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bnClustOmics  

Bayesian Network-Based Clustering of Multi-Omics Data
View on CRAN: Click here


Download and install bnClustOmics package within the R console
Install from CRAN:
install.packages("bnClustOmics")

Install from Github:
library("remotes")
install_github("cran/bnClustOmics")

Install by package version:
library("remotes")
install_version("bnClustOmics", "1.1.1")



Attach the package and use:
library("bnClustOmics")
Maintained by
Polina Suter
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-06-10
Latest Update: 2022-08-05
Description:
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) , J. Kuipers and P. Suter and G. Moffa (2022) , J. Kuipers et al. (2018) .
How to cite:
Polina Suter (2022). bnClustOmics: Bayesian Network-Based Clustering of Multi-Omics Data. R package version 1.1.1, https://cran.r-project.org/web/packages/bnClustOmics. Accessed 24 Apr. 2025.
Previous versions and publish date:
1.0.9 (2022-06-10 11:10), 1.1.1 (2022-08-05 16:50)
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