LINKER_run {TraRe}R Documentation

GRN inference via selected model.

Description

Gene Regulatory Network inference via model selection. Consists of two phases, LINKER_runPhase1() and LINKER_runPhase2(). Help them for more information.

Usage

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
)

Arguments

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.

Value

List containing the GRN raw results, GRN modules and GRN graphs.

Examples

   ## 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)




[Package TraRe version 1.1.0 Index]