Pathway Enrichment Analysis Based on Bayesian Network
c(person("Samaneh","Maleknia",role = c("aut","cre"),email = "maleknias@gmail.com"),person("Mohsen","Namazi",role = "aut"),person("Kaveh","Kavousi",role = c("ctb")),person("Ali","Sharifi-Zarchi",role = c("ctb")),person("Vahid","Rezaei-Tabar",role = c("ctb")))
Maleknia et al. (2020) <doi:10.1101/2020.01.13.905448>. A novel pathway enrichment analysis package based on Bayesian network to investigate the topology features of the pathways. firstly, 187 kyoto encyclopedia of genes and genomes (KEGG) human non-metabolic pathways which their cycles were eliminated by biological approach, enter in analysis as Bayesian network structures. The constructed Bayesian network were optimized by the Least Absolute Shrinkage Selector Operator (lasso) and the parameters were learned based on gene expression data. Finally, the impacted pathways were enriched by Fisher’s Exact Test on significant parameters.
NetworkEnrichment, GeneExpression, Pathways, Bayesian, KEGG
bnlearn, corpcor, glmnet, graph, stats, utils
Samaneh Maleknia [aut, cre],
Mohsen Namazi [aut],
Kaveh Kavousi [ctb],
Ali Sharifi-Zarchi [ctb],
Vahid Rezaei-Tabar [ctb]

Bacterium and virus analysis of Orthologous Groups (BOG) is a
package for identifying differentially regulated genes in the
light of gene functions.
Jincheol Park, Cenny Taslim, Shili Lin, The Ohio State
University
It is designed to identify COG (Cluster of Orthologous
Groups) that are either over or under-represented among genes
that show differential expression under two different
conditions using statistical analysis and graphical
representations.

Bacterium and Virus Analysis of Orthologous Groups (BOG) is a
Package for Identifying Differentially Regulated Genes in the
Light of Gene Functions
Jincheol Park (Keimyung University, South Korea), Cenny Taslim, Shili Lin (The Ohio State University, USA)
An implementation of three statistical tests for identification of COG (Cluster of Orthologous Groups) that are over represented among genes that show differential expression under conditions. It also provides tabular and graphical summaries of the results for easy visualisation and presentation.