Represent mutation hot spots as a sequence logo

Generates a summary of the frequency of SSMs in a small region around a mutation hot spot using a "sequence logo"-style stacked plot

Usage

mutation_hotspot_logo(
  maf_df,
  hotspot_position = 128750677,
  genome_build,
  pad_length = 20,
  fasta_path,
  include_AA = FALSE,
  group_AA = FALSE,
  annotate_motif = FALSE,
  annotate_only = FALSE,
  return_data = FALSE,
  base_size = 5,
  aa_size = 3,
  text_size = 5,
  prepend_plot_label = "",
  include_title = TRUE,
  real_coordinates = TRUE,
  reverse = FALSE,
  verbose = FALSE
)

Value

a named list containing a ggplot object and various processed data

Examples

if (FALSE) { # \dontrun{
library(GAMBLR.open)
g_meta <- suppressMessages(get_gambl_metadata()) %>%
  dplyr::filter(seq_type == "genome")
# CXCR4 non-coding hotspot
muts <- get_ssm_by_regions(
  regions_list = "2:136875000-136875097",
  streamlined = FALSE,
  projection = "grch37",
  these_samples_metadata = g_meta
)


mutation_hotspot_logo(
  maf_df = muts,
  hotspot_position = 136875037,
  include_AA = TRUE,
  pad_length = 51,
  annotate_motif = TRUE,
  base_size = 2,
  prepend_plot_label = "CXCR4"
)


cap_meta <- suppressMessages(get_gambl_metadata()) %>%
  dplyr::filter(seq_type == "capture")

# ID3 hotspot
muts <- get_ssm_by_regions(
  regions_list = "1:23885706-23885798",
  streamlined = FALSE,
  projection = "grch37",
  this_seq_type = "capture",
  these_samples_metadata = cap_meta
)


mutation_hotspot_logo(
  maf_df = muts,
  hotspot_position = 23885750,
  include_AA = TRUE,
  aa_size = 3,
  pad_length = 42,
  annotate_motif = TRUE,
  base_size = 3,
  prepend_plot_label = "ID3",
  text_size = 8
)
} # }