enrichplot (version 1.13.1)

emapplot: emapplot

Description

Enrichment Map for enrichment result of over-representation test or gene set enrichment analysis

Usage

emapplot(x, showCategory = 30, ...)
# S4 method for enrichResult
emapplot(x, showCategory = 30, ...)
# S4 method for gseaResult
emapplot(x, showCategory = 30, ...)
# S4 method for compareClusterResult
emapplot(x, showCategory = 30, ...)
emapplot.enrichResult(
  x,
  showCategory = 30,
  layout = NULL,
  coords = NULL,
  color = "p.adjust",
  min_edge = 0.2,
  cex_label_category = 1,
  cex_category = 1,
  cex_line = 1,
  shadowtext = TRUE,
  label_style = "shadowtext",
  repel = FALSE,
  node_label = "category",
  with_edge = TRUE,
  group_category = FALSE,
  group_legend = FALSE,
  cex_label_group = 1,
  nWords = 4,
  label_format = 30,
  clusterFunction = stats::kmeans,
  nCluster = NULL,
  ...
)
emapplot.compareClusterResult(
  x,
  showCategory = 30,
  layout = NULL,
  coords = NULL,
  split = NULL,
  pie = "equal",
  legend_n = 5,
  cex_category = 1,
  cex_line = 1,
  min_edge = 0.2,
  cex_label_category = 1,
  shadowtext = TRUE,
  with_edge = TRUE,
  group_category = FALSE,
  label_format = 30,
  group_legend = FALSE,
  node_label = "category",
  label_style = "shadowtext",
  repel = FALSE,
  cex_label_group = 1,
  nWords = 4,
  clusterFunction = stats::kmeans,
  nCluster = NULL,
  cex_pie2axis = 1,
  ...
)

Arguments

x

Enrichment result.

showCategory

A number or a vector of terms. If it is a number, the first n terms will be displayed. If it is a vector of terms, the selected terms will be displayed.

...

additional parameters

additional parameters can refer the following parameters.

• force Force of repulsion between overlapping text labels. Defaults to 1.

• nudge_x, nudge_y Horizontal and vertical adjustments to nudge the starting position of each text label.

• direction "both", "x", or "y" <U+2013> direction in which to adjust position of labels.

• ellipse_style style of ellipse, one of "ggforce" an "polygon".

• ellipse_pro numeric indicating confidence value for the ellipses, it can be used only when ellipse_style = "polygon".

• alpha the transparency of ellipse fill.

• type The type of ellipse. The default "t" assumes a multivariate t-distribution, and "norm" assumes a multivariate normal distribution. "euclid" draws a circle with the radius equal to level, representing the euclidean distance from the center.

layout

Layout of the map, e.g. 'star', 'circle', 'gem', 'dh', 'graphopt', 'grid', 'mds', 'randomly', 'fr', 'kk', 'drl' or 'lgl'.

coords

a data.frame with two columns: 'x' for X-axis coordinate and 'y' for Y-axis coordinate.

color

Variable that used to color enriched terms, e.g. 'pvalue', 'p.adjust' or 'qvalue'.

min_edge

The minimum similarity threshold for whether two nodes are connected, should between 0 and 1, default value is 0.2.

cex_label_category

Scale of category node label size.

cex_category

Number indicating the amount by which plotting category nodes should be scaled relative to the default.

cex_line

Scale of line width

shadowtext

a logical value, whether to use shadow font.

label_style

style of group label, one of "shadowtext" and "ggforce".

repel

whether to correct the position of the label. Defaults to FALSE.

node_label

Select which labels to be displayed, one of 'category', 'group', 'all' and 'none'.

with_edge

Logical, if TRUE (the default), draw the edges of the network diagram.

group_category

a logical, if TRUE(the default), group the category.

group_legend

Logical, if TRUE, the grouping legend will be displayed. The default is FALSE.

cex_label_group

Numeric, scale of group labels size, the default value is 1.

nWords

Numeric, the number of words in the cluster tags, the default value is 4.

label_format

a numeric value sets wrap length, alternatively a custom function to format axis labels.

clusterFunction

function of Clustering method, such as stats::kmeans(the default), cluster::clara, cluster::fanny or cluster::pam.

nCluster

Numeric, the number of clusters, the default value is square root of the number of nodes.

split

separate result by 'category' variable

pie

proportion of clusters in the pie chart, one of 'equal' (default) and 'Count'

legend_n

number of circle in legend

cex_pie2axis

It is used to adjust the relative size of the pie chart on the coordinate axis, the default value is 1.

Value

ggplot object

Details

This function visualizes gene sets as a network (i.e. enrichment map). Mutually overlapping gene sets tend to cluster together, making it easier for interpretation. When the similarity between terms meets a certain threshold (default is 0.2, adjusted by parameter `min_edge`), there will be edges between terms. The stronger the similarity, the shorter and thicker the edges. The similarity between terms is obtained by function `pairwise_termsim`, the details of similarity calculation can be found in its documentation: pairwise_termsim.

Examples

# NOT RUN {
    library(DOSE)
    data(geneList)
    de <- names(geneList)[1:100]
    x <- enrichDO(de)
    x2 <- pairwise_termsim(x)
    emapplot(x2)
    # use `layout` to change the layout of map
    emapplot(x2, layout = "star")
    # use `showCategory` to  select the displayed terms. It can be a number of a vector of terms.
    emapplot(x2, showCategory = 10)
    categorys <- c("pre-malignant neoplasm", "intestinal disease",
                   "breast ductal carcinoma", "non-small cell lung carcinoma")
    emapplot(x2, showCategory = categorys)

    # It can also graph compareClusterResult
    data(gcSample)
    library(clusterProfiler)
    library(DOSE)
    library(org.Hs.eg.db)
    data(gcSample)
    xx <- compareCluster(gcSample, fun="enrichGO", OrgDb="org.Hs.eg.db")
    xx2 <- pairwise_termsim(xx)
    emapplot(xx2)
# }