Bootstrap AUC

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To test whether the difference in AUC/logAUC between two methods is statistically significant or not, AUC/logAUC of the new developed method(s) against the reference method can be compared with bootstrap.

Files needed:

  • ligands.name --> file with ligand names to perform enrichment
  • decoys.name --> file with decoy names to perform enrichment
  • score file(s) --> extract_all.sort.uniq.txt

First, the anaconda python environment needs to be set:

source /nfs/home/yingyang/.cshrc_anaconda

Plot the variation of AUC/logAUC

python /nfs/home/yingyang/work/scripts/bootstrap_AUC.py \
-l ./ligands.name -d ./decoys.name \
-s1 extract_all.sort.uniq.txt \
-p single

The figure will looks like this:

Variation AUC logAUC.png

Plot the change(s) in AUC/logAUC against reference score

python /nfs/home/yingyang/work/scripts/bootstrap_AUC.py \
-l ../ligands.name -d ../decoys.name \
-s1 score.standard -s2 score.amber score.freeform \
-p compare
Fig compare methods.png

Delta AUC and delta logAUC will be computed and displayed. The p-value from paired t-test indicate if change is statistically significant or not.