Extract node render information from a pePathway-class object

Description

Extract node render information from a pePathway-class object

Usage

peNodeRenderInfo(x, y = "Pert", input.shape = "box",
  default.shape = "ellipse", pos.col = "red", neg.col = "blue",
  zero.col = "white")

Arguments

Value

a named list as expected by nodeRenderInfo

Author(s)

Calin Voichita and Sorin Draghici

See Also

nodeRenderInfo,par

Examples

# load experiment
load(system.file("extdata/E-GEOD-21942.topTable.RData", package = "ROntoTools"))
fc <- top$logFC[top$adj.P.Val <= .01]
names(fc) <- top$entrez[top$adj.P.Val <= .01]
ref <- top$entrez

# load the set of pathways
kpg <- keggPathwayGraphs("hsa")
kpg <- setEdgeWeights(kpg)
kpg <- setNodeWeights(kpg, defaultWeight = 1)

# perform the pathway analysis
peRes <- pe(fc, graphs = kpg, ref = ref, nboot = 100, verbose = TRUE)

p <- peRes@pathways[[50]]
g <- layoutGraph(p@map, layoutType = "dot")
graphRenderInfo(g) <- list(fixedsize = FALSE)
edgeRenderInfo(g) <- peEdgeRenderInfo(p)
nodeRenderInfo(g) <- peNodeRenderInfo(p)
# notice the different type of nodes in the graph (box/circle)
# the color of each node represents the perturbation (red = positive, blue = negative)
# the shade represents the stregth of the perturbation 
renderGraph(g)

nodeRenderInfo(g) <- peNodeRenderInfo(p, "Acc")
# now, the color of each node represents the accumulation (red = positive, blue = negative)
# notice that square nodes with no parents have no accumulation
renderGraph(g)

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)

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> library(ROntoTools)
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: boot
Loading required package: KEGGREST
Loading required package: KEGGgraph

Attaching package: 'KEGGgraph'

The following object is masked from 'package:graphics':

    plot

Loading required package: Rgraphviz
Loading required package: grid
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/ROntoTools/peNodeRenderInfo.Rd_%03d_medium.png", width=480, height=480)
> ### Name: peNodeRenderInfo
> ### Title: Extract node render information from a 'pePathway-class' object
> ### Aliases: peNodeRenderInfo
> 
> ### ** Examples
> 
> 
> # load experiment
> load(system.file("extdata/E-GEOD-21942.topTable.RData", package = "ROntoTools"))
> fc <- top$logFC[top$adj.P.Val <= .01]
> names(fc) <- top$entrez[top$adj.P.Val <= .01]
> ref <- top$entrez
> 
> # load the set of pathways
> kpg <- keggPathwayGraphs("hsa")
Using cached pathway data. Database info:
pathway          KEGG Pathway Database
path             Release 73.0+/01-03, Jan 15
                 Kanehisa Laboratories
                 343,170 entries
Default parameters detected. Using pre-parsed data.
> kpg <- setEdgeWeights(kpg)
> kpg <- setNodeWeights(kpg, defaultWeight = 1)
> 
> # perform the pathway analysis
> peRes <- pe(fc, graphs = kpg, ref = ref, nboot = 100, verbose = TRUE)
Performing pathway analysis...
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> 
> p <- peRes@pathways[[50]]
> g <- layoutGraph(p@map, layoutType = "dot")
> graphRenderInfo(g) <- list(fixedsize = FALSE)
> edgeRenderInfo(g) <- peEdgeRenderInfo(p)
> nodeRenderInfo(g) <- peNodeRenderInfo(p)
> # notice the different type of nodes in the graph (box/circle)
> # the color of each node represents the perturbation (red = positive, blue = negative)
> # the shade represents the stregth of the perturbation 
> renderGraph(g)
> 
> nodeRenderInfo(g) <- peNodeRenderInfo(p, "Acc")
> # now, the color of each node represents the accumulation (red = positive, blue = negative)
> # notice that square nodes with no parents have no accumulation
> renderGraph(g)
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>