monsterMonsterNI: Bipartite Edge Reconstruction from Expression data

In netZoo/netZooR: Unified methods for the inference and analysis of gene regulatory networks

Bipartite Edge Reconstruction from Expression data

Description

This function generates a complete bipartite network from gene expression data and sequence motif data

Usage

monsterMonsterNI(
  motif.data,
  expr.data,
  verbose = FALSE,
  randomize = "none",
  method = "bere",
  ni.coefficient.cutoff = NA,
  alphaw = 1,
  regularization = "none",
  score = "motifincluded",
  cpp = FALSE
)

Arguments

motif.data	A motif dataset, a data.frame, matrix or exprSet containing 3 columns. Each row describes an motif associated with a transcription factor (column 1) a gene (column 2) and a score (column 3) for the motif.
expr.data	An expression dataset, as a genes (rows) by samples (columns)
verbose	logical to indicate printing of output for algorithm progress.
randomize	logical indicating randomization by genes, within genes or none
method	String to indicate algorithm method. Must be one of "bere","pearson","cd","lda", or "wcd". Default is "bere". Important note: the direct regulatory network observed from gene expression is currently implemented as a regular correlation as opposed to the partial correlation described in the paper (please see Schlauch et al., 2017, https://doi.org/10.1186/s12918-017-0517-y)
ni.coefficient.cutoff	numeric to specify a p-value cutoff at the network inference step. Default is NA, indicating inclusion of all coefficients.
alphaw	A weight parameter between 0 and 1 specifying proportion of weight to give to indirect compared to direct evidence. The default is 0.5 to give an equal weight to direct and indirect evidence.
regularization	String parameter indicating one of "none", "L1", "L2"
score	String to indicate whether motif information will be readded upon completion of the algorithm to give to indirect compared to direct evidence. See documentation.
cpp	logical use C++ for maximum speed, set to false if unable to run.

Value

matrix for inferred network between TFs and genes

Examples

data(yeast)
cc.net <- monsterMonsterNI(yeast$motif,yeast$exp.cc)

netZoo/netZooR documentation built on Oct. 16, 2024, 10:23 p.m.