R

ggplot2

Arrange multiple plots with ggplot2

frequently used

color gradient with custom points

Code Fragments

 

Sort Factors

c$chromosome <- factor(c$chromosome, levels=c("X", "2L", "2R", "3L", "3R", "4"))

 

Use R-Script from the command line

plot_tr<-function(data,description)
{
  par(mfrow=c(5,2))
  for(i in c("r1","r2","r3","r4","r5","r6","r7","r8","r9","r10"))
  {
    r<-data[data$V1==i,]
    boxplot(r$V2,r$V3,r$V4,r$V5,r$V6,r$V7,r$V8,names=c("b-g20","b-g40","b-g60","b-g80","b-g100","b-g150","b-g200"),main=paste(description,i))
  }
 
}
## COMMAND LINE ARGUMENTS ENTER HERE ##
args<-commandArgs(TRUE)
alen=length(args)
filename=args[alen-1]
description=args[alen]
 
 
#(filename)
#(description)
# filename has to be provided as an argument
d<-read.table(filename)
 
postscript(file=paste(filename,".ps",sep=""),onefile=TRUE,horizontal=FALSE)
plot_tr(d,"base-g60")
dev.off()
#dev.copy2eps(file=paste(filename,".eps"))

Call this script using the command

R --vanilla --args traj-2k-g60-r10 "base-g60"< ../../../../scripts/trajectory_printer.r

Old Manhattan plotter

Create a ROC curve manually

 

Pyramid plot (e.g. Tempo and Mode)

library(plotrix)
 
heatmap<-c("#121DED","#2B1CD6","#441CBF","#5D1CA8","#761C91","#8F1B7A","#A81B63","#C11B4C","#DA1B35","#F31B1E")
 
seq(1,20)
mel<-matrix(seq(1,20),ncol=10,byrow=T)
sim<-matrix(seq(21,40),ncol=10,byrow=T)
rn<-c("INE-1","roo")
 
library(MASS)
 
result <- by(survey, survey$Sex, function(x) {table(x$Smoke, x$Exer)})
 
pyramid.plot(lx=sim, rx=mel,
             labels=rn,
             gap=30, unit="Insertion counts",
             top.labels=c("D.simulans","Family","D. melanogaster"),
             lxcol=heatmap,
             rxcol=heatmap
)

Mantel Haensel plot with log(p-values)

Simple coalescent simulator

Grid

Venn Diagram with Grid

library(VennDiagram)
 
v1<-draw.pairwise.venn(1382, 596, 428,scaled=TRUE,category=c("Dmel","Dsim"),fill = c("blue", "green"),alpha=c(0.5,0.5))
v2<-draw.pairwise.venn(322, 171, 129,scaled=TRUE,category=c("Dmel","Dsim"),fill = c("blue", "green"),alpha=c(0.5,0.5))
v3<-draw.pairwise.venn(213, 87, 53,scaled=TRUE,category=c("Dmel","Dsim"),fill = c("blue", "green"),alpha=c(0.5,0.5))
v4<-draw.pairwise.venn(272, 109, 72,scaled=TRUE,category=c("Dmel","Dsim"),fill = c("blue", "green"),alpha=c(0.5,0.5))
v5<-draw.pairwise.venn(244, 107, 77,scaled=TRUE,category=c("Dmel","Dsim"),fill = c("blue", "green"),alpha=c(0.5,0.5))
v6<-draw.pairwise.venn(331, 122, 96,scaled=TRUE,category=c("Dmel","Dsim"),fill = c("blue", "green"),alpha=c(0.5,0.5))
 
gl<-grid.layout(nrow = 6, ncol = 1)
vp1<-viewport(layout.pos.row=1,layout.pos.col=1)
vp2<-viewport(layout.pos.row=2,layout.pos.col=1)
vp3<-viewport(layout.pos.row=3,layout.pos.col=1)
vp4<-viewport(layout.pos.row=4,layout.pos.col=1)
vp5<-viewport(layout.pos.row=5,layout.pos.col=1)
vp6<-viewport(layout.pos.row=6,layout.pos.col=1)
 
pdf("/Volumes/Volume_4/analysis/Pelement/analysis/2014-11-VennDiagramOverlapping/test.pdf", width = 3, height = 18)
grid.newpage()
pushViewport(viewport(layout=gl))
pushViewport(vp1)
grid.draw(v1)
popViewport()
 
pushViewport(vp2)
grid.draw(v2)
popViewport()
 
pushViewport(vp3)
grid.draw(v3)
popViewport()
 
pushViewport(vp4)
grid.draw(v4)
popViewport()
 
pushViewport(vp5)
grid.draw(v5)
popViewport()
 
pushViewport(vp6)
grid.draw(v6)
popViewport()
dev.off()