bngeneplot | R Documentation |
Plot gene relationship within the specified pathway
bngeneplot(
results,
exp,
expSample = NULL,
algo = "hc",
R = 20,
returnNet = FALSE,
algorithm.args = NULL,
bypassConverting = FALSE,
edgeLink = FALSE,
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,
useSiGN = FALSE
)
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 |
bypassConverting |
bypass the symbol converting If you use custom annotation databases that does not have SYMBOL listed in keys. ID of rownames and those listed in EA result must be same. |
edgeLink |
use geom_edge_link() instead of geom_edge_diagonal() |
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. |
useSiGN |
default to FALSE. For using SiGN-BN in the function in Windows 10/11, 1. Download the SiGN-BN HC+BS binary in WSL (https://sign.hgc.jp/signbn/download.html) 2. Set PATH to executable (sign.1.8.3) |
ggplot2 object
data("exampleEaRes");data("exampleGeneExp")
res <- bngeneplot(results = exampleEaRes, exp = exampleGeneExp, pathNum = 1,
R = 10, convertSymbol = TRUE, expRow = "ENSEMBL")
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