treeplot: treeplot

treeplotR Documentation

treeplot

Description

Functional grouping tree diagram for enrichment result of over-representation test or gene set enrichment analysis.

Usage

treeplot(x, ...)

## S4 method for signature 'enrichResult'
treeplot(x, ...)

## S4 method for signature 'gseaResult'
treeplot(x, ...)

## S4 method for signature 'compareClusterResult'
treeplot(x, ...)

treeplot.enrichResult(
  x,
  showCategory = 30,
  color = "p.adjust",
  nWords = 4,
  nCluster = 5,
  cex_category = 1,
  label_format = NULL,
  label_format_cladelab = 30,
  label_format_tiplab = NULL,
  fontsize = 4,
  offset = rel(1),
  offset_tiplab = rel(1),
  hclust_method = "ward.D",
  group_color = NULL,
  extend = 0.3,
  hilight = TRUE,
  hexpand = 0.1,
  align = "both",
  hilight.params = list(hilight = TRUE, align = "both"),
  offset.params = list(bar_tree = rel(1), tiplab = rel(1), extend = 0.3, hexpand = 0.1),
  cluster.params = list(method = "ward.D", n = 5, color = NULL, label_words_n = 4,
    label_format = 30),
  ...
)

treeplot.compareClusterResult(
  x,
  showCategory = 5,
  color = "p.adjust",
  nWords = 4,
  nCluster = 5,
  cex_category = 1,
  split = NULL,
  label_format = NULL,
  label_format_cladelab = 30,
  label_format_tiplab = NULL,
  fontsize = 4,
  offset = rel(1),
  pie = "equal",
  legend_n = 3,
  offset_tiplab = rel(1),
  hclust_method = "ward.D",
  group_color = NULL,
  extend = 0.3,
  hilight = TRUE,
  geneClusterPanel = "heatMap",
  hexpand = 0.1,
  align = "both",
  cluster.params = list(method = "ward.D", n = 5, color = NULL, label_words_n = 4,
    label_format = 30),
  hilight.params = list(hilight = TRUE, align = "both"),
  clusterPanel.params = list(clusterPanel = "heatMap", pie = "equal", legend_n = 3,
    colnames_angle = 0),
  offset.params = list(bar_tree = rel(1), tiplab = rel(1), extend = 0.3, hexpand = 0.1),
  ...
)

Arguments

x

enrichment result.

...

additional parameters

showCategory

number of enriched terms to display

color

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

nWords

The number of words in the cluster tags. Will be removed in the next version.

nCluster

The number of clusters, the default value is 5. Will be removed in the next version.

cex_category

Number indicating the amount by which plotting category. nodes should be scaled relative to the default. Will be removed in the next version.

label_format

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

label_format_cladelab

label_format for group labels, a numeric value sets wrap length, alternatively a custom function to format axis labels. Will be removed in the next version.

label_format_tiplab

label_format for tiplabs, a numeric value sets wrap length, alternatively a custom function to format axis labels. Will be removed in the next version.

fontsize

The size of text, default is 4.

offset

rel object or numeric value, distance bar and tree, offset of bar and text from the clade, default is rel(1), meaning 1 * 1.2 * x_range_of_tree plus distance_between_tree_and_tiplab (1 * (1.2 * x_range_of_tree + distance_between_tree_and_tiplab)). Will be removed in the next version.

offset_tiplab

tiplab offset, rel object or numeric value, the bigger the number, the farther the distance between the node and the branch. The default is rel(1), when geneClusterPanel = "pie", meaning 1 * max_radius_of_the_pies; when geneClusterPanel = "heatMap", meaning 1 * 0.16 * column_number_of_heatMap * x_range_of_tree; when geneClusterPanel = "dotplot", meaning 1 * 0.09 * column_number_of_dotplot * x_range_of_tree. Will be removed in the next version.

hclust_method

Method of hclust. This should be (an unambiguous abbreviation of) one of "ward.D", "ward.D2", "single", "complete", "average" (= UPGMA), "mcquitty" (= WPGMA), "median" (= WPGMC) or "centroid" (= UPGMC). Will be removed in the next version.

group_color

A vector of group colors, the length of the vector should be the same as nCluster. Will be removed in the next version.

extend

Numeric, extend the length of bar, default is 0.3. Will be removed in the next version.

hilight

Logical value, if TRUE(default), add ggtree::geom_hilight() layer. Will be removed in the next version.

hexpand

expand x limits by amount of xrange * hexpand. Will be removed in the next version.

align

control the align direction of the edge of high light rectangular. Options is 'none', 'left', 'right', 'both (default)'. Will be removed in the next version.

hilight.params

list, the parameters to control the attributes of highlight layer. see the hilight.params in the following. hilight.params control the attributes of highlight layer, it can be referred to the following parameters:

  • hilight Logical value, if TRUE(default), add ggtree::geom_hilight() layer.

