View source: R/visualization.R
GenePathwayOncoplots | R Documentation |
takes output generated by read.maf and draws an GenePathwayOncoplots.
GenePathwayOncoplots( maffile, gene_path, freq_matrix, risk_score, cut_off, final_character, 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 )
maffile |
an MAF object generated by read.maf. |
gene_path |
User input pathways geneset list. |
freq_matrix |
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_character |
The pathway signature,use to map gene in the GenePathwayOncoplots. |
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'. |
No return value
#get the path of the mutation annotation file and samples' survival data maf<-system.file("extdata","data_mutations_extended.txt",package = "pathwayTMB") sur_path<-system.file("extdata","sur.csv",package = "pathwayTMB") sur<-read.csv(sur_path,header=TRUE,row.names = 1) #perform the function 'get_mut_matrix' mut_matrix<-get_mut_matrix(maffile=maf,mut_fre = 0.01,is.TCGA=FALSE,sur=sur) #perform the function `get_PTMB` PTMB_matrix<-get_PTMB(freq_matrix=mut_matrix,genesmbol=genesmbol,gene_path=gene_path) set.seed(1) final_character<-get_final_signature(PTMB=PTMB_matrix,sur=sur) #calculate the risksciore riskscore<-plotKMcurves(t(PTMB_matrix[final_character,]),sur=sur,plots=FALSE)$risk_score cut<-median(riskscore) GenePathwayOncoplots(maf,gene_path,mut_matrix,riskscore,cut,final_character)
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