plotROC {pathwayTMB} | R Documentation |
plot the ROC curve
Description
This function uses to plot a ROC curve.
Usage
plotROC(
riskscore,
response,
main,
add = FALSE,
col = par("col"),
legacy.axes = TRUE,
print.auc = FALSE,
grid = FALSE,
auc.polygon = FALSE,
auc.polygon.col = "skyblue",
max.auc.polygon = FALSE,
max.auc.polygon.col = "#EEEEEE"
)
Arguments
riskscore |
a numeric vector of the same length than response, containing the predicted value of each observation. |
response |
a factor, numeric or character vector of responses (true class), typically encoded with 0 (controls) and 1 (cases). Only two classes can be used in a ROC curve. |
main |
the title of the ROC curve |
add |
if TRUE, the ROC curve will be added to an existing plot. If FALSE (default), a new plot will be created. |
col |
the color of the ROC curve |
legacy.axes |
a logical indicating if the specificity axis (x axis) must be plotted as as decreasing “specificity” (FALSE) or increasing “1 - specificity” (TRUE, the default) as in most legacy software. This affects only the axis, not the plot coordinates. |
print.auc |
boolean. Should the numeric value of AUC be printed on the plot? |
grid |
boolean or numeric vector of length 1 or 2. Should a background grid be added to the plot? Numeric: show a grid with the specified interval between each line; Logical: show the grid or not. Length 1: same values are taken for horizontal and vertical lines. Length 2: grid value for vertical (grid[1]) and horizontal (grid[2]). Note that these values are used to compute grid.v and grid.h. Therefore if you specify a grid.h and grid.v, it will be ignored. |
auc.polygon |
boolean. Whether or not to display the area as a polygon. |
auc.polygon.col |
color (col) for the AUC polygon. |
max.auc.polygon |
boolean. Whether or not to display the maximal possible area as a polygon. |
max.auc.polygon.col |
color (col) for the maximum AUC polygon. |
Value
No return value
Examples
#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
#get the path of samples' immunotherapy response data
res_path<- system.file("extdata","response.csv",package = "pathwayTMB")
response<-read.csv(res_path,header=TRUE,stringsAsFactors =FALSE,row.name=1)
plotROC(riskscore=riskscore,response=response,main="Objective Response",print.auc=TRUE)