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.
First we will install some prerequisite libraries before installing
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 Rstudio (Suggested but not required)
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"
Packrat (around 10 minutes)To install the latest development version from
- Download file
- Unarchive file, open the folder, start
Rin this folder
- Packrat will then automate the whole process for you
library(sake) shiny::runApp(system.file("sake", package="sake"))
Please follow the links to briefly walk you through the functions of
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.