bngeneplot: bngeneplot

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

bngeneplot

Description

Plot gene relationship within the specified pathway

Usage

bngeneplot(
  results,
  exp,
  expSample = NULL,
  algo = "hc",
  R = 20,
  returnNet = FALSE,
  algorithm.args = NULL,
  pathNum = NULL,
  convertSymbol = TRUE,
  expRow = "ENSEMBL",
  interactive = FALSE,
  cexCategory = 1,
  cl = NULL,
  showDir = FALSE,
  chooseDir = FALSE,
  scoreType = "bic-g",
  labelSize = 4,
  layout = "nicely",
  clusterAlpha = 0.2,
  strType = "normal",
  delZeroDegree = TRUE,
  otherVar = NULL,
  otherVarName = NULL,
  onlyDf = FALSE,
  disc = FALSE,
  tr = NULL,
  remainCont = NULL,
  sp = "hsapiens",
  compareRef = FALSE,
  compareRefType = "intersection",
  pathDb = "reactome",
  dep = NULL,
  depMeta = NULL,
  sizeDep = FALSE,
  showDepHist = TRUE,
  cellLineName = "5637_URINARY_TRACT",
  showLineage = FALSE,
  orgDb = org.Hs.eg.db,
  shadowText = TRUE,
  bgColor = "white",
  textColor = "black",
  strengthPlot = FALSE,
  nStrength = 10,
  strThresh = NULL,
  hub = NULL,
  seed = 1
)

Arguments

results	the enrichment analysis result
exp	gene expression matrix
expSample	candidate samples to be included in the inference default to all
algo	structure learning method used in boot.strength() default to "hc"
R	the number of bootstrap
returnNet	whether to return the network
algorithm.args	parameters to pass to bnlearn structure learnng function
pathNum	the pathway number (the number of row of the original result, ordered by p-value)
convertSymbol	whether the label of resulting network is converted to symbol, default to TRUE
expRow	the type of the identifier of rows of expression matrix
interactive	whether to use bnviewer (default to FALSE)
cexCategory	scaling factor of size of nodes
cl	cluster object from parallel::makeCluster()
showDir	show the confidence of direction of edges
chooseDir	if undirected edges are present, choose direction of edges (default: FALSE)
scoreType	score type to use on choosing direction
labelSize	the size of label of the nodes
layout	ggraph layout, default to "nicely"
clusterAlpha	if specified multiple pathways, the parameter is passed to geom_mark_hull()
strType	"normal" or "ms" for multiscale implementation
delZeroDegree	delete zero degree nodes
otherVar	other variables to be included in the inference
otherVarName	the names of other variables
onlyDf	return only data.frame used for inference
disc	discretize the expressoin data
tr	Specify data.frame if one needs to discretize as the same parametersas the other dataset
remainCont	Specify characters when perform discretization, if some columns are to be remain continuous
sp	query to graphite::pathways(), default to "hsapiens"
compareRef	whether compare to the reference network
compareRefType	"intersection" or "difference"
pathDb	query to graphite::pathways(), default to "reactome"
dep	the tibble storing dependency score from library depmap
depMeta	depmap::depmap_metadata(), needed for showLineage
sizeDep	whether to reflect DepMap score to the node size
showDepHist	whether to show depmap histogram
cellLineName	the cell line name to be included
showLineage	show the dependency score across the lineage
orgDb	perform clusterProfiler::setReadable based on this organism database
shadowText	whether to use shadow text for the better readability default: TRUE
bgColor	color for text background when shadowText is TRUE
textColor	color for text when shadowText is TRUE
strengthPlot	append the barplot depicting edges with high strength
nStrength	specify how many edges are included in the strength plot
strThresh	the threshold for strength
hub	visualize the genes with top-n hub scores
seed	A random seed to make the analysis reproducible, default is 1.

Value

ggplot2 object

Examples

data("exampleEaRes");data("exampleGeneExp")
res <- bngeneplot(results = exampleEaRes, exp = exampleGeneExp, pathNum = 1,
                  R = 10, convertSymbol = TRUE, expRow = "ENSEMBL")

noriakis/CBNplotTest documentation built on Nov. 18, 2022, 8:05 a.m.