MACP (version 0.1.0)

MCL_clustering: MCL clustering

Description

This function applies MCL clustering to further refine the predicted subnetworks produced by ClusterONE.

Usage

MCL_clustering(hc_ppi, predcpx, inflation = 9, csize = 2)

Value

List of refined complexes.

Arguments

hc_ppi

High-confidence interactions data containing id1-id2-weight triplets.

predcpx

A data.frame containing predicted complexes resulted from get_clusters.

inflation

MCL inflation parameter. Defaults to 9.

csize

An integer, the minimum size of the predicted complexes. Defaults to 2.

Author

Matineh Rahmatbakhsh

Details

MCL_clustering

Examples

# open high-confidence network
hc_ppi <-
read.delim(
system.file("extdata/ppi_input_ClusterONE.txt", package = "MACP"),
header = FALSE)
# predict complexes by ClusterONE
predcpx <-
get_clusters(csize = 3, d = 0.3, p = 2,
max_overlap = 0.8,
tpath = file.path(system.file("extdata", package = "MACP")))
# Break down big complexes by MCL
MCL_clusters <- MCL_clustering(hc_ppi, predcpx, inflation = 4, csize = 2)