bnclustNetworks

This function derives consensus models of networks representing all clusters based on several
threshold for posterior probabilities of individual edges.

Unsupervised Bayesian network-based clustering of multi-omics data. Both binary and continuous data types
are allowed as inputs. The package serves a dual purpose: it clusters (patient) samples and learns the multi-omics networks that characterize discovered
clusters. Prior network knowledge (e.g., public interaction databases) can be included via blacklisting and
penalization matrices. For clustering, the EM algorithm is employed. For structure search at the M-step,
the Bayesian approach is used. The output includes membership assignments of samples, cluster-specific MAP networks, and posterior probabilities
of all edges in the discovered networks. In addition to likelihood, AIC and BIC scores are returned. They can be used for choosing the number
of clusters.
References:
P. Suter et al. (2021) <doi:10.1101/2021.12.16.473083>,
J. Kuipers and P. Suter and G. Moffa (2022) <doi:10.1080/10618600.2021.2020127>,
J. Kuipers et al. (2018) <doi:10.1038/s41467-018-06867-x>.

Polina Suter

bnClustOmics

Bayesian Network-Based Clustering of Multi-Omics Data

Jack Kuipers

bnclustNetworks function

<dl><dt>bnres</dt>
<dd>an object of class 'bnclustOmics'; see bnclustOmics</dd>
<dt>bnnames</dt>
<dd>an object of class 'bnInfo'; see bnInfo</dd>
<dt>sump</dt>
<dd>threshold for the sum of posterior probabilities in all discovered networks</dd>
<dt>minp</dt>
<dd>threshold for the minimum posterior probability in at least one network, when the sum of posterioirs is bigger than sump</dd>
<dt>minkp</dt>
<dd>threshold for the minimum posterior probability in at least one network, when the sum of posterioirs is less than sump</dd>
<dt>maxkp</dt>
<dd>(optional) threshold for the maximum posterior probability in at least one network; used to esclude cluster specific edges from the edges with high sum of posterioirs (&gt;sump)</dd></dl>

Arguments

Deriving consensus networks based on posterior probabilities of mixture model — bnclustNetworks

<dl>

<dt>bnres</dt>
<dd>an object of class 'bnclustOmics'; see bnclustOmics</dd>


<dt>bnnames</dt>
<dd>an object of class 'bnInfo'; see bnInfo</dd>


<dt>sump</dt>
<dd>threshold for the sum of posterior probabilities in all discovered networks</dd>


<dt>minp</dt>
<dd>threshold for the minimum posterior probability in at least one network, when the sum of posterioirs is bigger than sump</dd>


<dt>minkp</dt>
<dd>threshold for the minimum posterior probability in at least one network, when the sum of posterioirs is less than sump</dd>


<dt>maxkp</dt>
<dd>(optional) threshold for the maximum posterior probability in at least one network; used to esclude cluster specific edges from the edges with high sum of posterioirs (&gt;sump)</dd>

</dl>

bnclustNetworks: Deriving consensus networks based on posterior probabilities of mixture model

Description

Usage

Value

Arguments

Examples