RadioGx: Analysis of Large-Scale Radio-Genomic Data

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) <doi:10.1101/449793>.

Version: 0.0.1
Depends: R (≥ 3.5.0), CoreGx
Imports: PharmacoGx, Biobase, RColorBrewer, caTools, magicaxis, methods, reshape2, KernSmooth, cluster, Matrix, scales
Published: 2019-06-18
Author: Venkata Manem [aut], Petr Smirnov [aut], Ian Smith [aut], Meghan Lambie [aut], Christopher Eeles [aut], Scott Bratman [aut], Benjamin Haibe-Kains [aut, cre]
Maintainer: Benjamin Haibe-Kains <benjamin.haibe.kains at utoronto.ca>
License: GPL-3
NeedsCompilation: no
Citation: RadioGx citation info
Materials: README
CRAN checks: RadioGx results

Downloads:

Reference manual: RadioGx.pdf
Package source: RadioGx_0.0.1.tar.gz
Windows binaries: r-devel: RadioGx_0.0.1.zip, r-devel-gcc8: RadioGx_0.0.1.zip, r-release: RadioGx_0.0.1.zip, r-oldrel: RadioGx_0.0.1.zip
OS X binaries: r-release: RadioGx_0.0.1.tgz, r-oldrel: not available

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