xEnrichRadial: Function to visualise enrichment results using radial-like...

In XGR: Exploring Genomic Relations for Enhanced Interpretation Through Enrichment, Similarity, Network and Annotation Analysis

Description

xEnrichRadial is supposed to visualise enrichment results using radial-like plot. It returns three ggplot2 objects, the first for visualing the network with nodes lablelled by codes, the second for listing code meaning in a table, and the third for the network with nodes colored/sized with enrichment results.

Usage

xEnrichRadial(eTerm, ig = NULL, fixed = T, node.color = c("or",
"adjp", "zscore"), colormap = "grey-orange-darkred", zlim = NULL,
node.size = c("adjp", "or", "zscore"), slim = NULL,
node.size.range = c(0.5, 3.5), edge.color = "skyblue",
edge.color.alpha = 0.5, edge.curve = 0.1, edge.arrow.gap = 0.02,
...)

Arguments

eTerm	an object of class "eTerm" or "ls_eTerm". Alterntively, it can be a data frame having all these columns ('name','adjp','or','zscore'; 'group' optionally). Be aware that multiple ontologies are not supported here
ig	the igraph object. If provided, only those terms within it will be visualised. By default, it is NULL meaning no surch restriction
fixed	logical to indicate whether all terms in ig will be visualised. By default, it is TURE; otherwise only overlapped terms from eTerm will be visualised
node.color	which statistics will be used for node coloring. It can be "or" for the odds ratio, "adjp" for adjusted p value (FDR) and "zscore" for enrichment z-score
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), "rainbow" (rainbow colormap, that is, red-yellow-green-cyan-blue-magenta), and "ggplot2" (emulating ggplot2 default color palette). Alternatively, any hyphen-separated HTML color names, e.g. "lightyellow-orange" (by default), "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
zlim	the minimum and maximum values for which colors should be plotted
node.size	which statistics will be used for node size. It can be "or" for the odds ratio, "adjp" for adjusted p value (FDR) and "zscore" for enrichment z-score
slim	the minimum and maximum values for which sizes should be plotted
node.size.range	the range of actual node size
edge.color	a character specifying which edge attribute defining the the edge colors
edge.color.alpha	the 0-1 value specifying transparency of edge colors
edge.curve	a numeric value specifying the edge curve. 0 for the straight line
edge.arrow.gap	a gap between the arrow and the node
...	additional graphic parameters used in xGGnetwork

Value

a list with 3 components, three ggplot objects (code, table, data) and an igraph object (ig appended with node attributes 'zscore', 'adjp' and 'or')

Note

none

See Also

xEnrichViewer, xOBOcode, xGGnetwork

Examples

## Not run: 
# Load the XGR package and specify the location of built-in data
library(XGR)
RData.location <- "http://galahad.well.ox.ac.uk/bigdata/"

ls_res <- xEnrichRadial(eTerm, ig, fixed=T, node.color="or",
colormap="grey-orange-darkred", zlim=c(0,7), node.size="adjp",
slim=c(0,30), node.size.range=c(1,3))
pdf("xEnrichRadial.pdf", width=6.5, height=6.5)
print(ls_res$data + coord_equal(ratio=1.3))
print(ls_res$code + coord_equal(ratio=1.3))
print(ls_res$table)
dev.off()

# advanced use: customise layout
ig.PhasedTargets <- xRDataLoader('ig.PhasedTargets',
RData.location=RData.location)
ig <- xLayout(ig.PhasedTargets,
layout="gplot.layout.fruchtermanreingold")
ls_res <- xEnrichRadial(df, ig=ig, fixed=F, node.color="or",
node.size="adjp", node.xcoord="xcoord", node.ycoord="ycoord")
pdf("xEnrichRadial.pdf", width=6.5, height=6.5)
print(ls_res$data + coord_equal())
gridExtra::grid.arrange(grobs=c(list(ls_res$code+coord_equal()),ls_res$table),
ncol=2)
dev.off()

## End(Not run)

XGR documentation built on June 18, 2019, 3:01 p.m.