\section{Example phenotypes and interactions}\label{examplePhenotypes}
\subsection{Preliminaries}

<<exampleSingleKnockDownEffects1>>=
library(HD2013SGI)

data("Interactions",package="HD2013SGI")
data("mainEffects",package="HD2013SGI")

dir.create(file.path("result","Figures"),
           recursive=TRUE,showWarnings=FALSE)
@

\subsection{Examples of single knock down phenotypes}\label{exampleSingleKDPhenotypes}

Main effects are first summarized over all four siRNA design pairs and divided by the median deviation to compute a z-score. Then, mean and standard deviation of main effects are calculated over the two replicates of the screen.
<<exampleSingleKnockDownEffects2>>=
MT1 = apply(mainEffects$target,c(1,4,5),mean,na.rm=TRUE)
for (i in seq_len(dim(MT1)[2])) {
  for (j in seq_len(dim(MT1)[3])) {
    MT1[,i,j] = MT1[,i,j] / mad(MT1[,i,j],center=0.0)
  }
}
MT = apply(MT1,c(1,2),mean,na.rm=TRUE)
SD = apply(MT1,c(1,2),sd,na.rm=TRUE)
@

Main effects for five different phenotypes are plotted for two genes.

<<exampleSingleKnockDownEffects3,results=hide>>=
f = c("count", "nuc.0.s.area","nuc.0.m.eccentricity",
      "cell.Bact.m.eccentricity","cell.act.m.majoraxis")
MT2 = MT[,f]
SD2 = SD[,f]
colnames(MT2) = c("count", "nuclear area", "nuclear eccentricity",
                 "cell eccentricity", "actin majoraxis")
ylim=range(c(MT2["SETD8",],MT2["TCF20",]))

g = "SETD8"

pdf(file=file.path("result","Figures","singleKnockDown-SETD8.pdf"),
    width=2.5,height=5)
par(mar=c(12,4,4,1)+0.1,xpd=NA)
bp = barplot(MT2[g,],ylab="z-score",ylim=ylim,las=2,main=g)
abline(h=0.0,xpd=FALSE)
points(bp,MT1[g,f,1])
points(bp,MT1[g,f,2])
dev.off()

g = "TCF20"

pdf(file=file.path("result","Figures","singleKnockDown-TCF20.pdf"),
    width=2.5,height=5)
par(mar=c(12,4,4,1)+0.1,xpd=NA)
bp = barplot(MT2[g,],ylab="z-score",ylim=ylim,las=2,main=g)
abline(h=0.0,xpd=FALSE)
points(bp,MT1[g,f,1])
points(bp,MT1[g,f,2])
dev.off()
@
\begin{center}
\includegraphics[width=0.3\textwidth]{result/Figures/singleKnockDown-SETD8.pdf}
\includegraphics[width=0.3\textwidth]{result/Figures/singleKnockDown-TCF20.pdf}
\end{center}

\subsection{Example of genetic interactions}\label{exampleDoubleKDPhenotypes}

Barplots for example interactions.
<<exampleInteractions1,results=hide>>=
plotExampleInteractions <- function(f,target,query,Interactions,mainEffects) {
  MT = mainEffects$target[target,,,f,]
  dim(MT) = c(prod(dim(MT)[1:2]),dim(MT)[3])
  MQ = mainEffects$query[,query,,f,]
  dim(MQ) = c(prod(dim(MQ)[1:2]),dim(MQ)[3])
  PI = Interactions$piscore
  PI = PI[target,,query,,f,]
  dim(PI) = c(prod(dim(PI)[1:2]),dim(PI)[3])
  EXP = MT+MQ
  DKD = MT+MQ+PI
  X = apply(PI,1,mean)
  names(X) = c("pi11","pi21","pi12","pi22")
  SD = apply(PI,1,sd)
  pv = apply(PI,1,function(x) { t.test(x)$p.value } )
#  I = seq_len(dim(PI)[1])
  par(xpd=NA,mar=c(8,5,4,1))
  bp=barplot(X,las=2, #col=col,
             main=sprintf("t=%s q=%s ph=%s",target,query,f),
             names.arg = rep("",4))
  points(bp,PI[,1])
  points(bp,PI[,2])
  abline(h=0.0,xpd=FALSE)
  r = range(X)
  if (r[1] > 0) { r[1] = 0.0 }
  if (r[2] < 0) { r[2] = 0.0 }
  d = diff(r)
  A = c("+")
  B = c("+")
  C = c("-")
  text(x=bp,y=rep(r[1]-2*d/7,4),c(A,C,A,C))
  text(x=bp,y=rep(r[1]-3*d/7,4),c(C,A,C,A))
  text(x=bp,y=rep(r[1]-4*d/7,4),c(B,B,C,C))
  text(x=bp,y=rep(r[1]-5*d/7,4),c(C,C,B,B))
  text(rep(0.0,4),r[1] - (2:5)*d/7,adj=c(1,0.5),
       sprintf("%s #%d",c(target,target,query,query),c(1,2,1,2)))
}

pdf(file=file.path("result","Figures","interaction-PHF16-SETD8.pdf"),
    height=4,width=3)
plotExampleInteractions(f="cell.act.m.majoraxis",
                        target="PHF16",query="SETD8",
                        Interactions, mainEffects)
dev.off()
pdf(file=file.path("result","Figures","interaction-SIN3A-RUVBL1.pdf"),
    height=4,width=3)
plotExampleInteractions(f="nuc.0.m.eccentricity",
                        target="SIN3A",query="RUVBL1",
                        Interactions, mainEffects)
dev.off()
@

\begin{center}
\includegraphics[width=0.3\textwidth]{result/Figures/interaction-PHF16-SETD8.pdf}
\includegraphics[width=0.3\textwidth]{result/Figures/interaction-SIN3A-RUVBL1.pdf}
\end{center}

\subsection{Overlap of interactions}\label{OverlapOfInteractions}

To show the overlap of interactions called in different phenotypes, Interactions with an adjusted p-value of 0.01 are considered.
<<overlapOfInteractions1>>=
f = c("nuc.0.s.area","nuc.0.m.majoraxis",
      "cell.Bact.m.eccentricity","cell.act.m.majoraxis")
PI = Interactions$padj <= 0.01
PI[is.na(PI)] = FALSE
dim(PI) = c(prod(dim(PI)[1:4]),dim(PI)[5])
row.names(PI) = sprintf("A%d",seq_len(nrow(PI)))
colnames(PI) = Interactions$Anno$phenotype
PI = PI[,f]

I = which(apply(PI,1,any))
Overlap = table(as.data.frame(PI[I,]))
print(Overlap)
save(Overlap, file=file.path("result","Figures","Overlap.rda"))
@

A mosaic plot of the Venn diagram.
<<overlapOfInteractions2,results=hide>>=
pdf(file.path("result","Figures","Mosaicplot.pdf"))
mosaic(Overlap, shade = TRUE)
dev.off()
@
\begin{center}
\includegraphics[width=0.7\textwidth]{result/Figures/Mosaicplot.pdf}
\end{center}

Write lists of identifiers for generating a Venn diagram with a webtool (e.g. http://bioinfogp.cnb.csic.es/tools/venny/index.html).
<<overlapOfInteractions3,eval=FALSE>>=
L = apply(PI[,f],2,function(x) names(which(x)))
for (i in 1:4) {
  writeLines(L[[i]],file.path("result","Figures",
                              sprintf("interactionlist%d.txt",i)))
}
@