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) . 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.


Reference manual

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0.1.2 by Jacob R. Bradley, 6 months ago

Browse source code at

Authors: Jacob R. Bradley [aut, cre] , Timothy I. Cannings [aut]

Documentation:   PDF Manual  

MIT + file LICENSE license

Imports stats, utils, glmnet, Matrix, dplyr, purrr, latex2exp, matrixStats, ggplot2, gglasso, PRROC

Suggests testthat

See at CRAN