plot_original_vs_reconstructed: Plot the similarity between a mutation matrix and its...

In MutationalPatterns: Comprehensive genome-wide analysis of mutational processes

Description

When a reconstructed profile has a cosine similarity of more than 0.95 with original, the reconstructed profile is considered very good.

Usage

plot_original_vs_reconstructed(
  mut_matrix,
  reconstructed,
  y_intercept = 0.95,
  ylims = c(0.6, 1)
)

Arguments

mut_matrix	mutation count matrix (dimensions: x mutation types X n samples)
reconstructed	A reconstructed mutation count matrix
y_intercept	The y intercept of the plotted horizontal line. Default: 0.95.
ylims	The limits of the y axis. Default: c(0.6, 1)

Value

A ggplot figure

Examples

## See the 'mut_matrix()' example for how we obtained the mutation matrix:
mut_mat <- readRDS(system.file("states/mut_mat_data.rds",
  package = "MutationalPatterns"
))

## Extracting signatures can be computationally intensive, so
## we use pre-computed data generated with the following command:
# nmf_res <- extract_signatures(mut_mat, rank = 2)

nmf_res <- readRDS(system.file("states/nmf_res_data.rds",
  package = "MutationalPatterns"
))

## Create figure
plot_original_vs_reconstructed(mut_mat, nmf_res$reconstructed)

## You can also use the results of signature refitting.
## Here we load some data as an example
fit_res <- readRDS(system.file("states/snv_refit.rds",
  package = "MutationalPatterns"
))
plot_original_vs_reconstructed(mut_mat, fit_res$reconstructed)

## You can also change the height of the horizontal line
plot_original_vs_reconstructed(mut_mat, fit_res$reconstructed, y_intercept = 0.90)

## It's also possible to change the limits of the y axis
plot_original_vs_reconstructed(mut_mat, fit_res$reconstructed, ylims = c(0, 1))

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