Before library installation install required Bioconductor and CRAN packages through this code:
bioconductor_packages=c('edgeR','RUVSeq','DESeq2','limma','rhdf5','artMS')
#For R version 3.5> use BiocManager to install required bioconductor packages:
if (length(setdiff(bioconductor_packages, rownames(installed.packages()))) > 0) {
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install(setdiff(bioconductor_packages, rownames(installed.packages())))
}
#For R version <3.5 use the BiocInstaller to install required bioconductor packages:
source("https://bioconductor.org/biocLite.R")
BiocInstaller::biocLite(bioconductor_packages)
packages=c('magrittr','dplyr','ggplot2','doParallel','foreach','lme4','Rfast','httr','data.table')
if (length(setdiff(packages, rownames(installed.packages()))) > 0) {
install.packages(setdiff(packages, rownames(installed.packages())))
}
Next, install the octad.db, package with all required files for computation available via link octad.db
install.packages("path%to%octad.db_0.99.0.tar.gz", repos = NULL, type="source")
Or without downloading the distributive:
install.packages("https://chenlab-data-public.s3-us-west-2.amazonaws.com/octad/octad.db_0.99.0.tar.gz",
method="libcurl",repos=NULL,type="source")
It takes a few minutes to install the package and verify files. Afterward, the pipeline will be ready to run. Finally, install the package:
devtools::install_github('Bin-Chen-Lab/octad',build_vignettes = TRUE)
By default, octad package uses expression data for 978 genes from the LINCS dataset. However, it can influence the result and we advice using whole octad database. To obtatin whole results for DE, downloading of the additional OCTAD database octad.counts.and.tpm.h5 from the AWS link is required.
The tutorial available via following link
The several examples listed in the file octad_example.R :
If you use our work, please cite the paper OCTAD: an open workplace for virtually screening therapeutics targeting precise cancer patient groups using gene expression features, Nature Protocols. Both OCTAD package and website was developed by Bin Chen laboratory. Examples and questions can be addressed to Eugene Chekalin, PhD, chekali1@msu.edu or Bin Chen, PhD, PI, bin.chen@hc.msu.edu