summarize_by_gene: Simplify binary matrix to one column per gene that counts any...

In AxelitoMartin/gnomeR: Wrangle and analyze IMPACT and TCGA mutation data

Simplify binary matrix to one column per gene that counts any alteration type as 1

Description

This will reduce the number of columns in your binary matrix, and the resulting data frame will have only 1 col per gene, as opposed to separate columns for mutation/cna/fusion.

Usage

summarize_by_gene(gene_binary, other_vars = NULL)

Arguments

gene_binary	a 0/1 matrix of gene alterations
other_vars	One or more column names (quoted or unquoted) in data to be retained in resulting data frame. Default is NULL.

Value

a binary matrix with a row for each sample and one column per gene

Examples

samples <- unique(gnomeR::mutations$sampleId)[1:10]
gene_binary <- create_gene_binary(
  samples = samples, mutation = mutations, cna = cna,
  mut_type = "somatic_only",
  include_silent = FALSE,
  specify_panel = "IMPACT341"
) %>%
  summarize_by_gene()

AxelitoMartin/gnomeR documentation built on Oct. 18, 2024, 11:39 a.m.