GDCRNATools - an R/Bioconductor package for downloading, organizing, and integrative analyzing lncRNA, mRNA, and miRNA data in GDC

1. Introduction

The Genomic Data Commons (GDC) maintains standardized genomic, clinical, and biospecimen data from National Cancer Institute (NCI) programs including The Cancer Genome Atlas (TCGA) and Therapeutically Applicable Research To Generate Effective Treatments (TARGET), It also accepts high quality datasets from non-NCI supported cancer research programs, such as genomic data from the Foundation Medicine.

GDCRNATools is an R package which provides a standard, easy-to-use and comprehensive pipeline for downloading, organizing, and integrative analyzing RNA expression data in the GDC portal with an emphasis on deciphering the lncRNA-mRNA related ceRNA regulatory network in cancer.

2. Manual and R script

The comprehensive manual of GDCRNATools is available here: GDCRNATools Manual

R code of the workflow is available here: GDCRNATools Workflow

3. Installation

GDCRNATools has been accepted by Bioconductor as the development version. However, before the next release of R/Bioconductor in mid-April, it is highly recommended to install GDCRNATools by downloading and installing locally, rather than via Bioconductor.

Please download the compressed package here: GDCRNATools_0.99.16.tar.gz

3.1 On Windows system

• Make sure that your R is installed in 'c:\program files'

• Install Rtools in 'c:\program files'

• Add R and Rtools to the Path Variable on the Environment Variables panel, including

  c:\program files\Rtools\bin

  c:\program files\Rtools\gcc-4.6.3\bin

  c:\program files\R\R.3.x.x\bin\i386

  c:\program files\R\R.3.x.x\bin\x64

• Run the following code in R

install.packages('GDCRNATools_0.99.16.tar.gz', repos = NULL, type='source')

3.2 On Linux and Mac systems

Just run the following code in R

install.packages('GDCRNATools_0.99.16.tar.gz', repos = NULL, type='source')

3.3 Note

If GDCRNATools cannot be installed due to the lack of dependencies, please run the following code ahead to install those pacakges either simutaneously or separately:

source("https://bioconductor.org/biocLite.R")

### install packages simutaneously ###
biocLite(c('limma', 'edgeR', 'DESeq2', 'clusterProfiler', 'DOSE', 'org.Hs.eg.db', 'biomaRt', 'BiocParallel', 'GenomicDataCommons'))
install.packages(c('shiny', 'jsonlite', 'rjson', 'survival', 'survminer', 'ggplot2', 'gplots', 'Hmisc', 'DT', 'matrixStats', 'xml2'))

### install packages seperately ###
biocLite('limma')
biocLite('edgeR')
biocLite('DESeq2')
biocLite('clusterProfiler')
biocLite('DOSE')
biocLite('org.Hs.eg.db')
biocLite('biomaRt')
biocLite('BiocParallel')
biocLite('GenomicDataCommons')

install.packages('shiny')
install.packages('jsonlite')
install.packages('rjson')
install.packages('survival')
install.packages('survminer')
install.packages('ggplot2')
install.packages('gplots')
install.packages('Hmisc')
install.packages('DT')
install.packages('matrixStats')
install.packages('xml2')