View source: R/NetworkSummary.R
| MEGENA.ModuleSummary | R Documentation | 
Summarizes modules into a table.
MEGENA.ModuleSummary(MEGENA.output,
mod.pvalue = 0.05,hub.pvalue = 0.05,
min.size = 10,max.size = 2500,
annot.table = NULL,symbol.col = NULL,id.col = NULL, 
output.sig = TRUE)
MEGENA.output | 
 A list object. The output from "do.MEGENA()".  | 
mod.pvalue | 
 module compactness significance p-value, to identify modules with significant compactness.  | 
hub.pvalue | 
 node degree significance p-value to identify nodes with significantly high degree.  | 
min.size | 
 minimum module size allowed to finalize in the summary output.  | 
max.size | 
 maximum module size allowed to finalize in the summary output.  | 
annot.table | 
 Default value is NULL, indicating no mapping is provided between node names to gene symbols. If provided, the mapping between node names (id.col) and gene symbol (symbol.col) are used.  | 
id.col | 
 column index of annot.table for node names.  | 
symbol.col | 
 column index of annot.table for gene symbols.  | 
output.sig | 
 Default value is TRUE, indicating significant modules are outputted.  | 
output$module.table contains many important information including module hierarchy, as indicated by
A list object with the components:
modules | 
 Final set of modules obtained upon apply mod.pvalue for significance, min.size and max.size for module size thresholding.  | 
mapped.modules | 
 gene symbol mapped modules when "annot.table" is provided.  | 
module.table | 
 data.frame object for module summary table. Columns include: id, module.size, module.parent, module.hub, module.scale and module.pvalue.  | 
Won-Min Song
## Not run: 
rm(list = ls())
data(Sample_Expression)
ijw <- calculate.correlation(datExpr[1:100,],doPerm = 2)
el <- calculate.PFN(ijw[,1:3])
g <- graph.data.frame(el,directed = FALSE)
MEGENA.output <- do.MEGENA(g = g,remove.unsig = FALSE,doPar = FALSE,n.perm = 10)
output.summary <- MEGENA.ModuleSummary(MEGENA.output,
mod.pvalue = 0.05,hub.pvalue = 0.05,
min.size = 10,max.size = 5000,
annot.table = NULL,id.col = NULL,symbol.col = NULL,
output.sig = TRUE)
## End(Not run)
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