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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) <doi:10.48550/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: |
0.1.4 |
| Depends: |
R (≥ 2.10) |
| Imports: |
stats, utils, glmnet, Matrix, dplyr, purrr, latex2exp, matrixStats, ggplot2, gglasso, PRROC |
| Suggests: |
testthat (≥ 2.1.0) |
| Published: |
2021-11-15 |
| Author: |
Jacob R. Bradley 
[aut, cre],
Timothy I. Cannings
[aut] |
| Maintainer: |
Jacob R. Bradley <cobrbradley at gmail.com> |
| License: |
MIT + file LICENSE |
| NeedsCompilation: |
no |
| Materials: |
README NEWS |
| In views: |
Omics |
| CRAN checks: |
ICBioMark results |
Documentation:
Downloads:
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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