TCGAvisualize_oncoprint: Creating a oncoprint

In BioinformaticsFMRP/TCGAbiolinks: TCGAbiolinks: An R/Bioconductor package for integrative analysis with GDC data

Creating a oncoprint

Description

Creating a oncoprint

Usage

TCGAvisualize_oncoprint(
  mut,
  genes,
  filename,
  color,
  annotation.position = "bottom",
  annotation,
  height,
  width = 10,
  rm.empty.columns = FALSE,
  show.column.names = FALSE,
  show.row.barplot = TRUE,
  label.title = "Mutation",
  column.names.size = 8,
  label.font.size = 16,
  rows.font.size = 16,
  dist.col = 0.5,
  dist.row = 0.5,
  information = "Variant_Type",
  row.order = TRUE,
  col.order = TRUE,
  heatmap.legend.side = "bottom",
  annotation.legend.side = "bottom"
)

Arguments

mut	A dataframe from the mutation annotation file (see TCGAquery_maf from TCGAbiolinks)
genes	Gene list
filename	name of the pdf
color	named vector for the plot
annotation.position	Position of the annotation "bottom" or "top"
annotation	Matrix or data frame with the annotation. Should have a column bcr_patient_barcode with the same ID of the mutation object
height	pdf height
width	pdf width
rm.empty.columns	If there is no alteration in that sample, whether remove it on the oncoprint
show.column.names	Show column names? Default: FALSE
show.row.barplot	Show barplot annotation on rows?
label.title	Title of the label
column.names.size	Size of the fonts of the columns names
label.font.size	Size of the fonts
rows.font.size	Size of the fonts
dist.col	distance between columns in the plot
dist.row	distance between rows in the plot
information	Which column to use as information from MAF. Options: 1) "Variant_Classification" (The information will be "Frame_Shift_Del", "Frame_Shift_Ins", "In_Frame_Del", "In_Frame_Ins", "Missense_Mutation", "Nonsense_Mutation", "Nonstop_Mutation", "RNA", "Silent" , "Splice_Site", "Targeted_Region", "Translation_Start_Site") 2) "Variant_Type" (The information will be INS,DEL,SNP)
row.order	Order the genes (rows) Default:TRUE. Genes with more mutations will be in the first rows
col.order	Order columns. Default:TRUE.
heatmap.legend.side	Position of the heatmap legend
annotation.legend.side	Position of the annotation legend

Value

A oncoprint plot

Examples

## Not run: 
library(dplyr)
query <- GDCquery(
   project = "TCGA-CHOL",
   data.category = "Simple Nucleotide Variation",
   access = "open",
   legacy = FALSE,
   data.type = "Masked Somatic Mutation",
   workflow.type = "Aliquot Ensemble Somatic Variant Merging and Masking"
)
GDCdownload(query)
mut <- GDCprepare(query)
TCGAvisualize_oncoprint(mut = mut, genes = mut$Hugo_Symbol[1:10], rm.empty.columns = TRUE)
TCGAvisualize_oncoprint(
  mut = mut, genes = mut$Hugo_Symbol[1:10],
  filename = "onco.pdf",
  color = c("background"="#CCCCCC","DEL"="purple","INS"="yellow","SNP"="brown")
)
clin <- GDCquery_clinic("TCGA-ACC","clinical")
clin <- clin[,c("bcr_patient_barcode","disease","gender","tumor_stage","race","vital_status")]
TCGAvisualize_oncoprint(
   mut = mut, genes = mut$Hugo_Symbol[1:20],
   filename = "onco.pdf",
   annotation = clin,
   color=c("background"="#CCCCCC","DEL"="purple","INS"="yellow","SNP"="brown"),
   rows.font.size=10,
   heatmap.legend.side = "right",
   dist.col = 0,
   label.font.size = 10
)

## End(Not run)

BioinformaticsFMRP/TCGAbiolinks documentation built on April 12, 2024, 2:08 a.m.