venn: Plot a Venn diagram

In gplots: Various R Programming Tools for Plotting Data

Plot a Venn diagram

Description

Plot a Venn diagrams for up to 5 sets

Usage

venn(data, universe=NA, small=0.7, showSetLogicLabel=FALSE,
     simplify=FALSE, show.plot=TRUE, intersections=TRUE, names,
     ...)

## S3 method for class 'venn'
plot(x, y, ..., small=0.7, showSetLogicLabel=FALSE,
     simplify=FALSE)

Arguments

data,x	Either a list list containing vectors of names or indices of group intersections, or a data frame containing boolean indicators of group intersectionship (see below)
universe	Subset of valid name/index elements. Values ignore values in codedata not in this list will be ignored. Use NA to use all elements of data (the default).
small	Character scaling of the smallest group counts
showSetLogicLabel	Logical flag indicating whether the internal group label should be displayed
simplify	Logical flag indicating whether unobserved groups should be omitted.
show.plot	Logical flag indicating whether the plot should be displayed. If false, simply returns the group count matrix.
intersections	Logical flag indicating if the returned object should have the attribute "individuals.in.intersections" featuring for every set a list of individuals that are assigned to it.
y	Ignored
...	Optional graphical parameters.
names	Optional vector of group names.

Details

data should be either a named list of vectors containing character string names ("GeneAABBB", "GeneBBBCY", .., "GeneXXZZ") or indexes of group intersections (1, 2, .., N), or a data frame containing indicator variables (TRUE, FALSE, TRUE, ..) for group intersectionship. Group names will be taken from the component list element or column names.

Value

Invisibly returns an object of class "venn", containing:

• A matrix of all possible sets of groups, and the observed count of items belonging to each The fist column contains observed counts, subsequent columns contain 0-1 indicators of group intersectionship.

• If intersections=TRUE, the attribute intersections will be a list of vectors containing the names of the elements belonging to each subset.

Author(s)

Steffen Moeller (email was steffen\[e-mail], may no longer be active), with cleanup and packaging by Gregory R. Warnes [e-mail].

Examples

##
## Example using a list of item names belonging to the
## specified group.
##

## construct some fake gene names..
oneName <- function() paste(sample(LETTERS,5,replace=TRUE),collapse="")
geneNames <- replicate(1000, oneName())

##
GroupA <- sample(geneNames, 400, replace=FALSE)
GroupB <- sample(geneNames, 750, replace=FALSE)
GroupC <- sample(geneNames, 250, replace=FALSE)
GroupD <- sample(geneNames, 300, replace=FALSE)
input  <-list(GroupA,GroupB,GroupC,GroupD)
input

tmp <- venn(input)
attr(tmp, "intersections")

##
## Example using a list of item indexes belonging to the
## specified group.
##
GroupA.i <- which(geneNames %in% GroupA)
GroupB.i <- which(geneNames %in% GroupB)
GroupC.i <- which(geneNames %in% GroupC)
GroupD.i <- which(geneNames %in% GroupD)
input.i  <-list(A=GroupA.i,B=GroupB.i,C=GroupC.i,D=GroupD.i)
input.i

venn(input.i)

##
## Example using a data frame of indicator ('f'lag) columns
##
GroupA.f <- geneNames %in% GroupA
GroupB.f <- geneNames %in% GroupB
GroupC.f <- geneNames %in% GroupC
GroupD.f <- geneNames %in% GroupD
input.df <- data.frame(A=GroupA.f,B=GroupB.f,C=GroupC.f,D=GroupD.f)
head(input.df)
venn(input.df)

## smaller set to create empty groupings
small <- input.df[1:20,]

venn(small, simplify=FALSE) # with empty groupings
venn(small, simplify=TRUE)  # without empty groupings

## Capture group counts, but don't plot
tmp <- venn(input, show.plot=FALSE)
tmp

## Show internal binary group labels
venn(input, showSetLogicLabel=TRUE)

## Limit  universe
tmp <- venn(input, universe=geneNames[1:100])
tmp

##
## Example to determine which elements are in A and B but not in
## C and D using the 'intersections' attribute.
##
tmp <- venn(input, intersection=TRUE)
isect <- attr(tmp, "intersection")

# Look at all of the subsets
str(isect)

# Extract and combine the subsets of interest..
AandB <- unique(c(isect$A, isect$B, isect$'A:B'))

# and look at the results
str(AandB)

##
## The full set of elements of each intersection is provided in the
## "interesections" attribute.
##
a<-venn(list(1:5,3:8), show.plot=FALSE)
intersections<-attr(a,"intersections")
print(intersections)
# $A
# [1] "1" "2"
#
# $B
# [1] "6" "7" "8"
#
# $`A:B`
# [1] "3" "4" "5"

gplots documentation built on April 25, 2022, 9:06 a.m.