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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.4 |
rolling source/ R- | ICBioMark_0.1.4.tar.gz |
2.9 MiB |
0.1.4 |
rolling linux/jammy R-4.5 | ICBioMark_0.1.4.tar.gz |
3.7 MiB |
0.1.4 |
rolling linux/noble R-4.5 | ICBioMark_0.1.4.tar.gz |
3.7 MiB |
0.1.4 |
latest source/ R- | ICBioMark_0.1.4.tar.gz |
2.9 MiB |
0.1.4 |
latest linux/jammy R-4.5 | ICBioMark_0.1.4.tar.gz |
3.7 MiB |
0.1.4 |
latest linux/noble R-4.5 | ICBioMark_0.1.4.tar.gz |
3.7 MiB |
0.1.4 |
2026-04-26 source/ R- | ICBioMark_0.1.4.tar.gz |
2.9 MiB |
0.1.4 |
2026-04-23 source/ R- | ICBioMark_0.1.4.tar.gz |
2.9 MiB |
0.1.4 |
2026-04-09 windows/windows R-4.5 | ICBioMark_0.1.4.zip |
3.7 MiB |
0.1.4 |
2025-04-20 source/ R- | ICBioMark_0.1.4.tar.gz |
2.9 MiB |