scde

DOI: 10.18129/B9.bioc.scde  

Single Cell Differential Expression

Bioconductor version: Release (3.16)

The scde package implements a set of statistical methods for analyzing single-cell RNA-seq data. scde fits individual error models for single-cell RNA-seq measurements. These models can then be used for assessment of differential expression between groups of cells, as well as other types of analysis. The scde package also contains the pagoda framework which applies pathway and gene set overdispersion analysis to identify and characterize putative cell subpopulations based on transcriptional signatures. The overall approach to the differential expression analysis is detailed in the following publication: "Bayesian approach to single-cell differential expression analysis" (Kharchenko PV, Silberstein L, Scadden DT, Nature Methods, doi: 10.1038/nmeth.2967). The overall approach to subpopulation identification and characterization is detailed in the following pre-print: "Characterizing transcriptional heterogeneity through pathway and gene set overdispersion analysis" (Fan J, Salathia N, Liu R, Kaeser G, Yung Y, Herman J, Kaper F, Fan JB, Zhang K, Chun J, and Kharchenko PV, Nature Methods, doi:10.1038/nmeth.3734).

Author: Peter Kharchenko [aut, cre], Jean Fan [aut]

Maintainer: Jean Fan <jeanfan at jhu.edu>

Installation

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

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("scde")

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

Documentation

PDF		Reference Manual

Details

biocViews	Bayesian, DifferentialExpression, ImmunoOncology, RNASeq, Software, StatisticalMethod, Transcription
Version	2.26.2
In Bioconductor since	BioC 3.3 (R-3.3) (7 years)
License	GPL-2
Depends	R (>= 3.0.0), flexmix
Imports	Rcpp (>= 0.10.4), RcppArmadillo (>= 0.5.400.2.0), mgcv, Rook, rjson, MASS, Cairo, RColorBrewer, edgeR, quantreg, methods, nnet, RMTstat, extRemes, pcaMethods, BiocParallel, parallel
LinkingTo	Rcpp, RcppArmadillo
Suggests	knitr, cba, fastcluster, WGCNA, GO.db, org.Hs.eg.db, rmarkdown
SystemRequirements
Enhances
URL	http://pklab.med.harvard.edu/scde
BugReports	https://github.com/hms-dbmi/scde/issues
Depends On Me
Imports Me
Suggests Me	pagoda2
Links To Me
Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package	scde_2.26.2.tar.gz
Windows Binary	scde_2.26.2.zip (64-bit only)
macOS Binary (x86_64)	scde_2.26.2.tgz
macOS Binary (arm64)	scde_2.26.2.tgz
Source Repository	git clone https://git.bioconductor.org/packages/scde
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/scde
Bioc Package Browser	https://code.bioconductor.org/browse/scde/
Package Short Url	https://bioconductor.org/packages/scde/
Package Downloads Report	Download Stats
Old Source Packages for BioC 3.16	Source Archive