example_gen_model

An example of the output produced by fit_gen_model() on simulated data.

datasets

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.

Jacob R. Bradley

ICBioMark

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

Timothy I. Cannings

example_gen_model function

A list with two entries:<dl class="dl-horizontal">
<dt>fit</dt><dd>A glmnet fit object.</dd>
<dt>dev</dt><dd>A table containing the average deviance of each cross-validation fold, for each penalisation factor in fit$lambda.</dd>
<dt>s_min</dt><dd>The index of the regularisation penalty minimising average deviance across folds.</dd>
</dl>

Format

Generative Model from Simulated Data — example_gen_model

A list with two entries:<dl class='dl-horizontal'>
<dt>fit</dt><dd>A glmnet fit object.</dd>
<dt>dev</dt><dd>A table containing the average deviance of each cross-validation fold, for each penalisation factor in fit$lambda.</dd>
<dt>s_min</dt><dd>The index of the regularisation penalty minimising average deviance across folds.</dd>
</dl>

example_gen_model: Generative Model from Simulated Data

Description

Usage

Arguments

Format