findLinkedCommunities: Finds Linked communities in the network.

In SystemsGenetics/KINC.R: Provides additional functions for network files created using KINC.

Description

This function uses the linked communities (linkcomm) method for module discover. This approaches finds modules of edges rather than modules of nodes. This allows nodes to be in more than one module better supporting the concept of multifunctional genes. This function generates three output files that it writes to the current working directory.

Usage

findLinkedCommunities(
  net,
  file_prefix = "net",
  module_prefix = "M",
  hcmethod = "ward.D",
  meta = TRUE,
  ignore_inverse = TRUE,
  th = 0.5,
  min.vertices = 10
)

Arguments

net	A network data frame containing the KINC-produced network. The loadNetwork function imports a dataframe in the correct format for this function.
file_prefix	A prefix to add to the beginning of each file name.
module_prefix	A prefix to add to the beginning of the module names. By deafult this is simply the letter 'M'.
hcmethod	A character string naming the hierarchical clustering method to use. Can be one of "ward.D", "single", "complete", "average", "mcquitty", "median", or "centroid". Defaults to "single".
meta	Indicates if modules should be collapsed into meta-modules. If set to TRUE then the linked communities returned are meta modules. Defaults to FALSE.
ignore_inverse	If TRUE inverese edges are removed from the analysis. Defaults to TRUE
th	Specifies the Jaccard similarity score between two modules gene content in order for those modules to be merged. Only applies if meta=TRUE. Lower threshold results in merging being more common.
min.verticies	If a network is disconnected then communities will be found in each subgraph independnet of the others. This argument specifies the number of elements that must exist in a subgraph for communities to be identified.

Value

The linked communities object.

SystemsGenetics/KINC.R documentation built on Nov. 10, 2021, 9:22 p.m.