geneConnector {netboxr} | R Documentation |
This function generates sub-network mapping from a list of candidate genes
geneConnector( geneList, networkGraph, directed = FALSE, pValueAdj = "BH", pValueCutoff = 0.05, communityMethod = "ebc", keepIsolatedNodes = FALSE )
geneList |
character vector containing a list of candidate genes |
networkGraph |
igraph network graph object. This igraph object contains curated network information |
directed |
boolean value indicating whether the input network is directed or undirected (default = FALSE) |
pValueAdj |
string for p-value correction method c("BH", "Bonferroni") as described in the details section (default = "BH") |
pValueCutoff |
numeric value of p-value cutoff for linker nodes (default = 0.05) |
communityMethod |
string for community detection method c("ebc","lec") as described in the details section (default = "ebc") |
keepIsolatedNodes |
A boolean value indicating whether to keep isolated nodes in the netboxr result (default = FALSE) |
P-value correction methods include the Bonferroni correction ("bonferroni") or Benjamini & Hochberg ("BH"). Community detection methods include using edge betweeness score ("ebc") or using leading eigenvector method ("lec)
a list of returned netboxr results
netboxGraph: igraph object of NetBox algorithm identified network nodes and connections
netboxCommunity: igraph object of network community assignment
netboxOutput: data frame of NetBox algorithm identified network nodes and connections
nodeType: data frame of node types ("candidate" or "linker") in the NetBox algorithm indentified network.
moduleMembership: data frame of module (community) membership.
neighborData: data frame of information of nodes directly connected to candidate gene nodes.
Eric Minwei Liu, emliu.research@gmail.com
data(netbox2010) sifNetwork<-netbox2010$network graphReduced <- networkSimplify(sifNetwork,directed = FALSE) geneList<-as.character(netbox2010$geneList) results<-geneConnector(geneList=geneList,networkGraph=graphReduced, pValueAdj='BH',pValueCutoff=0.05, communityMethod='lec',keepIsolatedNodes=FALSE) names(results) plot(results$netboxGraph, layout = layout_with_fr) write.table(results$netboxOutput, file = "network.sif", sep = " ", quote = FALSE, col.names = FALSE, row.names = FALSE ) write.table(results$neighborData, file = "neighborList.txt", sep = " ", quote = FALSE, col.names = TRUE, row.names = FALSE ) write.table(results$moduleMembership, file = "memb.ebc.txt", sep = " ", quote = FALSE, col.names = FALSE, row.names = FALSE ) # write.table(results$nodeType, file = "nodeType.txt", sep = " ", quote = FALSE, col.names = FALSE, row.names = FALSE ) #