LINKER_runPhase2 {TraRe} | R Documentation |
Run second phase of the linker method where a bipartitive graph is generated from the phase I output. A bipartite graph is a set of graph nodes decomposed into two disjoint sets such that no two graph nodes within the same set are adjacent.
LINKER_runPhase2(modules, Data, NrCores, mode = "VBSR", alpha = 1 - 1e-06)
modules |
Modules obtained from the phase I linker output. |
Data |
Matrix of log-normalized estimated counts of the gene expression data (Nr Genes x Nr samples) |
NrCores |
Nr of computer cores for the parallel parts of the method. Note that the parallelization is NOT initialized in any of the functions. By default, 2. |
mode |
Chosen method(s) to link module eigengenes to regulators. The available options are 'VBSR', 'LASSOmin', 'LASSO1se' and 'LM'. By default, all methods are chosen. |
alpha |
alpha parameter if a LASSO model is chosen. |
igraph object containing the related drivers and targets in the form of a bipartitive graph.
## We are going to proceed in the same manner as in the `liner_runphaseone()` example ## but we start at the end of it, loading the output from the example folder. phaseone <- readRDS(paste0(system.file('extdata',package='TraRe'), '/linker_phaseone_example.rds')) ## We are loading drivers and targets to generate lognorm_est_counts, as we need it ## for the phase 2. drivers <- readRDS(paste0(system.file('extdata',package='TraRe'), '/tfs_linker_example.rds')) targets <- readRDS(paste0(system.file('extdata',package='TraRe'), '/targets_linker_example.rds')) lognorm_est_counts <- as.matrix(rbind(drivers,targets)) ## Now we proceed to call `LINKER_runPhase2()`. ## We first, we need to extract modules from the `LINKER_runPhase1()` output. modules_phaseone<-LINKER_extract_modules(phaseone) ## Now we generate the bipartitive graph from the extracted modules graph <- LINKER_runPhase2(modules=modules_phaseone,Data=lognorm_est_counts, NrCores=1,mode='LM')