package rankers
Install
Dune Dependency
Authors
Maintainers
Sources
sha256=794a7c2d09d56a5b267b05618b25c4e8263b4eb3cc5ed4371d1f1616b870f10b
md5=aab7f7218b1514cfeb09068058436453
Description
Reference implementation of the Vanishing Ranking Kernels method.
A single parameter QSAR modeling technique for HTS data; with an applicability domain.
Manuscript to appear soon.
Published: 13 Jan 2023
README
RanKers
Reference implementation of the Vanishing Ranking Kernels (VRK) method
How to install the software
For beginners/non opam users: download and execute the latest self-installer shell script from (https://github.com/UnixJunkie/rankers/releases).
Then execute:
./rankers-1.0.0.sh ~/usr/rankers-1.0.0
This will create ~/usr/rankers-1.0.0/bin/rankers_bwmine, among other things in the same directory.
For opam users:
opam install rankers
Do not hesitate to contact the author in case you have problems installing or using the software or if you have any question.
Example
Example ROC curve on a hold-out test set. The test set had 38 active molecules and 664 inactives. ROC AUC: 0.861; BEDROC AUC: 0.766; PR AUC: 0.678. The ROC curve is in purple; the precision-recall (PR) curve in cyan. The probability of activity given a raw score is the red curve. The green curve is the number of actives divided by the number of decoys as a function of the scores filtering threshold.
Train and test a model:
rankers_bwmine -i data/tox21_nrar_ligands_std_rand_01.txt
Same, but using 16 cores :
rankers_bwmine -np 16 -i data/tox21_nrar_ligands_std_rand_01.txt
Usage
rankers_bwmine -i <train.txt>
[-p <float>]: proportion of the (randomized) dataset
used to train (default=0.80)
[-k {uni|tri|epa|biw}]: kernel function choice (default=biw)
[-np <int>]: max number of processes (default=1)
[-o <filename>]: write raw test scores to file
[--train <train.txt>]: training set (overrides -p)
[--valid <valid.txt>]: validation set (overrides -p)
[--test <test.txt>]: test set (overrides -p)
[-n <int>]: max number of optimization steps; default=150
[--capf <float>]: keep only fraction of decoys
[--capx <int>]: keep only X decoys per active
[--capi <int>]: limit total number of molecules
(but keep all actives)
[--seed <int>: fix random seed]
[--pr]: use PR AUC instead of ROC AUC during optimization
[-kb <float>]: user-chosen kernel bandwidth
[--mcc-scan]: scan classif. threshold to maximize MCC
[--tap]: tap the train-valid-test partitions to disk
[-q|--quick]: exit early; just after model training
[--noplot]: turn off gnuplot
[-v]: verbose/debug mode
[-h|--help]: show this help message