SeqNet (version 1.1.3)

get_sigma.default: Get the covariance matrix

Description

The associations in each module are taken as partial correlations, and the covariance matrix is calculated from these assuming that expression for gene i is the weighted average over each module using 1/sqrt(m_i) as the weight, where m_i is the number of modules containing gene i.

Usage

# S3 method for default
get_sigma(x, ...)

Arguments

x

Either a 'network', 'network_module', or 'matrix' object.

...

Additional arguments.

Value

A covariance matrix.

Examples

# NOT RUN {
# Create a random network with 10 nodes and add random edge weights.
nw <- random_network(10)
nw <- gen_partial_correlations(nw)
# Get covariance matrix for the network or individual modules in the network.
get_sigma(nw)
module <- nw$modules[[1]]
get_sigma(module)
# }