Description Usage Arguments Details Value Author(s) References See Also Examples
kda2cytoscape
generates input files for Cytoscape to visualize the
graph and hubnets after the wKDA process finished. The network
visualization is a streamlined depiction of the module enrichment in hub
neighborhoods.
1 2 | kda2cytoscape(job, node.list = NULL, modules = NULL, ndrivers = 5,
depth = 1)
|
job |
wKDA result data list as returned by |
node.list |
array of node/gene names to be visualized with their neighbor node.
if this is not specified top |
modules |
array of module names to be visualized |
ndrivers |
maximum number of drivers per module |
depth |
depth for neighborhood search in the graph |
kda2cytoscape
first, selects top scoring key drivers for
each module; then, assigns a colormap to modules, processes each module
separately, finds key nodes' neighborhoods within a particular search
depth, and saves the edge and node lists of the modules to the specified
output folder. Besides, it returns this configuration data to the user.
Created file list for Cytoscape are given below:
1 2 3 4 5 6 7 8 9 | kda2cytoscape.top.kds.txt: top key drivers of the modules are
listed in this file. Number of the key drivers can be set by
user with ndrivers parameter.
kda2cytoscape.edges.txt: edge lists of the integrated graph
that includes the subnetworks of all modules.
kda2cytoscape.nodes.txt: node lists of the integrated graph
that includes the subnetworks of all modules.
module.color.mapping.txt: color mapping for the modules,
i.e. one color is assigned to each module.
|
job |
updated data list including the node and edge information of the modules converted to Cytoscape format |
Zeyneb Kurt
Shu L, Zhao Y, Kurt Z, Byars SG, Tukiainen T, Kettunen J, Orozco LD, Pellegrini M, Lusis AJ, Ripatti S, Zhang B, Inouye M, Makinen V-P, Yang X. Mergeomics: multidimensional data integration to identify pathogenic perturbations to biological systems. BMC genomics. 2016;17(1):874.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | ## get the prepared and KDA applied dataset:(see kda.analyze for details)
data(job_kda_analyze)
## set the relevant parameters:
job.kda$label<-"HDLC"
## parent folder for results
job.kda$folder<-"Results"
## Input a network
## columns: TAIL HEAD WEIGHT
job.kda$netfile<-system.file("extdata","network.mouseliver.mouse.txt",
package="Mergeomics")
## Gene sets derived from ModuleMerge, containing two columns, MODULE,
## NODE, delimited by tab
job.kda$modfile<- system.file("extdata","mergedModules.txt",
package="Mergeomics")
## "0" means we do not consider edge weights while 1 is opposite.
job.kda$edgefactor<-0.0
## The searching depth for the KDA
job.kda$depth<-1
## 0 means we do not consider the directions of the regulatory interactions
## while 1 is opposite.
job.kda$direction <- 1
## finish the KDA process
job.kda <- kda.finish(job.kda)
## prepare the cytoscape-ready files:
job.kda <- kda2cytoscape(job.kda)
## remove the results folder
unlink("Results", recursive = TRUE)
|
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