Output priors (deal only)

The priors for a deal network may be output to file for inspection with the -output-priors. The deal Bayesian network model has a quite complex default prior which is based on the given network data, structure and imaginary sample size, see [1] for details. The bnlearn Bayesian network, which is the recommended and default Bayesian network model, has no prior to output, see [8] for details.

Options

The options are as follows:

Option	Description	Default
-output-priors	do a task to output the priors of a network to file
-output-priors-name name	label the task with a name	Task-n
-output-priors-network-name network	output priors for this network	previous network (or the default model given by a node for each data variable and no edges if there is no previous network)
-output-priors-file priors.dat	output the priors to file priors.dat	priors.dat

Example

The following is an example parameter file to output the priors of a network.

#input continuous data
-input-data
-input-data-file example-cts.dat
-input-data-cts

#input discrete data
-input-data
-input-data-file example-discrete.dat
-input-data-discrete

#input SNP data as discrete data
-input-data
-input-data-file example.bed
-input-data-discrete-snp

#input the example network in format 1
-input-network
-input-network-file example-network-format1.dat
-input-network-type deal

#output the priors to file
-output-priors
-output-priors-file example-priors.dat

This parameter file, paras-output-priors.txt, can be found in example.zip and can be used as follows:

./bayesnetty paras-output-priors.txt

Which should produce output that looks like something as follows:

BayesNetty: Bayesian Network software, v1.00
--------------------------------------------------
Copyright 2015-present Richard Howey, GNU General Public License, v3
Institute of Genetic Medicine, Newcastle University

Random seed: 1551957572
--------------------------------------------------
Task name: Task-1
Loading data
Continuous data file: example-cts.dat
Number of ID columns: 2
Including (all) 2 variables in analysis
Each variable has 1500 data entries
Missing value: not set
--------------------------------------------------
--------------------------------------------------
Task name: Task-2
Loading data
Discrete data file: example-discrete.dat
Number of ID columns: 2
Including the 1 and only variable in analysis
Each variable has 1500 data entries
Missing value: NA
--------------------------------------------------
--------------------------------------------------
Task name: Task-3
Loading data
SNP binary data file: example.bed
SNP data treated as discrete data
Total number of SNPs: 2
Total number of subjects: 1500
Number of ID columns: 2
Including (all) 2 variables in analysis
Each variable has 1500 data entries
--------------------------------------------------
--------------------------------------------------
Task name: Task-4
Loading network
Network file: example-network-format1.dat
Network type: deal
Total number of nodes: 5 (Discrete: 3 | Factor: 0 | Continuous: 2)
Total number of edges: 4
Network Structure: [mood][rs1][rs2][pheno|rs1:rs2][express|pheno:mood]
Imaginary sample size: 10
Total data at each node: 1495
Missing data at each node: 5
--------------------------------------------------
--------------------------------------------------
Task name: Task-5
Outputting priors
Network: Task-4
Network Structure: [mood][rs1][rs2][pheno|rs1:rs2][express|pheno:mood]
Output priors to file: example-priors.dat
--------------------------------------------------

Run time: less than one second

The data is loaded, the network input and then the prior is output to a file.