Pretty Lollipop Plot. — pretty_lollipop

Generates a visually appealing lollipop plot.

Usage

pretty_lollipop_plot(
  maf_df,
  gene = NULL,
  plot_title,
  by_allele = TRUE,
  max_count = 10,
  include_silent = FALSE,
  labelPos = NULL,
  show_rate = FALSE,
  title_size = 8,
  x_axis_size = 4,
  domain_label_size = 0,
  aa_label_size = 3
)

Arguments

maf_df: A data frame containing the mutation data.
gene: The gene symbol to plot.
plot_title: Optional, the title of the plot. Default is gene.
by_allele: Set to FALSE to consider all mutations at the same codon as equivalent. When FALSE, and combined with labelPos, the labels will only indicate the amino acid number. Default is TRUE.
include_silent: Logical parameter indicating whether to include silent mutations into coding mutations. Default is FALSE.
labelPos: Specify which AA positions to label in the plot (default is no labels).

Value

A lollipop plot.

Details

Retrieve maf data of a specific sample or a set of samples. A gene of interest can then be visualized with the given maf data. Silent mutations can be visualized setting include_silent to TRUE.

Examples

library(GAMBLR.open)
suppressMessages(
  suppressWarnings({

#get meta data (BL_Thomas)
metadata <- suppressMessages(get_gambl_metadata()) %>%
    filter(seq_type == "genome") %>%
    check_and_clean_metadata(.,duplicate_action="keep_first")

maf_df <- get_coding_ssm(
    these_samples_metadata = metadata
)

#construct pretty_lollipop_plot.
lollipop_result <- pretty_lollipop_plot(maf_df, "DDX3X")
print(lollipop_result)
}))