plot_enrichment_depletion: Plot enrichment/depletion of mutations in genomic regions

In MutationalPatterns: Comprehensive genome-wide analysis of mutational processes

Description

Plot enrichment/depletion of mutations in genomic regions

Usage

plot_enrichment_depletion(df, sig_type = c("fdr", "p"))

Arguments

df	Dataframe result from enrichment_depletion_test()
sig_type	The type of significance to be used. Possible values: * 'fdr' False discovery rate. A type of multiple testing correction.; * 'p' for regular p values.

Value

Plot with two parts. 1: Barplot with no. mutations expected and observed per region. 2: Effect size of enrichment/depletion (log2ratio) with results significance test.

See Also

enrichment_depletion_test, genomic_distribution

Examples

## See the 'genomic_distribution()' example for how we obtained the
## following data:
distr <- readRDS(system.file("states/distr_data.rds",
  package = "MutationalPatterns"
))

tissue <- c(
  "colon", "colon", "colon",
  "intestine", "intestine", "intestine",
  "liver", "liver", "liver"
)

## Perform the enrichment/depletion test.
distr_test <- enrichment_depletion_test(distr, by = tissue)

## Plot the enrichment/depletion
plot_enrichment_depletion(distr_test)

#Perform and plot the enrichmet depletion test for all samples pooled
distr_test2 <- enrichment_depletion_test(distr)
plot_enrichment_depletion(distr_test2)

## Plot with p values instead of fdr
plot_enrichment_depletion(distr_test, sig_type = "p")

## Use multiple (max 3) significance cutoffs.
## This will vary the number of significance stars.
distr_multistars <- enrichment_depletion_test(distr,
  by = tissue,
  p_cutoffs = c(0.05, 0.01, 0.005),
  fdr_cutoffs = c(0.1, 0.05, 0.01)
)
plot_enrichment_depletion(distr_multistars)

MutationalPatterns documentation built on Nov. 14, 2020, 2:03 a.m.