create ROC curve and determine optimal cut-off and establishing PPV

Using the below script I was able to create a labeled and coloured boxplot and calculate p-value for 2 classes, eg LB/B and LP/P which were established by VKGL.
Now I want to create an ROC curve for both classes thereby determining the optimal cut-off (youden index) and in addtion determine the PPV. Is possible to integrate this in the below script?

Does anybody have an idea how to do this?

Note, I have already installed following packagess

install.packages("tidyverse")

install.packages("dplyr")

install.packages('xlsx')

install.packages("ggpubr")

my_data %>%

  • filter(classification %in% c("LB/B", "LP/P") & Source %in% c("VKGL"))%>%
  • ggplot(mapping=aes(x=classification, y= Backbone Hbond, color="red", fill = "orange", alpha=0.2))+
  • geom_boxplot()+
  • labs(title = "Backbone Hbond for LB/B and LP/P classes (VKGL)",
  •    x = "Classification",
    
  •    y = "Backbone Hbond")+
    
  • stat_compare_means(label.x = 1.3, size = 4)

Thanks,

Rene

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