package rankers
Install
Dune Dependency
Authors
Maintainers
Sources
sha256=3404a48a2af13c04fd258a9b968e849899783012f312405b4c2aede27945ad4d
md5=3e63f2fca02a81c6dc8156546446a765
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: 12 Feb 2020
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