|Did you know ...||Search Documentation:|
|Packs (add-ons) for SWI-Prolog|
|Title:||BNs for large cohort genomic studies.|
|Rating:||Not rated. Create the first rating!|
|Author:||Nicos Angelopoulos http://stoics.org.uk/~nicos|
|Maintainer:||Nicos Angelopoulos http://stoics.org.uk/~nicos|
|Packager:||Nicos Angelopoulos http://stoics.org.uk/~nicos|
No reviews. Create the first review!.
gBN runs the BN learning algorithm Gobnilp and implements many post-processing visualisation functions for analysing large scale patient studies from genomic information. Specially so for cancer patient data.
Currently only tested on *nix like systems. Developed on Linux Mint 2020.\ It should also work on MacOS with one of the linux-like platforms installed.
The following executables should be installed on your local machine.
The following R packages will be asked for installation at loading time, if not already present in local R installation.
Pack lib (
pack(lib)), developed by us is central to loading all the Prolog dependencies.
% swipl ?- pack_install(lib).
The following will be installed, interactively, by
pack(lib), at loading time if they are not
already present in the local SWI installation.
% swipl ?- pack_install(mtx).
All packs installable this way can be found on the SWI-Prolog pack list.
% swipl ?- pack_install(gbn). ?- use_module(library(gbn)). % Loading installed R library: RColorBrewer % Loading installed R library: cowplot % Loading installed R library: ggplot2 % Loading installed R library: ggpubr % Loading installed R library: gridExtra ?- gbn([debug(true)]). % Turning debugging on for predicate handle: gbn(gbn) % Options: [$restore(gbn,debug,false),copy(false),data(pack(gbn/data/asia.dat)),display_dot(svg),odir(_33202),std_output(std_file)] % Output directory: 'asia-20.09.27' % Settings on: asia.set
A more complex example:
% swipl ?- use_module(library(gbn)). ?- [cancer(aml)]. ?- aml. % Starting: aml % Starting: fisher_nets % Starting: fam_hmaps % Starting: gates_nets % Starting: svg_legend % Finished: aml true.
The above would create an output directory: aml_min60-21.01.19 where the date stamp will reflect the current date.
Cancer datasets from our paper (each can be run as per example above):
Datasets are in the source directory: data/ (with cancer datasets in data/gbns_in_cancer/).
Nicos Angelopoulos,\ London, 2021
Pack contains 132 files holding a total of 9.0M bytes.