tool.coalesce: Calculate overlaps between groups (main function)

In Mergeomics: Integrative network analysis of omics data

Description

tool.coalesce is utilized to merge and trim either overlapping modules (containing shared genes) or overlapping genes (containing shared markers)

Usage

tool.coalesce(items, groups, rcutoff = 0, ncore = NULL)

Arguments

items	array of item identities
groups	array of group identities for items
rcutoff	maximum overlap not coalesced
ncore	minimum number of items required for trimming

Value

a data list with the following components:

CLUSTER	cluster identities after merging and triming (a subset of group identities)
ITEM	item identities
GROUPS	comma separated overlapping group identities

Author(s)

Ville-Petteri Makinen

References

Shu L, Zhao Y, Kurt Z, Byars SG, Tukiainen T, Kettunen J, Orozco LD, Pellegrini M, Lusis AJ, Ripatti S, Zhang B, Inouye M, Makinen V-P, Yang X. Mergeomics: multidimensional data integration to identify pathogenic perturbations to biological systems. BMC genomics. 2016;17(1):874.

Examples

## read the coexpr module file as an example:
moddata <- tool.read(system.file("extdata",
"modules.mousecoexpr.liver.human.txt", package="Mergeomics"))

## let us find the overlapping ratio between first 10 modules in the file:
## to merge overlapping modules first collect member genes:
mod.names <- unique(moddata$MODULE)[1:min(length(unique(moddata$MODULE)),
10)]
moddata <- moddata[which(!is.na(match(moddata$MODULE, mod.names))),]

## Merge and trim overlapping modules.(max allowed overlap ratio is 0.33)
rmax <- 0.33
moddata$OVERLAP <- moddata$MODULE
moddata <- tool.coalesce(items=moddata$GENE, groups=moddata$MODULE,
rcutoff=rmax)
moddata$MODULE <- moddata$CLUSTER
moddata$GENE <- moddata$ITEM
moddata$OVERLAP <- moddata$GROUPS
moddata <- moddata[,c("MODULE", "GENE", "OVERLAP")]
moddata <- unique(moddata)

Mergeomics documentation built on Nov. 8, 2020, 6:58 p.m.