Pretty mutual exclusivity plot

Usage

pretty_mutual_exclusivity(
  maf_data,
  mut_mat,
  cn_mat,
  corr_mat,
  p_mat,
  min_mutation_percent = 2,
  genes,
  these_samples_metadata,
  q_threshold = 0.05,
  drop_positive_correlations = FALSE,
  exclude_insignificant_genes = TRUE,
  engine = "ggcorrplot",
  font_size = 7,
  use_alpha = FALSE,
  clustering_distance = "binary",
  gene_anno_df,
  size_factor = 0.01,
  split,
  return_data = FALSE,
  include_silent = FALSE,
  include_hotspots = FALSE,
  review_hotspots = FALSE,
  bonferroni = FALSE,
  verbose = FALSE,
  metadataBarHeight = 3,
  metadataBarFontsize = 4,
  legend_direction = "horizontal",
  annotate_by_pathology = TRUE,
  show_heatmap_legend = TRUE,
  cut_k,
  width = 10
)

Arguments

return_data: Default False
include_silent: Default False
include_hotspots: Default False
review_hotspots: Default False
bonferroni: Default False
verbose: Default FALSE

Examples

suppressMessages(library(GAMBLR.open))
suppressMessages(library(ComplexHeatmap))

bl_fl_dlbcl_meta = get_gambl_metadata() %>%
  dplyr::filter(pathology %in% c("DLBCL","FL","BL"), seq_type != "mrna") %>%
  check_and_clean_metadata(.,duplicate_action="keep_first")
#> Using the bundled metadata in GAMBLR.data...
#> Duplicate rows (keeping first occurrence) for 'sample_id' and 'seq_type' have been dropped.
dlbcl_meta = dplyr::filter(bl_fl_dlbcl_meta,pathology=="DLBCL") %>%
             check_and_clean_metadata(.,duplicate_action="keep_first")

all_coding <- get_all_coding_ssm(bl_fl_dlbcl_meta)

if (FALSE) { # \dontrun{
lymphgens = get_lymphgen(flavour = "no_cnvs.no_sv.with_A53")
lg_feats = lymphgens$feature_annotation
lg_genes = unique(lg_feats$Feature)

pretty_mutual_exclusivity(
   maf_data = all_coding,
   genes = lg_genes,
   these = dlbcl_meta,
   size_factor =  0.007,
   engine = "ComplexHeatmap",
   font_size = 6,
   use_alpha = FALSE,
   clustering_distance = "binary",
   include_hotspots = TRUE)
} # }

fl_bl_dlbcl_genes = dplyr::filter(GAMBLR.data::lymphoma_genes,
  FL_Tier == 1 | BL_Tier == 1 | DLBCL_Tier ==1) %>%
  pull(Gene)

# because the first steps of this are slow we can
# store the output matrix as a shortcut for subsequent runs

suppressWarnings(
  suppressMessages({
outs = pretty_mutual_exclusivity(
  maf_data = all_coding,
  genes = fl_bl_dlbcl_genes,
  these = bl_fl_dlbcl_meta,
  engine = "ComplexHeatmap",
  font_size = 5,
  use_alpha = TRUE,
  clustering_distance = "binary",
  include_hotspots = FALSE,
  return_data = TRUE
)
draw(outs$plot)

}))


suppressWarnings(
  suppressMessages({

pretty_mutual_exclusivity(
  mut_mat=outs$mut_mat,
  corr_mat = outs$corr_mat,
  p_mat = outs$p_mat,
  maf_data = all_coding,
  genes = fl_bl_dlbcl_genes,
  these = bl_fl_dlbcl_meta,
  engine = "ComplexHeatmap",
  font_size = 5,
  use_alpha = TRUE,
  size_factor = 0.004,
  clustering_distance = "euclidean",
  include_hotspots = FALSE
)

}))


suppressWarnings(
  suppressMessages({

pretty_mutual_exclusivity(
  p_mat = outs$p_mat,
  maf_data = all_coding,
  genes = fl_bl_dlbcl_genes,
  these = dlbcl_meta,
  engine = "ComplexHeatmap",
  font_size = 5,
  use_alpha = TRUE,
  size_factor = 0.004,
  clustering_distance = "euclidean",
  legend_direction = "vertical",
  include_hotspots = FALSE)

}))