Implementation of the methodology proposed in 'Data-driven design of targeted gene panels for estimating immunotherapy biomarkers', Bradley and Cannings (2021) <arXiv:2102.04296>. This package allows the user to fit generative models of mutation from an annotated mutation dataset, and then further to produce tunable linear estimators of exome-wide biomarkers. It also contains functions to simulate mutation annotated format (MAF) data, as well as to analyse the output and performance of models.
Version: | 0.1.2 |
Depends: | R (≥ 2.10) |
Imports: | stats, utils, glmnet, Matrix, dplyr, purrr, latex2exp, matrixStats, ggplot2, gglasso, PRROC |
Suggests: | testthat (≥ 2.1.0) |
Published: | 2021-03-18 |
Author: | Jacob R. Bradley |
Maintainer: | Jacob R. Bradley <cobrbradley at gmail.com> |
License: | MIT + file LICENSE |
NeedsCompilation: | no |
Materials: | README NEWS |
CRAN checks: | ICBioMark results |
Reference manual: | ICBioMark.pdf |
Package source: | ICBioMark_0.1.2.tar.gz |
Windows binaries: | r-devel: ICBioMark_0.1.2.zip, r-release: ICBioMark_0.1.2.zip, r-oldrel: ICBioMark_0.1.2.zip |
macOS binaries: | r-release (arm64): ICBioMark_0.1.2.tgz, r-release (x86_64): ICBioMark_0.1.2.tgz, r-oldrel: ICBioMark_0.1.2.tgz |
Old sources: | ICBioMark archive |
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