RBioMIR

RBioMIR - An R package for differential expression (DE) analysis of small RNA-Seq based miRNA profiling experiments. 

When using this program please cite: Zhang J, Hadj-Moussa H, and Storey KB. (2016). Current progress of high-throughput microRNA differential expression analysis and random forest gene selection for model and non-model systems: an R implementation. Journal of Integrative Bioinformatics, 13(5), 306. PMID:28187420.

Download and install R and R Studio. To install the latest version of RBioMIR, please select the following commands (copy/paste) and run them in R Studio (make sure you are connected to the internet):
(1) Run the following command to install devtools (needed to run RBioMIR), otherwise skip this step:
         install.packages("devtools")
(2) Run the following command to install Bioconductor (needed to run RBioMIR), otherwise skip this step:
     source("https://bioconductor.org/biocLite.R")
     biocLite()
         For help with installing Bioconductor, visit (https://www.bioconductor.org/install/)
(3) Run the following command to install RBioMIR
          devtools::install_github("jzhangc/git_RBioMIR/RBioMIR", repos = BiocInstaller::biocinstallRepos())
(4) To set a working directory use, replace "..." with your folder address:   
         For Mac and Linux: setwd("working directory")
 
 
The source code and the R package can be downloaded through GitHub: https://github.com/jzhangc/git_RBioMIR.git.
 
To access the Unix Shell codes for initial data processing of small RNA-Seq raw reads, CLICK HERE!