visNetReorder: Function to visualise the multiple graph colorings reorded...

In dnet: Integrative Analysis of Omics Data in Terms of Network, Evolution and Ontology

Description

visNetReorder is supposed to visualise the multiple graph colorings reorded within a sheet-shape rectangle grid

Usage

visNetReorder(
g,
data,
sReorder,
height = 7,
margin = rep(0.1, 4),
border.color = "#EEEEEE",
colormap = c("bwr", "jet", "gbr", "wyr", "br", "yr", "rainbow", "wb"),
ncolors = 40,
zlim = NULL,
colorbar = T,
colorbar.fraction = 0.5,
newpage = T,
glayout = layout.fruchterman.reingold,
mtext.side = 3,
mtext.adj = 0,
mtext.cex = 1,
mtext.font = 2,
mtext.col = "black",
...
)

Arguments

g	an object of class "igraph" or "graphNEL"
data	an input data matrix used to color-code vertices/nodes. One column corresponds to one graph node coloring. The input matrix must have row names, and these names should include all node names of input graph, i.e. V(g)$name, since there is a mapping operation. After mapping, the length of the pattern vector should be the same as the number of nodes of input graph. The way of how to color-code is to map values in the pattern onto the whole colormap (see the next arguments: colormap, ncolors, zlim and colorbar)
sReorder	an object of class "sReorder"
height	a numeric value specifying the height of device
margin	margins as units of length 4 or 1
border.color	the border color of each figure
colormap	short name for the colormap. It can be one of "jet" (jet colormap), "bwr" (blue-white-red colormap), "gbr" (green-black-red colormap), "wyr" (white-yellow-red colormap), "br" (black-red colormap), "yr" (yellow-red colormap), "wb" (white-black colormap), and "rainbow" (rainbow colormap, that is, red-yellow-green-cyan-blue-magenta). Alternatively, any hyphen-separated HTML color names, e.g. "blue-black-yellow", "royalblue-white-sandybrown", "darkgreen-white-darkviolet". A list of standard color names can be found in http://html-color-codes.info/color-names
ncolors	the number of colors specified over the colormap
zlim	the minimum and maximum z/patttern values for which colors should be plotted, defaulting to the range of the finite values of z. Each of the given colors will be used to color an equispaced interval of this range. The midpoints of the intervals cover the range, so that values just outside the range will be plotted
colorbar	logical to indicate whether to append a colorbar. If pattern is null, it always sets to false
colorbar.fraction	the relative fraction of colorbar block against the figure block
newpage	logical to indicate whether to open a new page. By default, it sets to true for opening a new page
glayout	either a function or a numeric matrix configuring how the vertices will be placed on the plot. If layout is a function, this function will be called with the graph as the single parameter to determine the actual coordinates. This function can be one of "layout.auto", "layout.random", "layout.circle", "layout.sphere", "layout.fruchterman.reingold", "layout.kamada.kawai", "layout.spring", "layout.reingold.tilford", "layout.fruchterman.reingold.grid", "layout.lgl", "layout.graphopt", "layout.svd" and "layout.norm". A full explanation of these layouts can be found in http://igraph.org/r/doc/layout_nicely.html
mtext.side	on which side of the mtext plot (1=bottom, 2=left, 3=top, 4=right)
mtext.adj	the adjustment for mtext alignment (0 for left or bottom alignment, 1 for right or top alignment)
mtext.cex	the font size of mtext labels
mtext.font	the font weight of mtext labels
mtext.col	the color of mtext labels
...	additional graphic parameters. See http://igraph.org/r/doc/plot.common.html for the complete list.

Value

invisible

Note

none

See Also

visNet, dNetReorder

Examples

# 1) generate a random graph according to the ER model
g <- erdos.renyi.game(100, 1/100)

# 2) produce the induced subgraph only based on the nodes in query
subg <- dNetInduce(g, V(g), knn=0)

# 3) reorder the module with vertices being color-coded by input data
nnodes <- vcount(subg)
nsamples <- 10
data <- matrix(runif(nnodes*nsamples), nrow=nnodes, ncol=nsamples)
rownames(data) <- V(subg)$name
sReorder <- dNetReorder(g=subg, data, feature="node",
node.normalise="none")

# 4) visualise the module with vertices being color-coded by input data
visNetReorder(g=subg, colormap="bwr", data=data, sReorder)

dnet documentation built on Feb. 20, 2020, 3:01 p.m.