bioconductor v3.9.0 Enrichplot

The 'enrichplot' package implements several visualization methods for interpreting functional enrichment results obtained from ORA or GSEA analysis.

Link to this section Summary

Functions

barplotenrichResult()

barplot

cnetplot()

cnetplot

color_palette()

color_palette

dotplot()

dotplot

emapplot()

emapplot

fortifyenrichResult()

fortify

ggtable()

ggtable

goplot()

goplot

gsInfo()

gsInfo

gseaplot()

gseaplot

gseaplot2()

gseaplot2

gsearank()

gsearank

heatplot()

heatplot

list2graph()

convert gene IDs to igraph object

pmcplot()

pmcplot

reexports()

Objects exported from other packages

ridgeplot()

ridgeplot

upsetplot_methods()

upsetplot method

Link to this section Functions

barplotenrichResult()

barplot

Description

barplot of enrichResult

Usage

list(list("barplot"), list("enrichResult"))(height, x = "Count", color = "p.adjust",
  showCategory = 8, font.size = 12, title = "", ...)

Arguments

Argument	Description
`height`	enrichResult object
`x`	one of 'Count' and 'GeneRatio'
`color`	one of 'pvalue', 'p.adjust', 'qvalue'
`showCategory`	number of categories to show
`font.size`	font size
`title`	plot title
`...`	other parameter, ignored

Value

ggplot object

Examples

library(DOSE)
data(geneList)
de <- names(geneList)[1:100]
x <- enrichDO(de)
barplot(x)

cnetplot()

cnetplot

Description

Gene-Concept Network

Usage

cnetplot(x, showCategory = 5, foldChange = NULL, layout = "kk", ...)
list(list("cnetplot"), list("enrichResult"))(x, showCategory = 5,
  foldChange = NULL, layout = "kk", ...)
list(list("cnetplot"), list("gseaResult"))(x, showCategory = 5, foldChange = NULL,
  layout = "kk", ...)
cnetplot.enrichResult(x, showCategory = 5, foldChange = NULL,
  layout = "kk", colorEdge = FALSE, circular = FALSE,
  node_label = TRUE, ...)

Arguments

Argument	Description
`x`	enrichment result
`showCategory`	number of enriched terms to display
`foldChange`	fold Change
`layout`	layout of the network
`...`	additional parameters
`colorEdge`	whether coloring edge by enriched terms
`circular`	whether using circular layout
`node_label`	whether display node label

Details

plot linkages of genes and enriched concepts (e.g. GO categories, KEGG pathways)

Value

ggplot object

Author

Guangchuang Yu

Examples

library(DOSE)
data(geneList)
de <- names(geneList)[1:100]
x <- enrichDO(de)
cnetplot(x)

color_palette()

color_palette

Description

create color palette for continuous data

Usage

color_palette(colors)

Arguments

Argument	Description
`colors`	colors of length >=2

Value

color vector

Author

guangchuang yu

Examples

color_palette(c("red", "yellow", "green"))

dotplot()

dotplot

Description

dotplot for enrichment result

Usage

dotplot(object, ...)
list(list("dotplot"), list("enrichResult"))(object, x = "GeneRatio",
  color = "p.adjust", showCategory = 10, size = NULL, split = NULL,
  font.size = 12, title = "", ...)
list(list("dotplot"), list("gseaResult"))(object, x = "GeneRatio",
  color = "p.adjust", showCategory = 10, size = NULL, split = NULL,
  font.size = 12, title = "", ...)

Arguments

Argument	Description
`object`	input object
`...`	additional parameters
`x`	variable for x-axis, one of 'GeneRatio' or 'Count'
`color`	variable that used to color enriched terms, e.g. pvalue, p.adjust or qvalue
`showCategory`	number of enriched terms to display
`size`	variable that used to scale the sizes of categories
`split`	separate result by 'category' variable
`font.size`	font size
`title`	plot title

Value

plot

Author

guangchuang yu

Examples

library(DOSE)
data(geneList)
de <- names(geneList)[1:100]
x <- enrichDO(de)
dotplot(x)

emapplot()

emapplot

Description

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

Usage

emapplot(x, showCategory = 30, color = "p.adjust", layout = "kk",
  ...)
list(list("emapplot"), list("enrichResult"))(x, showCategory = 30,
  color = "p.adjust", layout = "kk", ...)
list(list("emapplot"), list("gseaResult"))(x, showCategory = 30,
  color = "p.adjust", layout = "kk", ...)
emapplot.enrichResult(x, showCategory = 30, color = "p.adjust",
  layout = "kk", ...)

