Package: scde
Type: Package
Title: Single Cell Differential Expression
Version: 2.12.0
Date: 2016-01-20
Description: 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]
Authors@R: c(
    person("Peter", "Kharchenko", role = c("aut", "cre"),
		     email = "Peter_Kharchenko@hms.harvard.edu"),
    person("Jean", "Fan", role = "aut",
	         email = "jeanfan@fas.harvard.edu")
	         )
Maintainer: Jean Fan <jeanfan@fas.harvard.edu>
URL: http://pklab.med.harvard.edu/scde
BugReports: https://github.com/hms-dbmi/scde/issues
License: GPL-2
LazyData: true
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
Suggests: knitr, cba, fastcluster, WGCNA, GO.db, org.Hs.eg.db,
        rmarkdown
biocViews: ImmunoOncology, RNASeq, StatisticalMethod,
        DifferentialExpression, Bayesian, Transcription, Software
LinkingTo: Rcpp, RcppArmadillo
VignetteBuilder: knitr
Packaged: 2019-05-03 03:46:02 UTC; biocbuild
RoxygenNote: 5.0.0
NeedsCompilation: yes
git_url: https://git.bioconductor.org/packages/scde
git_branch: RELEASE_3_9
git_last_commit: ec52dd0
git_last_commit_date: 2019-05-02
Date/Publication: 2019-05-02
Built: R 3.6.0; i386-w64-mingw32; 2019-05-03 14:22:57 UTC; windows
Archs: i386, x64
