Oncoplot: Drawing a waterfall plot of a particular pathway.

In ssMutPA: Single-Sample Mutation-Based Pathway Analysis

Drawing a waterfall plot of a particular pathway.

Description

Load the data in MAF format and draw a waterfall plot.

Usage

Oncoplot(
  maf,
  samp_class,
  sur,
  mut_status,
  pathway,
  pathway_name,
  isTCGA = FALSE,
  top = 20,
  clinicalFeatures = c("sample_group", "event"),
  class_col = c("#00468B", "#ED0000"),
  event_col = c("#B3DE69", "#BC80BD"),
  sortByAnnotation = TRUE,
  gene_mar = 7,
  removeNonMutated = FALSE,
  drawRowBar = TRUE,
  drawColBar = TRUE,
  leftBarData = NULL,
  leftBarLims = NULL,
  rightBarData = NULL,
  rightBarLims = NULL,
  topBarData = NULL,
  logColBar = FALSE,
  draw_titv = FALSE,
  showTumorSampleBarcodes = FALSE,
  fill = TRUE,
  showTitle = TRUE,
  titleText = NULL,
  vc_cols = NULL
)

Arguments

maf	A data of MAF format.
samp_class	A vector containing subtype labels of the samples.
sur	A matrix containing the samples' survival time and survival status.
mut_status	A binary mutations matrix.The file can be generated by the function 'get_mut_status'.
pathway	A list containing pathway information .
pathway_name	The names of the pathways that you want to visualize.For example "JAK-STAT signaling pathway".
isTCGA	Is input MAF file from TCGA source? If TRUE uses only first 12 characters from Tumor_Sample_Barcode.
top	How many top genes to be drawn,genes are arranged from high to low depending on the frequency of mutations. defaults to 20.
clinicalFeatures	Columns names from 'clinical.data' slot of MAF to be drawn in the plot.
class_col	The color of sample class .
event_col	The color of survival status .
sortByAnnotation	Logical sort oncomatrix (samples) by provided 'clinicalFeatures'. Sorts based on first 'clinicalFeatures'. Defaults to TRUE. column-sort.
gene_mar	Margin width for gene names.
removeNonMutated	Logical. If TRUE removes samples with no mutations in the GenePathwayOncoplots for better visualization. Default FALSE.
drawRowBar	Logical. Plots righ barplot for each gene. Default TRUE.
drawColBar	Logical plots top barplot for each sample. Default TRUE.
leftBarData	Data for leftside barplot. Must be a data.frame with two columns containing gene names and values. Default 'NULL'.
leftBarLims	Limits for 'leftBarData'. Default 'NULL'.
rightBarData	Data for rightside barplot. Must be a data.frame with two columns containing to gene names and values. Default 'NULL' which draws distibution by variant classification. This option is applicable when only 'drawRowBar' is TRUE.
rightBarLims	Limits for 'rightBarData'. Default 'NULL'.
topBarData	Default 'NULL' which draws absolute number of mutation load for each sample. Can be overridden by choosing one clinical indicator(Numeric) or by providing a two column data.frame contaning sample names and values for each sample. This option is applicable when only 'drawColBar' is TRUE.
logColBar	Plot top bar plot on log10 scale. Default FALSE.
draw_titv	Logical Includes TiTv plot. Default FALSE
showTumorSampleBarcodes	Logical to include sample names.
fill	Logical. If TRUE draws genes and samples as blank grids even when they are not altered.
showTitle	Default TRUE.
titleText	Custom title. Default 'NULL'.
vc_cols	named vector of colors for each Variant_Classification.

Value

A waterfall plot

Examples

#load the data
mut_path <- system.file("extdata","maffile.txt",package = "ssMutPA")
maf<-maftools::read.maf(mut_path ,isTCGA = FALSE)
pathway_path <- system.file("extdata","kegg_323_gmt.Rdata",package = "ssMutPA")
load(pathway_path)
data(samp_class_onco,mut_onco,sur_onco)
samples <- names(samp_class_onco)
samp_class_onco <- paste0("class_",samp_class_onco)
names(samp_class_onco) <- samples
sur_onco$event <- ifelse(sur_onco$event%in%1,"Dead","Alive")
col <- c("#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3")
##draw a waterfall plot
#win.graph()
Oncoplot(maf,samp_class_onco,sur_onco,mut_onco,kegg_323_gmt,"IL-17 signaling pathway",vc_cols=col)

ssMutPA documentation built on Oct. 16, 2024, 1:06 a.m.