counts2Venn: Make venn diagrams based on significance classification

In jtlovell/limmaDE2: A pipeline for differential expression analyses in LIMMA

Description

counts2Venn Take a binary significance classification matrix and produce two types of venn diagrams.

Usage

counts2Venn(x, cols, names, colors = "black", type = "both", legx = 0,
  legy = 0, ...)

Arguments

x	A dataframe or matrix containing the binary significance calls (1=significant, 0=NS)
cols	A vector with the column names or numbers to use for plots. Must be of length <=4.
names	A vector of names for each of the venn circles.
colors	A vector of colors to use for each cirlce.
type	The type of diagram to plot. Euler = size of circles is weighted. Both = both types. Any other call gives typical venn diagrams.
legx, legy	Position of legend for plot type "limma" or "both"
...	additional arguments passed to plot.

Details

given a binary significance classification matrix, run functions to produce venn diagrams. if scaled, runs venneuler::venneuler venn diagrams. Otherwise, runs limma::vennCounts/vennDiagram

Value

generates a plot. Does not return anything

Examples

## Not run: 
data(kidney) # from simseq
counts<-kidney$counts
counts<-counts[sample(1:nrow(counts),1000),]
info<-data.frame(rep=kidney$replic,
                 treatment=kidney$treatment)
stats<-pipeLIMMA(counts=counts, info=info,
   formula = " ~ treatment", block=NULL)
sig<-makeBinarySig(x= stats$stats, what="Pvalue")
counts2Venn(x=sig, cols=c(1), names=c("treatment"),
   colors=c("blue"),type="limma", legx=-3.3,legy=-3)

## End(Not run)

jtlovell/limmaDE2 documentation built on May 20, 2019, 3:14 a.m.