  • align control the align direction of the edge of high light rectangular. Options is 'none', 'left', 'right', 'both (default)'.

offset.params

list, the parameters to control the offset. see the offset.params in the following. offset.params control the attributes of offset, it can be referred to the following parameters:

  • bar_tree rel object or numeric value, distance bar and tree, offset of bar and text from the clade, default is rel(1), meaning 1 * 1.2 * x_range_of_tree plus distance_between_tree_and_tiplab (1 * (1.2 * x_range_of_tree + distance_between_tree_and_tiplab)).

  • tiplab tiplab offset, rel object or numeric value, the bigger the number, the farther the distance between the node and the branch. The default is rel(1), when clusterPanel = "pie", meaning 1 * max_radius_of_the_pies; when clusterPanel = "heatMap", meaning 1 * 0.16 * column_number_of_heatMap * x_range_of_tree; when clusterPanel = "dotplot", meaning 1 * 0.09 * column_number_of_dotplot * x_range_of_tree.

  • extend Numeric, extend the length of bar, default is 0.3.

  • hexpand expand x limits by amount of xrange * hexpand.

cluster.params

list, the parameters to control the attributes of highlighted nodes and edges. see the cluster.params in the following. cluster.params control the attributes of highlight, it can be referred to the following parameters:

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

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

  • color A vector of group colors, the length of the vector should be the same as nCluster.

  • label_words_n 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.

split

Separate result by 'category' variable.

pie

Used only when geneClusterPanel = "pie", proportion of clusters in the pie chart, one of 'equal' (default) and 'Count'. Will be removed in the next version.

legend_n

Number of circle in legend, the default value is 3. Will be removed in the next version.

geneClusterPanel

one of "heatMap"(default), "dotplot", "pie". Will be removed in the next version.

clusterPanel.params

list, the parameters to control the attributes of cluster panel. see the clusterPanel.params in the following. clusterPanel.params control the attributes of cluster panel, it can be referred to the following parameters:

  • clusterPanel one of "heatMap"(default), "dotplot", "pie".

  • pie pUsed only when ClusterPanel = "pie", proportion of clusters in the pie chart, one of 'equal' (default) and 'Count'.

  • legend_n number of circle in legend.

  • colnames_angle set the angle of colnames.

Details

This function visualizes gene sets as a tree. Gene sets with high similarity tend to cluster together, making it easier for interpretation.

Value

ggplot object

Examples

## Not run: 
    library(clusterProfiler)
    library(org.Hs.eg.db)
    library(enrichplot)
    library(GOSemSim)
    library(ggplot2)
    library(DOSE)
    data(geneList)
    gene <- names(geneList)[abs(geneList) > 2]
    ego <- enrichGO(gene  = gene,
        universe      = names(geneList),
        OrgDb         = org.Hs.eg.db,
        ont           = "BP",
        pAdjustMethod = "BH",
        pvalueCutoff  = 0.01,
        qvalueCutoff  = 0.05,
        readable      = TRUE)
    d <- godata('org.Hs.eg.db', ont="BP")
    ego2 <- pairwise_termsim(ego, method = "Wang", semData = d)
    treeplot(ego2, showCategory = 30)
    # use `hilight = FALSE` to remove ggtree::geom_hilight() layer.
    treeplot(ego2, showCategory = 30, hilight = FALSE)
    # use `offset` parameter to adjust the distance of bar and tree.
    treeplot(ego2, showCategory = 30, hilight = FALSE, offset = rel(1.5))
    # use `offset_tiplab` parameter to adjust the distance of nodes and branches.
    treeplot(ego2, showCategory = 30, hilight = FALSE, offset_tiplab = rel(1.5))
    keep <- rownames(ego2@termsim)[c(1:10, 16:20)]
    keep
    treeplot(ego2, showCategory = keep)
    treeplot(ego2, showCategory = 20, 
        group_color = c("#999999", "#E69F00", "#56B4E9", "#009E73", "#F0E442"))
    # It can also graph compareClusterResult
    data(gcSample)
    xx <- compareCluster(gcSample, fun="enrichKEGG",
                         organism="hsa", pvalueCutoff=0.05)
    xx <- pairwise_termsim(xx)                     
    treeplot(xx)                     
    
    # use `geneClusterPanel` to change the gene cluster panel.
    treeplot(xx, geneClusterPanel = "dotplot")  
    
    treeplot(xx, geneClusterPanel = "pie")  
   
## End(Not run)

YuLab-SMU/enrichplot documentation built on April 15, 2024, 5:18 p.m.