library(ggplot2)
library(reshape2)
library(ccmap)
library(ccdata)
#---------------
#load in cmap data
data(cmap_es)
data(atc4)
drugs <- colnames(cmap_es)
#get similarity matrix long
tsim <- get_tan_sim(cmap_es, es=TRUE)
#get tp/fp rates
trates <- get_rates(tsim, atc4)
#put tp/fp rates into dataframe
trates_df <- data.frame(fp=trates$fp, tp=trates$tp)
#plot tp vs fp
ggplot(trates_df, aes(fp, tp)) + geom_point()
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