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cmapR (CMap R code)

Parsing and utility functions for analyzing CMap data. To learn more about the CMap project at the Broad Institute, please visit

NOTICE - Updates for Bioconductor

cmapR has been accepted in Bioconductor. In accordance with Bioconductor standards, we have changed some of the function naming conventions. Function names that used to contain . have been replaced with _. Hence, parse.gctx is now parse_gctx and so on. The older function names will still work with a warning. There is additional info and examples in the vignettes/tutorial.Rmd.

Install instructions

Installing from Bioconductor

In R version 4.0 or newer:

if (!requireNamespace("BiocManager", quietly = TRUE))


Dependencies are listed in DESCRIPTION


A docker container with a slightly earlier version of cmapR can be obtained here: This may be preferable for those who would like to use the package without installing on their system.

Installing from Github source

Perhaps the simplest way to install directly from github is using devtools::install_github("cmap/cmapR"). Note that this requires having previously installed the devtools package.

The script install_cmapR.R takes care of installing all the dependencies and then running devtools::install_github("cmap/cmapR"), so you can simply source this script after cloning this repository.

Alternatively, you can point your R's install.packages function at a tarball of the cmapR archive. You can generate this archive by cloning this repository and doing the following:

# make a gzip tar ball of the repo
R CMD build cmapR
# makes cmapR_1.0.tar.gz

# check that the package is ok
R CMD check cmapR_1.0.tar.gz	

Once you have created the tarball, open an R terminal and execute the following:

install.packages("cmapR_1.0.tar.gz", type="source", repos=NULL)

You can also source individual files as needed instead of installing the entire package.

# For example, just load the IO methods

Citation information

If you use GCTx and/or cmapR in your work, please cite Enache et al.