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Analysis of Large-Scale Radio-Genomic Data

Bioconductor version: Release (3.19)

Computational tool box for radio-genomic analysis which integrates radio-response data, radio-biological modelling and comprehensive cell line annotations for hundreds of cancer cell lines. The 'RadioSet' class enables creation and manipulation of standardized datasets including information about cancer cells lines, radio-response assays and dose-response indicators. Included methods allow fitting and plotting dose-response data using established radio-biological models along with quality control to validate results. Additional functions related to fitting and plotting dose response curves, quantifying statistical correlation and calculating area under the curve (AUC) or survival fraction (SF) are included. For more details please see the included documentation, references, as well as: Manem, V. et al (2018) .

Author: Venkata Manem [aut], Petr Smirnov [aut], Ian Smith [aut], Meghan Lambie [aut], Christopher Eeles [aut], Scott Bratman [aut], Jermiah Joseph [aut], Benjamin Haibe-Kains [aut, cre]

Maintainer: Benjamin Haibe-Kains <benjamin.haibe.kains at>

Citation (from within R, enter citation("RadioGx")):


To install this package, start R (version "4.4") and enter:

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


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

RadioGx: An R Package for Analysis of Large Radiogenomic Datasets HTML R Script
Reference Manual PDF


biocViews Classification, Pharmacogenetics, Pharmacogenomics, QualityControl, Software, Survival
Version 2.8.0
In Bioconductor since BioC 3.12 (R-4.0) (3.5 years)
License GPL-3
Depends R (>= 4.1), CoreGx
Imports SummarizedExperiment, BiocGenerics, data.table, S4Vectors, Biobase, parallel, BiocParallel, RColorBrewer, caTools, magicaxis, methods, reshape2, scales, grDevices, graphics, stats, utils, assertthat, matrixStats, downloader
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Suggests rmarkdown, BiocStyle, knitr, pander, markdown
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Follow Installation instructions to use this package in your R session.

Source Package RadioGx_2.8.0.tar.gz
Windows Binary (64-bit only)
macOS Binary (x86_64) RadioGx_2.8.0.tgz
macOS Binary (arm64) RadioGx_2.8.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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