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README.md

sake

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Single-cell RNA-Seq Analysis and Klustering Evaluation

The aim of sake is to provide a user-friendly tool for easy analysis of NGS Single-Cell transcriptomic data

Flowchart of SAKE package and example analysis results: a) Analysis workflow for analyzing single-cell RNA-Seq data. b) Quality Controls to compare total sequenced reads to total gene transcripts detected. c) Sample correlation heat map plot d) A heat map of sample assignment from NMF run, with dark red indicating high confidence in cluster assignments e) t-SNE plot to compare NMF assigned groups with t-SNE projections. f) A table of NMF identified features (genes defining each cluster) and a box plot of gene expression distributions across NMF assigned groups. g) Summary table for GO term enrichment analysis for each NMF assigned group.

Installation

First we will install some prerequisite libraries before installing sake

For Centos (tested on 6.9)

sudo yum install openssl-devel libcurl-devel libpng-devel libxml2-devel libxslt

# Require `gcc` >= 4.6 
sudo yum install centos-release-scl
sudo yum install devtoolset-3-toolchain
scl enable devtoolset-3 bash

For Ubuntu (tested on 16.10)

sudo apt-get install libcurl4-openssl-dev libpng-dev libxslt-dev libssl-dev libxml2-dev xsltproc

For Mac OS (tested on Sierra 10.12.1)

# follow instructions to install brew on MAC
http://brew.sh
# install required packages 
brew install curl openssl libpng libxslt libxml2 
# update gcc
brew install gcc48

Download and Install R

To install the latest development version from GitHub (around 30 minutes)

source("http://bioconductor.org/biocLite.R")
biocLite(c("annotate", "AnnotationHub", "biomaRt", "DESeq2", "gage", "gageData", "GO.db", "pathview", "plotly", "DT"))

install.packages("devtools")
devtools::install_github("renozao/pkgmaker", ref="develop")
devtools::install_github("naikai/sake") # You may want to consider "devtools::install_github("naikai/sake", CC=gcc-7) to flag for use with the GCC compiler" 

To install the latest development version from Packrat (around 10 minutes)

  • Download file
  • Unarchive file, open the folder, start R in this folder
  • Packrat will then automate the whole process for you

Usage

library(sake)
shiny::runApp(system.file("sake", package="sake"))

Getting Started

Please follow the links to briefly walk you through the functions of sake package.

Copying & Distribution

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.