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Michael edited this page Jan 17, 2017 · 2 revisions

Single-Cell Overview of Normalized Expression data

SCONE (Single-Cell Overview of Normalized Expression), a package for single-cell RNA-seq data quality control (QC) and normalization. This data-driven framework uses summaries of expression data to assess the efficacy of normalization workflows.

R Package Installation

The easiest way to install the scone package is to execute to following R commands:

source("https://bioconductor.org/biocLite.R")
biocLite("devtools")
biocLite("YosefLab/scone", ref = "v0.99.0", dependencies=TRUE)

Note that the master branch of scone is ahead of the current release v0.99.0, and it requires both R-devel (>= 3.4) and Bioconductor devel.

Code Repository Installation

To gain access to the full scone repository, you may use git clone command in your terminal:

git clone https://github.com/YosefLab/scone.git

and then checkout the latest release:

cd scone
git checkout v0.99.0

The release may be installed using the R command line utility:

R CMD install .

SCONE Easy-Bake Script: Run Essential SCONE Modules

Within the git repo, users can access the ezbake.R script

./scripts/ezbake.R

Requirements

  • R (R version 3.3)
  • See DESCRIPTION file for additional R library dependencies