nsclc_maf

A pre-loaded mutation dataset from Campbell et. al (2016), downloaded from The Cancer Genome Atlas.

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

nsclc_maf function

An annotated mutation dataframe with 6 columns and 299855 rows:<dl class="dl-horizontal">
<dt>Tumor_Sample_Barcode</dt><dd>A sample id for each mutation.</dd>
<dt>Hugo_Symbol</dt><dd>The name of the gene location for each mutation.</dd>
<dt>Variant_Classification</dt><dd>The mutation type for each mutation.</dd>
<dt>Chromosome</dt><dd>Chromosome on which the mutation occurred.</dd>
<dt>Start_Position</dt><dd>Start nucleotide location for mutation.</dd>
<dt>End_Position</dt><dd>End nucleotide location for mutation.</dd>
</dl>

Format

Non-Small Cell Lung Cancer MAF Data — nsclc_maf

An annotated mutation dataframe with 6 columns and 299855 rows:<dl class='dl-horizontal'>
<dt>Tumor_Sample_Barcode</dt><dd>A sample id for each mutation.</dd>
<dt>Hugo_Symbol</dt><dd>The name of the gene location for each mutation.</dd>
<dt>Variant_Classification</dt><dd>The mutation type for each mutation.</dd>
<dt>Chromosome</dt><dd>Chromosome on which the mutation occurred.</dd>
<dt>Start_Position</dt><dd>Start nucleotide location for mutation.</dd>
<dt>End_Position</dt><dd>End nucleotide location for mutation.</dd>
</dl>

nsclc_maf: Non-Small Cell Lung Cancer MAF Data

Description

Usage

Arguments

Format