limma (version 3.22.7)

venn: Venn Diagrams

Description

Compute Classification Counts and Make Venn Diagram.

Usage

vennCounts(x, include="both")
vennDiagram(object, include="both", names=NULL, mar=rep(1,4), cex=c(1.5,1,0.7), lwd=1, circle.col=NULL, counts.col=NULL, show.include=NULL, ...)

Arguments

x

numeric matrix of 0's and 1's indicating significance of a test. Usually created by decideTests.

object

either a TestResults matrix from decideTests or a VennCounts object produced by vennCounts.

include

character vector specifying whether all differentially expressed genes should be counted, or whether the counts should be restricted to genes changing in a certain direction. Choices are "both" for all differentially expressed genes, "up" for up-regulated genes only or "down" for down-regulated genes only. If include=c("up","down") then both the up and down counts will be shown. This argument is ignored if object if object is already a vennCounts object.

names

character vector giving names for the sets or contrasts

mar

numeric vector of length 4 specifying the width of the margins around the plot. This argument is passed to par.

cex

numerical vector of length 3 giving scaling factors for large, medium and small text on the plot.

lwd

numerical value giving the amount by which the circles should be scaled on the plot. See par.

circle.col

vector of colors for the circles. See par for possible values.

counts.col

vector of colors for the counts. Of same length as include. See par for possible values.

show.include

logical value whether the value of include should be printed on the plot. Defaults to FALSE if include is a single value and TRUE otherwise

...

any other arguments are passed to plot

Value

vennCounts produces a VennCounts object, which is a numeric matrix with last column "Counts" giving counts for each possible vector outcome. vennDiagram causes a plot to be produced on the current graphical device.

Details

vennDiagram can plot up to five sets. vennCounts can collate intersection counts for any number of sets.

See Also

An overview of linear model functions in limma is given by 06.LinearModels.

Examples

Y <- matrix(rnorm(100*6),100,6)
Y[1:10,3:4] <- Y[1:10,3:4]+3
Y[1:20,5:6] <- Y[1:20,5:6]+3
design <- cbind(1,c(0,0,1,1,0,0),c(0,0,0,0,1,1))
fit <- eBayes(lmFit(Y,design))
results <- decideTests(fit)
a <- vennCounts(results)
print(a)
mfrow.old <- par()$mfrow
par(mfrow=c(1,2))
vennDiagram(a)
vennDiagram(results, 
    include=c("up", "down"),
    counts.col=c("red", "blue"),
    circle.col = c("red", "blue", "green3"))
par(mfrow=mfrow.old)