In noriakis/CBNplot: plot bayesian network inferred from gene expression data based on enrichment analysis results

CBNplot: Bayesian network plot for clusterProfiler results

Introduction

The R package to infer and plot Bayesian networks. The network are inferred from expression data based on clusterProfiler or ReactomePA results. It makes use of libraries including clusterProfiler, ReactomePA, bnlearn, graphite and depmap. In this vignette, the description of functions and several use cases are depicted using random data. The more detailed use cases including the analysis of the dataset GSE133624, which contains RNA-Seq data of bladder cancer, can be found on the book (https://noriakis.github.io/CBNplot/).

Installation

BiocManager::install("CBNplot")

Usage

Generation of data

library(CBNplot)
library(bnlearn)
library(org.Hs.eg.db)

## Load data
data(gaussian.test)

## Draw genes in the KEGG pathway as DEG
kegg <- org.Hs.egPATH2EG
mapped <- mappedkeys(kegg)
genes <- as.list(kegg[mapped])[["00532"]]

## Random data
counts <- head(gaussian.test, length(genes))
row.names(counts) <- genes

## Perform enrichment analysis
pway <- clusterProfiler::enrichKEGG(gene = genes)
pway <- clusterProfiler::setReadable(pway, org.Hs.eg.db, keyType="ENTREZID")

The use of CBNplot

bngeneplot

Then use CBNplot. Basically, you need to supply the enrichment analysis result, normalized expression value and samples to be included. For bngeneplot, the pathway number in the result slot of enrichment analysis results must be given.

bngeneplot(results = pway,exp = counts, pathNum = 1, expRow="ENTREZID")

Data frame of raw values used in the inference, data frame containing strength and direction, averaged network, and plot can be obtained by specifying returnNet=TRUE

ret <- bngeneplot(results = pway,exp = counts, pathNum = 1, returnNet=TRUE, , expRow="ENTREZID")
head(ret$str)

The resulting network can be converted to igraph object using bnlearn::as.igraph().

g <- bnlearn::as.igraph(ret$av)
igraph::evcent(g)$vector

bnpathplot

The relationship between pathways can be drawn by bnpathplot. The number to be included in the inference can be specified by nCategory.

bnpathplot(results = pway,exp = counts, nCategory=5, shadowText = TRUE, expRow="ENTREZID")

bngeneplotCustom and bnpathplotCustom

bngeneplotCustom and bnpathplotCustom can be used to customize visualization with more flexibility, like highlighting the nodes and edges of interest by glowEdgeNum and hub.

bnpathplotCustom(results = pway, exp = counts, expRow="ENTREZID",
                 fontFamily="serif", glowEdgeNum=1, hub=1)
bngeneplotCustom(results = pway, exp = counts, expRow="ENTREZID",
                 pathNum=1, fontFamily="sans", glowEdgeNum=NULL, hub=1)

The detailed usage for the package, like including covariates to the plot and probabilistic reasoning is available in the package documentation (https://noriakis.github.io/CBNplot/).