Mergeomics (version 1.0.0)

tool.coalesce.find: Find overlapping clusters

Description

tool.coalesce.find finds overlapped clusters of the given data according to a given overlapping ratio by using tool.overlap and tool.cluster, respectively.

Usage

tool.coalesce.find(data, rmax)

Arguments

data

a list including ITEM identities and their GROUP identities

rmax

maximum overlap not coalesced

Value

CLUSTER

cluster label

NODE

item (node) name

References

Shu L, Zhao Y, Kurt Z, Byars S, Tukiainen T, Kettunen J, Ripatti S, Zhang B, Inouye M, Makinen VP, Yang X. Mergeomics: integration of diverse genomics resources to identify pathogenic perturbations to biological systems. bioRxiv doi: http://dx.doi.org/10.1101/036012

Examples

## Generate item and group labels for 100 items:
## Assume that unique gene number (items) is 60:
members <- 1:100 ## will be updated
modules <- 1:100 ## will be updated
set.seed(1)
for (i in 1:10){
## each time pick 10 items (genes) from 60 unique item labels
members[(i*10-9):(i*10)] <- sample(60,10) 
}
## Assume that unique group labels is 30:
for (i in 1:10){
## each time pick 10 items (genes) from 30 unique group labels
modules[(i*10-9):(i*10)] <- sample(30, 10)
}
rcutoff <- 0.33
ncore <- length(members)
## Default output.
res <- data.frame(CLUSTER=modules, GROUPS=modules, ITEM=members,
stringsAsFactors=FALSE)
## Iterative merging and trimming.
res$COUNT <- 0.0
while(TRUE) {
clust <- tool.coalesce.find(res, rcutoff)    
if(is.null(clust)) break
res <- tool.coalesce.merge(clust, ncore)
}