LINKER_run: GRN inference via selected model.

In ubioinformat/TraRe: Transcriptional Rewiring

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(
  TraReObj,
  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,
  Lambda = 5,
  train_size = 0.8,
  onlymods = FALSE,
  only_train = FALSE
)

Arguments

TraReObj	TraReObj containing preprocessed input matrix, linker_preprocessing output.
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 modules and graphs GRN uncovering. By default, 0.05.
Lambda	Lambda variable for Lasso models.
train_size	Fraction of samples selected for the train samples. Default: 0.8.
onlymods	Whether to infer only modules or modules and graphs. Default: FALSE
only_train	whether to use only training samples within LINKER run. Default: FALSE

Value

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

Examples

  ## For this example, we are going to load a example matrix
  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))
  # dim(lognorm_est_counts) # 1149   35                                      

  ## Load gene info, its an array of regulators' names.
  gene_info_p <- paste0(system.file('extdata',package='TraRe'),
                                '/geneinfo_rewiring_example.txt')
  gene_info <- read.delim(gene_info_p,header=TRUE)
  regulators <- gene_info[gene_info[,'regulator'] == 1,'uniq_isos']

  TraReObj <- trare_preprocessing(data_matrix = lognorm_est_counts,
                                     geneinfo = regulators, verbose = FALSE)

  linker_output <- LINKER_run(TraReObj = TraReObj, module_rep = "LINKER",
                           link_mode='VBSR', graph_mode='VBSR',
                           NrModules=10, Nr_bootstraps=1,
                           corrClustNrIter=100)

ubioinformat/TraRe documentation built on March 10, 2024, 1:11 a.m.