ICBioMark: Data-Driven Design of Targeted Gene Panels for Estimating Immunotherapy Biomarkers

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 ORCID iD [aut, cre], Timothy I. Cannings ORCID iD [aut]
Maintainer: Jacob R. Bradley <cobrbradley at gmail.com>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README NEWS
CRAN checks: ICBioMark results

Downloads:

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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