kda.start {Mergeomics} | R Documentation |
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.
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
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)