Arguments

Argument	Description
`x`	enrichment result.
`showCategory`	number of enriched terms to display
`color`	variable that used to color enriched terms, e.g. pvalue, p.adjust or qvalue
`layout`	layout of the map
`...`	additional parameters

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.

Value

ggplot object

Author

Guangchuang Yu

Examples

library(DOSE)
data(geneList)
de <- names(geneList)[1:100]
x <- enrichDO(de)
emapplot(x)

fortifyenrichResult()

fortify

Description

convert enrichResult object for ggplot2

Usage

list(list("fortify"), list("enrichResult"))(model, data, showCategory = 5,
  by = "Count", order = FALSE, drop = FALSE, split = NULL, ...)

Arguments

Argument	Description
`model`	enrichResult object
`data`	not use here
`showCategory`	Category numbers to show
`by`	one of Count and GeneRatio
`order`	logical
`drop`	logical
`split`	separate result by 'split' variable
`...`	additional parameter

Value

data.frame

ggtable()

ggtable

Description

plot table

Usage

ggtable(d, p = NULL)

Arguments

Argument	Description
`d`	data frame
`p`	ggplot object to extract color to color rownames(d), optional

Value

ggplot object

Author

guangchuang yu

goplot()

goplot

Description

plot induced GO DAG of significant terms

Usage

goplot(x, showCategory = 10, color = "p.adjust", layout = "sugiyama",
  geom = "text", ...)
list(list("goplot"), list("enrichResult"))(x, showCategory = 10,
  color = "p.adjust", layout = "sugiyama", geom = "text", ...)
list(list("goplot"), list("gseaResult"))(x, showCategory = 10, color = "p.adjust",
  layout = "sugiyama", geom = "text", ...)
goplot.enrichResult(x, showCategory = 10, color = "p.adjust",
  layout = "sugiyama", geom = "text", ...)

Arguments

Argument	Description
`x`	enrichment result.
`showCategory`	number of enriched terms to display
`color`	variable that used to color enriched terms, e.g. pvalue, p.adjust or qvalue
`layout`	layout of the map
`geom`	label geom, one of 'label' or 'text'
`...`	additional parameter

Value

ggplot object

Author

guangchuang yu

gsInfo()

gsInfo

Description

extract gsea result of selected geneSet

Usage

gsInfo(object, geneSetID)

Arguments

Argument	Description
`object`	gseaResult object
`geneSetID`	gene set ID

Value

data.frame

Author

Guangchuang Yu

gseaplot()

gseaplot

Description

visualize analyzing result of GSEA

Usage

gseaplot(x, geneSetID, by = "all", title = "", ...)
list(list("gseaplot"), list("gseaResult"))(x, geneSetID, by = "all", title = "",
  color = "black", color.line = "green", color.vline = "#FA5860",
  ...)
gseaplot.gseaResult(x, geneSetID, by = "all", title = "",
  color = "black", color.line = "green", color.vline = "#FA5860",
  ...)

