Skip to contents

Prep data for oncoplot

Source: R/oncoplot.R
ggoncoplot_prep_df.Rd

Prep data for oncoplot

Usage

ggoncoplot_prep_df(
  data,
  col_genes,
  col_samples,
  genes_for_oncoplot,
  col_mutation_type = NULL,
  col_tooltip = col_samples,
  pathway = NULL,
  verbose = TRUE
)

Arguments

data

data for oncoplot. A data.frame with 1 row per mutation in your cohort. Must contain columns describing gene_symbols and sample_identifiers (data.frame)

col_genes

name of data column containing gene names/symbols (string)

col_samples

name of data column containing sample identifiers (string)

genes_for_oncoplot

a list of genes to include in the oncoplot (character).

col_mutation_type

name of data column describing mutation types (string)

col_tooltip

name of data column containing whatever information you want to display in (string)

pathway

a two column dataframe describing pathway. The column containing gene names should have the same name as col_gene (data.frame, optional)

verbose

verbose mode (flag, default TRUE)

Value

dataframe with the following columns: 'Gene', 'Sample', 'MutationType', 'Tooltip'. Sample is a factor with levels sorted in appropriate order for oncoplot vis. Genes represents either topn genes or specific genes set by genes_to_include

Examples

#' # ===== GBM =====
gbm_csv <- system.file(
  package = "ggoncoplot",
  "testdata/GBM_tcgamutations_mc3_maf.csv.gz"
)

gbm_df <- read.csv(file = gbm_csv, header = TRUE)

# Get genes in appropriate order for oncoplot
genes_for_oncoplot <- ggoncoplot:::get_genes_for_oncoplot(
  data = gbm_df,
  col_samples = "Tumor_Sample_Barcode",
  col_genes = "Hugo_Symbol",
  topn = 20,
  verbose = FALSE
)

# Create dataframe basis of oncoplot (1 row per sample-gene combo)
ggoncoplot:::ggoncoplot_prep_df(
  gbm_df,
  col_genes = "Hugo_Symbol",
  col_samples = "Tumor_Sample_Barcode",
  col_mutation_type = "Variant_Classification",
  genes_for_oncoplot = genes_for_oncoplot
)
#> # A tibble: 1,057 × 5
#>    Sample          Gene   MutationType      MutationCount Tooltip        
#>    <fct>           <fct>  <chr>                     <int> <chr>          
#>  1 TCGA-19-5956-01 PTEN   Multi_Hit                     3 TCGA-19-5956-01
#>  2 TCGA-19-5956-01 TP53   Multi_Hit                     2 TCGA-19-5956-01
#>  3 TCGA-19-5956-01 TTN    Multi_Hit                    28 TCGA-19-5956-01
#>  4 TCGA-19-5956-01 EGFR   Missense_Mutation             1 TCGA-19-5956-01
#>  5 TCGA-19-5956-01 MUC16  Multi_Hit                    15 TCGA-19-5956-01
#>  6 TCGA-19-5956-01 FLG    Multi_Hit                     8 TCGA-19-5956-01
#>  7 TCGA-19-5956-01 NF1    Multi_Hit                     3 TCGA-19-5956-01
#>  8 TCGA-19-5956-01 RYR2   Missense_Mutation             1 TCGA-19-5956-01
#>  9 TCGA-19-5956-01 ATRX   Multi_Hit                     5 TCGA-19-5956-01
#> 10 TCGA-19-5956-01 PIK3R1 Multi_Hit                     2 TCGA-19-5956-01
#> # ℹ 1,047 more rows