HiCociety (version 0.1.39)

hic2community: Create module objects from the Hi-C data

Description

It generates a list of graph of significant interactions, module table and module elements.

Usage

hic2community(
  fname,
  chr,
  resol,
  nbprob,
  farthest,
  par.noise = 1,
  network.cluster.method = "louvain",
  n_cores = NULL
)

Value

A list containing three elements: Graphs (an igraph object representing significant chromatin interactions for each chromosome), ModuleSummary (a data.frame containing information about chromatin interaction modules), and ModuleElements (a list of nodes forming significant chromatin interactions within each module).

Arguments

fname

Path to .hic file

chr

chromosome numbers to run.

resol

Resolution of Hi-C data

nbprob

Negative binomial probability. Higher value gives smaller number of stronger interaction.

farthest

The maximum searching distance between two nodes

par.noise

Parameter for noise removal. Default is 1, higher value gives more filtered interactions.

network.cluster.method

Can select between 'louvain' as default and 'label_prop' which means the label propagation method.

n_cores

The number of cores used for parallel computing. If set as NULL, n_cores is automatically set to the number of cores in the computer if it is not exceed 30. If it is more than 30, it is set as 30. Default = NULL

Author

Sora Yoon, PhD

Details

It generates a list of graph of significant interactions, module table and module elements.

Examples

# This example might take a long time to run, so we wrap it in donttest{}
# \donttest{
myhic=system.file('extdata', 'example.hic', package ='HiCocietyExample')
mycom = hic2community(myhic, "19", 5000, 0.975, 2000000,
par.noise=1, 'louvain', n_cores=2)
# }