bnpathplotCustom: bnpathplotCustom

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

bnpathplotCustom

Description

Plot pathway relationship using customized theme

Usage

bnpathplotCustom(
  results,
  exp,
  expSample = NULL,
  algo = "hc",
  R = 20,
  expRow = "ENSEMBL",
  color = "p.adjust",
  cexCategory = 1,
  cl = NULL,
  showDir = FALSE,
  chooseDir = FALSE,
  labelSize = 4,
  layout = "nicely",
  strType = "normal",
  compareRef = FALSE,
  disc = FALSE,
  tr = NULL,
  remainCont = NULL,
  qvalueCutOff = 0.05,
  adjpCutOff = 0.05,
  nCategory = 15,
  cexLine = 1,
  returnNet = FALSE,
  dep = NULL,
  sizeDep = FALSE,
  cellLineName = "5637_URINARY_TRACT",
  fontFamily = "sans",
  otherVar = NULL,
  otherVarName = NULL,
  onlyDf = FALSE,
  algorithm.args = NULL,
  strengthPlot = FALSE,
  nStrength = 10,
  strThresh = NULL,
  hub = NULL,
  glowEdgeNum = NULL,
  nodePal = c("blue", "red"),
  edgePal = c("blue", "red"),
  textCol = "black",
  backCol = "white",
  barTextCol = "black",
  barPal = c("red", "blue"),
  barBackCol = "white",
  scoreType = "bic-g",
  barLegendKeyCol = "white",
  orgDb = org.Hs.eg.db,
  barAxisCol = "black",
  barPanelGridCol = "black",
  seed = 1
)

Arguments

results	the enrichment analysis result
exp	gene expression matrix
expSample	candidate rows 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
expRow	the type of the identifier of rows of expression matrix
color	color of node, default to adjusted p-value
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
labelSize	the size of label of the nodes
layout	ggraph layout, default to "nicely"
strType	"normal" or "ms" for multiscale implementation
compareRef	whether compare to the reference network between pathway
disc	discretize the expressoin data
tr	Specify data.frame if one needs to discretize as the same parameters as the other dataset
remainCont	Specify characters when perform discretization, if some columns are to be remain continuous
qvalueCutOff	the cutoff value for qvalue
adjpCutOff	the cutoff value for adjusted pvalues
nCategory	the number of pathways to be included
cexLine	scaling factor of width of edges
returnNet	whether to return the network
dep	the tibble storing dependency score from library depmap
sizeDep	whether to reflect DepMap score to the node size
cellLineName	the cell line name to be included
fontFamily	font family name to be used for plotting
otherVar	other variables to be included in the inference
otherVarName	the names of other variables
onlyDf	return only data.frame used for inference
algorithm.args	parameters to pass to bnlearn structure learnng function
strengthPlot	append the barplot depicting edges with high strength
nStrength	specify how many edges are included in the strength plot
strThresh	threshold for strength, automatically determined if NULL
hub	change the shape of node according to hub scores (default NULL)
glowEdgeNum	edges with top-n confidence of direction are highlighted
nodePal	vector of coloring of nodes (low, high)
edgePal	vector of coloring of edges (low, high)
textCol	color of texts in network plot
backCol	color of background in network plot
barTextCol	text color in barplot
barPal	bar color
barBackCol	background color in barplot
scoreType	score type to use on inference
barLegendKeyCol	legend key color in barplot
orgDb	perform clusterProfiler::setReadable based on this organism database
barAxisCol	axis color in barplot
barPanelGridCol	panel grid color in barplot
seed	A random seed to make the analysis reproducible, default is 1.

Value

ggplot2 object

Examples

data("exampleEaRes");data("exampleGeneExp")
res <- bnpathplotCustom(results=exampleEaRes, exp=exampleGeneExp,
                        fontFamily="sans", glowEdgeNum=3, hub=3)

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