View source: R/linker_runphasetwo.R
LINKER_runPhase2 | R Documentation |
Run second phase of the linker method where a bipartite 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, mode = "VBSR", alpha = 1 - 1e-06, FDR = 0.05)
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) |
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. |
FDR |
The False Discovery Rate correction used for the modules and graphs GRN uncovering. By default, 0.05. |
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 `linker_runphaseone()` example
## but we start at the end of it, loading the output from the example folder.
linkerphase1 <- readRDS(paste0(system.file('extdata',package='TraRe'),
'/linker_phaseone_example.rds'))
## Again, we are going to load the expression matrix dataset
lognorm_est_counts_p <- paste0(system.file('extdata', package='TraRe'),
'/expression_rewiring_example.txt')
lognorm_est_counts <- as.matrix(read.delim(lognorm_est_counts_p,
header=TRUE,row.names=1))
## Now we proceed to call `LINKER_runPhase2()`.
## We first, we need to extract modules from the `LINKER_runPhase1()` output.
modules_phaseone <- TraRe::LINKER_extract_modules(linkerphase1)
## Now we generate the bipartite graph from the extracted modules
# graph <- TraRe::LINKER_runPhase2(modules = linkerphase1, Data = lognorm_est_counts,
# mode='LM')
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