Marginal Gene Barplot Breaks Too Dense

[selkamand]

Add options for customising the barplot breaks so density is not so

library(ggoncoplot)

# TCGA GBM dataset from TCGAmuations package
gbm_csv <- system.file(package='ggoncoplot', "testdata/GBM_tcgamutations_mc3_maf.csv.gz")
gbm_df <- read.csv(file = gbm_csv, header=TRUE)

gbm_clinical_csv <- system.file(
  package = "ggoncoplot",
  "testdata/GBM_tcgamutations_mc3_clinical.csv"
)

gbm_clinical_df <- read.csv(file = gbm_clinical_csv, header = TRUE)

ggoncoplot(
  gbm_df,
  col_genes = "Hugo_Symbol",
  col_samples = "Tumor_Sample_Barcode",
  col_mutation_type = "Variant_Classification",
  metadata = gbm_clinical_df,
  cols_to_plot_metadata = c('gender', 'histological_type', 'prior_glioma', 'tumor_tissue_site'), 
  draw_tmb_barplot = TRUE, 
  draw_gene_barplot = TRUE,
  show_all_samples = TRUE, 
  interactive = FALSE
)
#> ℹ 2 samples with metadata have no mutations. Fitering these out
#> ℹ To keep these samples, set `metadata_require_mutations = FALSE`. To view them in the oncoplot ensure you additionally set `show_all_samples = TRUE`
#> → TCGA-06-0165-01
#> → TCGA-06-0167-01
#> 
#> ── Identify Class ──
#> 
#> ℹ Found 7 unique mutation types in input set
#> ℹ 0/7 mutation types were valid PAVE terms
#> ℹ 0/7 mutation types were valid SO terms
#> ℹ 7/7 mutation types were valid MAF terms
#> ✔ Mutation Types are described using valid MAF terms ... using MAF palete
#> ! TMB plot: Ignoring `col_mutation_type` since `log10_transform = TRUE`.
#> This is because you cannot accurately plot stacked bars on a logarithmic scale

^{Created on 2024-06-18 with reprex v2.1.0}