penInit

This function can be used to initialize a penalization matrix for bnclustOmics clustering

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

penInit function

<dl><dt>bnnames</dt>
<dd>object of class bnInfo; see bnInfo</dd>
<dt>pfbase</dt>
<dd>a numeric value more or equal to 1, base penalization factor; 1 by default (no penalization)</dd>
<dt>intpf</dt>
<dd>(optional) a numeric value more or equal to 1, this value will be used to penalize interactions from 'intlist'</dd>
<dt>intlist</dt>
<dd>(optional) a matrix or data frame containing a list of interactions and optionally their scores; 2 columns are necessary 'gene1' and 'gene2'</dd>
<dt>intsame</dt>
<dd>penalization factor for edges connecting the same genes</dd>
<dt>usescore</dt>
<dd>(logical) when TRUE, interactions score from column 'score' of the parameter 'intlist' will be used to define penalization factor</dd></dl>

Arguments

Author

Initializing penalization matrix — penInit

<dl>

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


<dt>pfbase</dt>
<dd>a numeric value more or equal to 1, base penalization factor; 1 by default (no penalization)</dd>


<dt>intpf</dt>
<dd>(optional) a numeric value more or equal to 1, this value will be used to penalize interactions from 'intlist'</dd>


<dt>intlist</dt>
<dd>(optional) a matrix or data frame containing a list of interactions and optionally their scores; 2 columns are necessary 'gene1' and 'gene2'</dd>


<dt>intsame</dt>
<dd>penalization factor for edges connecting the same genes</dd>


<dt>usescore</dt>
<dd>(logical) when TRUE, interactions score from column 'score' of the parameter 'intlist' will be used to define penalization factor</dd>

</dl>

penInit: Initializing penalization matrix

Description

Usage

Value

Arguments

Author