Description Usage Arguments Details Value Author(s) References See Also Examples
kda.start
converts identities (such as module descriptions,
module identifiers, and module nodes) to indices. It prepares graph
topology and module information for wKDA process.
1 | kda.start(job)
|
job |
a data frame including fields for edges and nodes information of the graph (TAIL, HEAD, WEIGHT). It also involves path of input files including module descriptions and module-gene lists. |
kda.start
imports graph and relevant module descriptor input
files, creates an indexed graph structure, and converts identities to
indices from module descriptions and module-gene lists. Hence, it concludes
with a graph structure and a module set involving member gene IDs for
each module.
job |
Updated data frame including indexed graph topology, modules, and nodes information: graph: indexed topology modules: module identities modinfo: module descriptions (indexed) moddata: module data (indexed) module2nodes: lists of node indices for each module modulesizes: module sizes |
Ville-Petteri Makinen
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.
kda.analyze
, kda.finish
,
kda.prepare
, kda.start.edges
,
kda.start.identify
, kda.start.modules
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 31 32 33 34 35 36 37 38 39 40 | job.kda <- list()
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$direction <- 1
job.kda$nperm <- 20 # the default value is 2000, use 20 for unit tests
## kda.start() process takes long time while seeking hubs in the given net
## Here, we used a very small subset of the module list (1st 10 mods
## from the original module file):
moddata <- tool.read(job.kda$modfile)
mod.names <- unique(moddata$MODULE)[1:min(length(unique(moddata$MODULE)),
10)]
moddata <- moddata[which(!is.na(match(moddata$MODULE, mod.names))),]
## save this to a temporary file and set its path as new job.kda$modfile:
tool.save(moddata, "subsetof.supersets.txt")
job.kda$modfile <- "subsetof.supersets.txt"
job.kda <- kda.configure(job.kda)
## Import data for weighted key driver analysis:
job.kda <- kda.start(job.kda)
## Remove the temporary files used for the test:
file.remove("subsetof.supersets.txt")
## remove the results folder
unlink("Results", recursive = TRUE)
|
Writing to file...
Saved 1346 rows in 'subsetof.supersets.txt'.
[1] "subsetof.supersets.txt"
KDA Version:12.7.2015
Parameters:
Search depth: 1
Search direction: 1
Maximum overlap: 0.33
Minimum module size: 20
Minimum degree: automatic
Maximum degree: automatic
Edge factor: 0
Random seed: 1
Importing edges...
TAIL HEAD WEIGHT
Length:140663 Length:140663 Min. :1
Class :character Class :character 1st Qu.:1
Mode :character Mode :character Median :1
Mean :1
3rd Qu.:1
Max. :1
Importing modules...
MODULE NODE
Length:825 Length:825
Class :character Class :character
Mode :character Mode :character
Graph: 7.251717 Mb
[1] TRUE
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