tool.coalesce {Mergeomics}R Documentation

Calculate overlaps between groups (main function)

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)

[Package Mergeomics version 1.14.0 Index]