Arguments

Argument	Description
`x`	object of gsea result
`geneSetID`	geneSet ID
`by`	one of "runningScore" or "position"
`title`	plot title
`...`	additional parameters
`color`	color of line segments
`color.line`	color of running enrichment score line
`color.vline`	color of vertical line which indicating the maximum/minimal running enrichment score

Details

plotting function for gseaResult

Value

ggplot2 object

Author

Guangchuang Yu

Examples

library(DOSE)
data(geneList)
x <- gseDO(geneList)
gseaplot(x, geneSetID=1)

gseaplot2()

gseaplot2

Description

GSEA plot that mimic the plot generated by broad institute's GSEA software

Usage

gseaplot2(x, geneSetID, title = "", color = "green", base_size = 11,
  rel_heights = c(1.5, 0.5, 1), subplots = 1:3, pvalue_table = FALSE,
  ES_geom = "line")

Arguments

Argument	Description
`x`	gseaResult object
`geneSetID`	gene set ID
`title`	plot title
`color`	color of running enrichment score line
`base_size`	base font size
`rel_heights`	relative heights of subplots
`subplots`	which subplots to be displayed
`pvalue_table`	whether add pvalue table
`ES_geom`	geom for plotting running enrichment score, one of 'line' or 'dot'

Value

plot

Author

Guangchuang Yu

gsearank()

gsearank

Description

plot ranked list of genes with running enrichment score as bar height

Usage

gsearank(x, geneSetID, title = "")

Arguments

Argument	Description
`x`	gseaResult object
`geneSetID`	gene set ID
`title`	plot title

Value

ggplot object

Author

Guangchuang Yu

heatplot()

heatplot

Description

heatmap like plot for functional classification

Usage

heatplot(x, showCategory = 30, foldChange = NULL)
list(list("heatplot"), list("enrichResult"))(x, showCategory = 30,
  foldChange = NULL)
list(list("heatplot"), list("gseaResult"))(x, showCategory = 30,
  foldChange = NULL)
heatplot.enrichResult(x, showCategory = 30, foldChange = NULL)

Arguments

Argument	Description
`x`	enrichment result.
`showCategory`	number of enriched terms to display
`foldChange`	fold Change

Value

ggplot object

Author

guangchuang yu

Guangchuang Yu

Examples

library(DOSE)
data(geneList)
de <- names(geneList)[1:100]
x <- enrichDO(de)
heatplot(x)

list2graph()

convert gene IDs to igraph object

Description

convert a list of gene IDs to igraph object.

Usage

list2graph(inputList)

Arguments

Argument	Description
`inputList`	a list of gene IDs

Value

a igraph object.

Author

Guangchuang Yu

pmcplot()

pmcplot

Description

PubMed Central Trend plot

Usage

pmcplot(query, period, proportion = TRUE)

Arguments

Argument	Description
`query`	query terms
`period`	period of query in the unit of year
`proportion`	If TRUE, use query_hits/all_hits, otherwise use query_hits

Value

ggplot object

Author

guangchuang yu

reexports()

Objects exported from other packages

Description

These objects are imported from other packages. Follow the links below to see their documentation.

list(" ", " ", list(list("cowplot"), list(list(list("plot_grid")))), " ", " ", " ", list(list("ggplot2"), list(list(list("ggtitle")))), " ")

ridgeplot()

ridgeplot

Description

ridgeline plot for GSEA result

Usage

ridgeplot(x, showCategory = 30, fill = "p.adjust",
  core_enrichment = TRUE)
list(list("ridgeplot"), list("gseaResult"))(x, showCategory = 30,
  fill = "p.adjust", core_enrichment = TRUE)
ridgeplot.gseaResult(x, showCategory = 30, fill = "p.adjust",
  core_enrichment = TRUE)

Arguments

Argument	Description
`x`	gseaResult object
`showCategory`	number of categories for plotting
`fill`	one of "pvalue", "p.adjust", "qvalue"
`core_enrichment`	whether only using core_enriched genes

Value

ggplot object

Author

Guangchuang Yu

Examples

library(DOSE)
data(geneList)
x <- gseDO(geneList)
ridgeplot(x)

upsetplot_methods()

upsetplot method

Description

upsetplot method generics

Usage

upsetplot(x, ...)
list(list("upsetplot"), list("enrichResult"))(x, n = 10, ...)

Arguments

Argument	Description
`x`	object
`...`	additional parameters
`n`	number of categories to be plotted

Value

plot

Author

Guangchuang Yu

Examples

require(DOSE)
data(geneList)
de=names(geneList)[1:100]
x <- enrichDO(de)
upsetplot(x, 8)