dragon: Run DRAGON in R.

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

Run DRAGON in R.

Description

Description: Estimates a multi-omic Gaussian graphical model for two input layers of paired omic data.

Usage

dragon(
  layer1,
  layer2,
  pval = FALSE,
  gradient = "finite_difference",
  verbose = FALSE
)

Arguments

layer1	: first layer of omics data; rows: samples (order must match layer2), columns: variables
layer2	: second layer of omics data; rows: samples (order must match layer1), columns: variables.
pval	: calculate p-values for network edges. Not yet implemented in R; available in netZooPy.
gradient	: method for estimating parameters of p-value distribution, applies only if p-val == TRUE. default = "finite_difference"; other option = "exact"
verbose	: verbosity level (TRUE/FALSE)

Value

A list of model results. cov : the shrunken covariance matrix

• cov the shrunken covariance matrix

• prec the shrunken precision matrix

• ggm the shrunken Gaussian graphical model; matrix of partial correlations. Self-edges (diagonal elements) are set to zero.

• lambdas Vector of omics-specific tuning parameters (lambda1, lambda2) for layer1 and layer2

• gammas Reparameterized tuning parameters; gamma = 1 - lambda^2

• risk_grid Risk grid, for assessing optimization. Grid boundaries are in terms of gamma.

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