GRcalculator dockerfile

The dockerfile in this container builds a docker image (https://hub.docker.com/r/ucbd2k/grcalculator-docker/) that contains an RStudio/Shiny Server installation with minimum R package and external dependencies for running the GRcalculator applications. The dockerfile clones git repositories for the three R/Shiny apps deployed at http://www.grcalculator.org and installs them inside the docker image. See below for more details on the applications and links to their code repositories.

GRcalculator: an online tool for calculating and mining drug response data

GRcalculator is a Shiny application (http://www.grcalculator.org) developed to accompany the Nature paper Growth rate inhibition metrics correct for confounders in measuring sensitivity to cancer drugs by Hafner et al. (2016).

For a brief overview of the GRcalculator and the importance of the newly developed GR metrics methodology (Hafner et al. 2016), see this poster: https://figshare.com/articles/GRcalculator_an_online_tool_for_calculating_and_mining_drug_response_data/4244408

Citations

Clark NA, Hafner M, Kouril M, Williams EH, Muhlich JL, Pilarczyk M, et al. GRcalculator: an online tool for calculating and mining dose–response data. BMC Cancer 2017, 17(1):698. (https://doi.org/10.1186/s12885-017-3689-3)

Hafner M, Niepel M, Chung M, Sorger PK. Growth rate inhibition metrics correct for confounders in measuring sensitivity to cancer drugs. Nature Methods 2016, 13(6):521-527. (https://doi.org/10.1038/nmeth.3853)

Website design and online tool development

Nick Clark¹, Marc Hafner², Michal Kouril¹, Mario Niepel², Elizabeth Williams², Jeremy Muhlich² and Mario Medvedovic¹

¹ LINCS-BD2K Data Coordination and Integration Center, University of Cincinnati

² HMS LINCS Center, Harvard Medical School

Offline installation

Install R package dependencies:

# Install our "GRmetrics" Bioconductor package and others
source("http://bioconductor.org/biocLite.R")
biocLite("GRmetrics")
biocLite("S4Vectors")
# Install our "shinyLi" package
install.packages("devtools")
devtools::install_github("uc-bd2k/shinyLi")
# Install CRAN package dependencies
install.packages(c("shiny","shinyjs","shinyBS","ggplot2","plotly","drc","stringr","readr"))

Run the application from the R command line:

shiny::runGitHub('uc-bd2k/grcalculator')

Related software

The GRcalculator tool (http://www.grcalculator.org) is implemented in the form of three integrated Shiny applications (grcalculator, grbrowser and grtutorial).

grtutorial (https://github.com/uc-bd2k/grtutorial)

The grtutorial Shiny application (“About GR Metrics” link in the toolbar) provides background information about the advantages of the GR metrics over traditional metrics for quantifying dose-response assays as well as descriptions of the GRcalculator tools.

grbrowser (https://github.com/uc-bd2k/grbrowser)

The grbrowser Shiny application (“LINCS Dose-Response Datasets” section in the toolbar) facilitates interactive browsing and mining of drug response data generated by the LINCS project.

GRmetrics R package (https://github.com/uc-bd2k/GRmetrics)

This package re-creates the online calculation and visualization tools available at http://www.grcalculator.org/grcalculator/.

Bioconductor page: https://bioconductor.org/packages/GRmetrics

Vignette: https://bioconductor.org/packages/release/bioc/vignettes/GRmetrics/inst/doc/GRmetrics-vignette.html

# Use the following code to install the GRmetrics package in R
source("http://bioconductor.org/biocLite.R")
biocLite("GRmetrics")

MATLAB and Python tools (https://github.com/datarail/gr_metrics)

This repository contains the MATLAB, Python, and R implementations of GR metrics calculations with examples and supplementary information.