LINKER_run {TraRe} | R Documentation |
Gene Regulatory Network inference via model selection. Consists of two phases,
LINKER_runPhase1()
and LINKER_runPhase2()
. Help them for more information.
LINKER_run( lognorm_est_counts, target_filtered_idx, regulator_filtered_idx, nassay = 1, regulator = "regulator", link_mode = c("VBSR", "LASSOmin", "LASSO1se", "LM"), graph_mode = c("VBSR", "LASSOmin", "LASSO1se", "LM"), module_rep = "MEAN", NrModules = 100, corrClustNrIter = 100, Nr_bootstraps = 10, FDR = 0.05, NrCores = 1 )
lognorm_est_counts |
Matrix of log-normalized estimated counts of the gene expression data (Nr Genes x Nr samples) or SummarizedExperiment object. |
target_filtered_idx |
Index array of the target genes on the lognorm_est_counts matrix if SummarizedExperiment object is not provided. |
regulator_filtered_idx |
Index array of the regulatory genes on the lognorm_est_counts matrix if SummarizedExperiment object is not provided. |
nassay |
if SummarizedExperiment object is passed as input to lognorm_est_counts, name of the assay containing the desired matrix. Default: 1 (first item in assay's list). |
regulator |
if SummarizedExperiment object is passed as input to lognorm_est_counts, name of the rowData() variable to build target_filtered_idx and regulator_filtered_idx. This variable must be one for driver genes and zero for target genes. Default: 'regulator' |
link_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. |
graph_mode |
Chosen method(s) to generate the edges in the bipartite graph. The available options are 'VBSR', 'LASSOmin', 'LASSO1se' and 'LM'. By default, all methods are chosen. |
module_rep |
Method selected for use. Default set to MEAN. |
NrModules |
Number of modules that are a priori to be found (note that the final number of modules discovered may differ from this value). By default, 100 modules. |
corrClustNrIter |
output from preparedata(). By default, 100. |
Nr_bootstraps |
Number of bootstrap of Phase I. By default, 10. |
FDR |
The False Discovery Rate correction used for the enrichment analysis. By default, 0.05. |
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. |
List containing the GRN raw results, GRN modules and GRN graphs.
## For this example, we are going to join 60 drivers and ## 200 targets genes from the example folder. 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)) ## We create the index for drivers and targets in the log-normalized gene expression matrix. R<-60 T<-200 regulator_filtered_idx <- seq_len(R) target_filtered_idx <- R+c(seq_len(T)) ## We recommend to use the default values of the function. ## For the sake of time, we will select faster (and worse) ones. linkeroutput <- LINKER_run(lognorm_est_counts,target_filtered_idx=target_filtered_idx, regulator_filtered_idx=regulator_filtered_idx, link_mode='LASSOmin',graph_mode='LM',NrModules=5,Nr_bootstraps=1, NrCores=2,corrClustNrIter=10)