To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("SC3")

In most cases, you don't need to download the package archive at all.

SC3

Single-Cell Consensus Clustering

Bioconductor version: Release (3.5)

A tool for unsupervised clustering and analysis of single cell RNA-Seq data.

Author: Vladimir Kiselev

Maintainer: Vladimir Kiselev <vladimir.yu.kiselev at gmail.com>

Citation (from within R, enter citation("SC3")):

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("SC3")

biocViews	Classification, Clustering, DataRepresentation, DifferentialExpression, DimensionReduction, GUI, RNASeq, SingleCell, Software, SupportVectorMachine, Transcription, Transcriptomics, Visualization
Version	1.4.2
In Bioconductor since	BioC 3.3 (R-3.3) (1.5 years)
License	GPL-3
Depends	R (>= 3.3)
Imports	graphics, stats, utils, methods, e1071, parallel, foreach, doParallel, doRNG, shiny, ggplot2, pheatmap (>= 1.0.8), ROCR, robustbase, rrcov, cluster, WriteXLS, Rcpp (>= 0.11.1), scater
LinkingTo	Rcpp, RcppArmadillo
Suggests	knitr, rmarkdown, testthat, mclust
SystemRequirements
Enhances
URL	https://github.com/hemberg-lab/SC3
BugReports	https://support.bioconductor.org/t/sc3/
Depends On Me
Imports Me
Suggests Me
Build Report

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

Source Package	SC3_1.4.2.tar.gz
Windows Binary	SC3_1.4.2.zip (32- & 64-bit)
Mac OS X 10.11 (El Capitan)	SC3_1.4.2.tgz
Source Repository	git clone https://git.bioconductor.org/packages/SC3
Package Short Url	http://bioconductor.org/packages/SC3/
Package Downloads Report	Download Stats

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