liver

Liver QTL data was obtained from a F2 inner-cross between inbred MRL/MpJ and SM/J 
strains of mice.

Belief propagation methods in Bayesian Networks to propagate evidence through the network. The implementation of these methods are based on the article: Cowell, RG (2005). Local Propagation in Conditional Gaussian Bayesian Networks <https://www.jmlr.org/papers/v6/cowell05a.html>. For details please see Yu et. al. (2020) BayesNetBP: An R Package for Probabilistic Reasoning in Bayesian Networks <doi:10.18637/jss.v094.i03>. The optional 'cyjShiny' package for running the Shiny app is available at <https://github.com/cytoscape/cyjShiny>. Please see the example in the documentation of 'runBayesNetApp' function for installing 'cyjShiny' package from GitHub.

Han Yu

BayesNetBP

Bayesian Network Belief Propagation

liver function

The data set <code>liver</code> contains three objects: the data, a learned Bayesian network structure 
and <code>vector</code> specifying node type. The fields are described as follows:<dl class="dl-horizontal">
 <dt><code>data</code></dt><dd>a <code>data.frame</code> object that contains 280 samples (rows) and 15 variables: genotype data 
 (genotype states at 5 SNP markers) and phenotype data (HDL levels and normalized expression values of 10 genes). 
 Three of these phenotypes are dichotomized, including Cyp2b10, Spgl1 and HDL. Genotypes and dichotomized phenotypes 
 are of class <code>factor</code> and continuous phenotypes are of class <code>numeric</code>.</dd>
 <dt><code>dag</code></dt><dd>a <code>graphNEL</code> object, which is the network structure learned by <code>qtlnet</code> package.</dd>
 <dt><code>node.class</code></dt><dd>a named <code>vector</code> of <code>logical</code> values indicating whether each node is discrete.</dd>
</dl>

Format

Mus Musculus HDL QTL data from Leduc et. al. (2012) — liver

The data set <code>liver</code> contains three objects: the data, a learned Bayesian network structure 
and <code>vector</code> specifying node type. The fields are described as follows:<dl class='dl-horizontal'>
 <dt><code>data</code></dt><dd>a <code>data.frame</code> object that contains 280 samples (rows) and 15 variables: genotype data 
 (genotype states at 5 SNP markers) and phenotype data (HDL levels and normalized expression values of 10 genes). 
 Three of these phenotypes are dichotomized, including Cyp2b10, Spgl1 and HDL. Genotypes and dichotomized phenotypes 
 are of class <code>factor</code> and continuous phenotypes are of class <code>numeric</code>.</dd>
 <dt><code>dag</code></dt><dd>a <code>graphNEL</code> object, which is the network structure learned by <code>qtlnet</code> package.</dd>
 <dt><code>node.class</code></dt><dd>a named <code>vector</code> of <code>logical</code> values indicating whether each node is discrete.</dd>
</dl>

liver: Mus Musculus HDL QTL data from Leduc et. al. (2012)

Description

Usage

Arguments

Format

References