR,celda,史nycssloaders,DropletUtils,scds(>= 1.2.0),reticulate(>= 1.14), tools,tximport,fishpond,withr,GSEABase,R.utils,zinbwave,scRNAseq(>= 2.0.2),TENxPBMCData,yaml,rmarkdown,magrittr,scDblFinder,metap,VAM(>= 0.5.3),tibble,rlang,TSCAN,TrajectoryUtils,generics,scuttle, utils, stats
LinkingTo
Suggests testthat,Rsubread,BiocStyle,knitr,lintr,spelling,org.Mm.eg.db,stringr,kableExtra,史nythemes,史nyBS,史nyjqui,史nyWidgets,史nyFiles,BiocGenerics,RColorBrewer,fastmap(>= 1.1.0)
SystemRequirements
Enhances
URL https://www.camplab.net/sctk/
BugReports https://github.com/compbiomed/singleCellTK/issues
Depends On Me
Imports Me
Suggests Me celda
Links To Me
Build Report

Package Archives

Followbob 体育网址 指令使用这个package in your R session.

Source Package singleCellTK_2.7.0.tar.gz
Windows Binary singleCellTK_2.7.0.zip(64-bit only)
macOS 10.13 (High Sierra)
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 //www.anjoumacpherson.com/packages/singleCellTK/
Package Downloads Report Download Stats

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