get_Oncoplots: draw an GenePathwayOncoplots
In PMAPscore: Identify Prognosis-Related Pathways Altered by Somatic Mutation

get_Oncoplots

R Documentation

draw an GenePathwayOncoplots

Description

Load the data in MAF format and draws an GenePathwayOncoplots.

Usage

get_Oncoplots(
  maffile,
  path_gene,
  mut_status,
  risk_score,
  cut_off,
  final_signature,
  pathway_name,
  isTCGA = FALSE,
  top = 20,
  clinicalFeatures = "sample_group",
  annotationColor = c("red", "green"),
  sortByAnnotation = TRUE,
  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
)

Arguments

`maffile`	A data of MAF format.
`path_gene`	User input pathways geneset list.
`mut_status`	The mutations matrix,generated by 'get_mut_matrix'.
`risk_score`	Samples' PTMB-related risk score,which could be a biomarker for survival analysis and immunotherapy prediction.
`cut_off`	A threshold value(the median risk score as the default value).Using this value to divide the sample into high and low risk groups with different overall survival.
`final_signature`	The pathway signature,use to map gene in the GenePathwayOncoplots.
`pathway_name`	The name of the pathway that you want to visualize.For example "Gap junction"
`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. Dafault "sample_group".
`annotationColor`	Custom colors to use for sample annotation-"sample_group". Must be a named list containing a named vector of colors. Default "red" and "green".
`sortByAnnotation`	Logical sort oncomatrix (samples) by provided 'clinicalFeatures'. Sorts based on first 'clinicalFeatures'. Defaults to TRUE. column-sort.
`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'.

Value

No return value

Examples

#obtain the risksciore
data(km_data)
risk_score<-km_data$multiple_score
names(risk_score)<-rownames(km_data)
cut_off<-median(risk_score)
#load the dtata
data(final_signature,path_gene,mut_status,maffile)
##draw an GenePathwayOncoplots
get_Oncoplots(maffile,path_gene,mut_status,risk_score,cut_off,final_signature,"Gap junction")

PMAPscore documentation built on April 12, 2022, 9:06 a.m.