compute.PFN.par: Parallelized PFN computation

Description Usage Arguments Details Value Author(s)

View source: R/PFN_Computation.R

Description

PFN construction by parallelized edge screening.

Usage

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compute.PFN.par(sortedEdge,Ng,maxENum,Njob,Ncore,max.skipEdges = NULL,
keep.track = TRUE,initial.links = NULL)

Arguments

sortedEdge

3-column matrix for the input edgelist (e.g. - correlation pair list). Must be sorted by third column, which is usually weight vector.

Ng

integer. number of genes included in sortedEdge.

maxENum

Maximum number of edges to include in final PFN. The theoretical maximal number enforced by Euler's formula is 3(Ng-2).

max.skipEdges

Maximum number of edges to be counted before any valid edge to be included in PFN. This works as a termination condition to avoid exhaustive planarity testing over all edges provided in sortedEdge.

Njob

Number of edges to be passed to each core for parallelized edge screening.

Ncore

Number of cores to utilize.

keep.track

TRUE/FALSE logical. Indicate if the record of PFN construction is saved in temporary file "pfg_el.RData". Default is TRUE.

initial.links

If provided, PFN construction will restart by regarding these initial.links as already-built PFN.

Details

This is parallelized implementation of PFN construction, where it is possible to re-capture PFN construction by providing already computed edgelist into initial.links. Although provivded, this function itself may require careful caution and users are encouraged to use more user-friendly "calculate.PFN()" instead.

Value

A 3-column matrices, where first two columns are integer indices for vertices, and third is the weight vector.

Author(s)

Won-Min Song


MEGENA documentation built on May 29, 2017, 12:33 p.m.