R Graphical Manual

Browse All

Last data update: 2014.03.03

R: Render complex estimates

plotComplex

R Documentation

Render complex estimates

Description

plotComplex renders complex estimates from the apComplex algorithm using Rgraphviz.

Usage

plotComplex(complexMembers,g,VBs,VPs,geneName=FALSE,baitColor="yellow",preyColor="white",recipLineColor="red",unrecipBBLineColor="blue",unrecipBPLineColor="gray",y="neato")

Arguments

`complexMembers`	A character vector of proteins composing a complex estimate.
`g`	An object of class graph, the full bait-prey graph of AP-MS data used in analysis. complexMembers must be a subset of the node names of g.
`VBs`	A vector of viable baits used in the AP-MS experiment.
`VPs`	A vector of viable prey used in the AP-MS experiment.
`geneName`	A logical indicating whether or not nodes should be plotted with common gene names as labels rather than systematic names.
`baitColor`	Color of bait nodes.
`preyColor`	Color of prey nodes.
`recipLineColor`	Color of edges connecting baits which both detected each other as prey

`unrecipBBLineColor`	Color of edges connecting baits in which one bait finds the other as prey but not vice versa.
`unrecipBPLineColor`	Color of edges extending from baits to proteins that were only used as prey, hence reciprocity is not possible.
`y`	Layout of plot

Details

This is a simple function for plotting complex estimates resulting from the apComplex algorithm. Giving the upcoming changes in Rgraphviz, it will likely be changed substantially.

Value

A plotted graph of the complex estimate subgraph.

Author(s)

Denise Scholtens

References

Scholtens D and Gentleman R. Making sense of high-throughput protein-protein interaction data. Statistical Applications in Genetics and Molecular Biology 3, Article 39 (2004).

Scholtens D, Vidal M, and Gentleman R. Local modeling of global interactome networks. Bioinformatics 21, 3548-3557 (2005).

Examples


data(apEX)
data(apEXG)
PCMG2 <- findComplexes(apEX,sensitivity=.7,specificity=.75)
PCMG2sorted <- sortComplexes(PCMG2,apEX)

VBs <- rownames(apEX)
VPs <- setdiff(colnames(apEX),VBs)

plotComplex(PCMG2sorted$MBME[[1]],g=apEXG,VBs=VBs, VPs=VPs)

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(apComplex)
Loading required package: graph
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Loading required package: RBGL

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/apComplex/plotComplex.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plotComplex
> ### Title: Render complex estimates
> ### Aliases: plotComplex
> ### Keywords: graphs
> 
> ### ** Examples
> 
> 
> data(apEX)
> data(apEXG)
> PCMG2 <- findComplexes(apEX,sensitivity=.7,specificity=.75)
[1] "Finding Initial Maximal BH-complete Subgraphs"
[1] "Combining Complex Estimates"
[1] "calculating initial penalty terms"
[1] "looking at complex combinations"
> PCMG2sorted <- sortComplexes(PCMG2,apEX)
> 
> VBs <- rownames(apEX)
> VPs <- setdiff(colnames(apEX),VBs)
> 
> plotComplex(PCMG2sorted$MBME[[1]],g=apEXG,VBs=VBs, VPs=VPs)
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>