RAM (version 1.2.1.3)

group.venn: Plot Venn Diagram For Two To Five Sets With Item Labels

Description

This function use draw.pairwise.venn to creates a venn diagram for two vectors

Usage

group.venn(vectors, cat.cex=1.5, cex=1, cat.pos=NULL, cat.dist=NULL, label=TRUE, lab.cex=1, lab.col= "black", fill=NULL, file=NULL, ext=NULL, width=8, height=8)

Arguments

vectors

a list of vectors with names. See also RAM.input.formatting.

cat.cex

size of the category names. (see venn.diagram for details).

cex

size of the label of the circles. (see venn.diagram for details).

cat.pos

optional. Location of the category names along the circles. (see venn.diagram for details).

cat.dist

optional. Distance of the category names to the circles. (see venn.diagram for details).

label

logical. If TRUE, will plot the item labels for 2 data sets. For more than 2 datasets or this is set as FALSE, the labels will be numbers for each circle. (see venn.diagram for details).

lab.cex

size of the labels.

lab.col

color of the labels.

fill

optional, color of the circles. (see venn.diagram for details).

file

the file path where the image should be created (see ?RAM.plotting).

ext

filename extension, the type of image to be saved to.

height

the height of the image to be created (in inches).

width

the width of the image to be created (in inches).

Value

group.venn returns a venn diagram for 2 to 5 sets. The user can choose to place item labels for 2 sets of data, however, the label locations can be wrong if the the smaller data set is part of the bigger data set, in this case, set label as FALSE. If the input datasets is more than 2, label will be ignored.

See Also

see venn.diagram

Examples

data(ITS1, meta)
# core OTUs
core <- core.OTU.rank(data=list(ITS1=ITS1), meta=meta, rank="g",
                     meta.factor="Crop", percent=1)
# taxa that core OTUs assigned to
core.Crop1 <- core$ITS1$Crop1$taxa
core.Crop2 <- core$ITS1$Crop2$taxa
# venn plot
vectors <- list(Core_Crop1=core.Crop1, Core_Crop2=core.Crop2)
group.venn(vectors=vectors, label=TRUE, cat.pos=c(330, 150),
           lab.cex=0.7)
## Not run: 
# group.venn(vectors=vectors, label=FALSE, cat.pos=c(330, 150),
#            lab.cex=0.7, cex=3)
# ## End(Not run)