ssMutPA (version 0.1.2)

Oncoplot: 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
)

Value

A waterfall plot

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.

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)