I want to find some good predictors (genes). This is my data, log transformed RNA-seq:
TRG CDK6 EGFR KIF2C CDC20
Sample 1 TRG12 11.39 10.62 9.75 10.34
Sample 2 TRG12 10.16 8.63 8.68 9.08
Sample 3 TRG12 9.29 10.24 9.89 10.11
Sample 4 TRG45 11.53 9.22 9.35 9.13
Sample 5 TRG45 8.35 10.62 10.25 10.01
Sample 6 TRG45 11.71 10.43 8.87 9.44
I have calculated confusion matrix for different models like below
1- I tested each of 23 genes individually in this code and each of them gives p-value < 0.05 remained as a good predictor; For example for CDK6 I have done
glm=glm(TRG ~ CDK6, data = df, family = binomial(link = 'logit'))
Finally I obtained five genes and I put them in this model:
final <- glm(TRG ~ CDK6 + CXCL8 + IL6 + ISG15 + PTGS2 , data = df, family = binomial(link = 'logit'))
I want a plot like this for ROC curve of each model but I don't know how to do that
Any help please?