#calculates index score
ERB=function(D1,D2,MIC,DIA,MICBrkptL,MICBrkptU,VM1,M1,m1,VM2,M2,m2,withinOneVector){
tempMIC=MIC
tempDIA=DIA
temp=max(VM1,M1,m1,VM2,M2,m2)
VM1=temp/VM1; M1=temp/M1; m1=temp/m1
VM2=temp/VM2; M2=temp/M2; m2=temp/m2
### outside one intermediate range
II=0; SS=0; VM=0; RR=0; M=0; m=0
MIC=tempMIC[withinOneVector==0]
DIA=tempDIA[withinOneVector==0]
n=length(MIC)
for (i in 1:n){
#SS
if(MIC[i]<=MICBrkptL & DIA[i]>=D2)SS=SS+1
#intermediate
else if ((MIC[i]>MICBrkptL & MIC[i]<MICBrkptU) & (DIA[i]>D1 & DIA[i]<D2)) II=II+1
#resistant
else if(MIC[i]>=MICBrkptU & DIA[i]<=D1)RR=RR+1
#I MIC S DIA
else if((MIC[i]>MICBrkptL & MIC[i]<MICBrkptU) & DIA[i]>=D2)m=m+1
#R MIC S DIA
else if(MIC[i]>=MICBrkptU & DIA[i]>=D2)VM=VM+1
#S MIC I DIA
else if(MIC[i]<=MICBrkptL & (DIA[i]>D1 & DIA[i]<D2))m=m+1
#R MIC I DIA
else if(MIC[i]>=MICBrkptU & (DIA[i]>D1 & DIA[i]<D2))m=m+1
#S MIC R DIA
else if(MIC[i]<=MICBrkptL & DIA[i]<=D1)M=M+1
#I MIC R DIA
else if((MIC[i]>MICBrkptL & MIC[i]<MICBrkptU) & DIA[i]<=D1)m=m+1
}
index1=VM2*VM/n+M2*M/n+m2*m/n
CorrectPerc1=sum(SS,RR,II)/n*100
VMPerc1=VM/n*100
MPerc1=M/n*100
mPerc1=m/n*100
SS1=SS; RR1=RR; II1=II
VMCount1=VM; MCount1=M; mCount1=m
###inside one intermediate range
II=0; SS=0; VM=0; RR=0; M=0; m=0
if(sum(withinOneVector)>0){
MIC=tempMIC[withinOneVector==1]
DIA=tempDIA[withinOneVector==1]
n=length(MIC)
for (i in 1:n){
#SS
if(MIC[i]<=MICBrkptL & DIA[i]>=D2)SS=SS+1
#intermediate
else if ((MIC[i]>MICBrkptL & MIC[i]<MICBrkptU) & (DIA[i]>D1 & DIA[i]<D2)) II=II+1
#resistant
else if(MIC[i]>=MICBrkptU & DIA[i]<=D1)RR=RR+1
#I MIC S DIA
else if((MIC[i]>MICBrkptL & MIC[i]<MICBrkptU) & DIA[i]>=D2)m=m+1
#R MIC S DIA
else if(MIC[i]>=MICBrkptU & DIA[i]>=D2)VM=VM+1
#S MIC I DIA
else if(MIC[i]<=MICBrkptL & (DIA[i]>D1 & DIA[i]<D2))m=m+1
#R MIC I DIA
else if(MIC[i]>=MICBrkptU & (DIA[i]>D1 & DIA[i]<D2))m=m+1
#S MIC R DIA
else if(MIC[i]<=MICBrkptL & DIA[i]<=D1)M=M+1
#I MIC R DIA
else if((MIC[i]>MICBrkptL & MIC[i]<MICBrkptU) & DIA[i]<=D1)m=m+1
}
index2=VM1*VM/n+M1*M/n+m1*m/n
CorrectPerc2=sum(SS,RR,II)/n*100
VMPerc2=VM/n*100
MPerc2=M/n*100
mPerc2=m/n*100
SS2=SS; RR2=RR; II2=II
VMCount2=VM; MCount2=M; mCount2=m
}else{
index2=0
CorrectPerc2=100
VMPerc2=0
MPerc2=0
mPerc2=0
SS2=0; RR2=0; II2=0
VMCount2=0; MCount2=0; mCount2=0
}
return(list(idx=index1+index2,CorPerc1=CorrectPerc1,VMPerc1=VMPerc1,MPerc1=MPerc1,mPerc1=mPerc1,CorrectCount1=sum(SS1,RR1,II1),
VMCount1=VMCount1,MCount1=MCount1,mCount1=mCount1,
CorPerc2=CorrectPerc2,VMPerc2=VMPerc2,MPerc2=MPerc2,mPerc2=mPerc2,
CorrectCount2=sum(SS2,RR2,II2),VMCount2=VMCount2,MCount2=MCount2,mCount2=mCount2))
}
#finds optimum DIA given breakpoints M1 and M2 error rate bounded method
findBrkptsERB=function(MIC,DIA,VM1=10,M1=10,m1=40,VM2=2,M2=2,m2=5,
MICBrkptL,MICBrkptU,minWidth=4,maxWidth=20){
# VM1=10;M1=10;m1=40;VM2=2;M2=2;m2=5;minWidth=4;maxWidth=20
#find optimal
parms=findBrkptsERBC(MIC,DIA,VM1,M1,m1,VM2,M2,m2,MICBrkptL,MICBrkptU,minWidth,maxWidth)
D1=parms$D1; D2=parms$D2
#find information for plotting and display information
N=length(MIC)
withinOne=rep(0,length(MIC))
withinOne[which(MIC>=MICBrkptL & MIC<=MICBrkptU)]=1
numwithinOne=sum(withinOne)
cat('Optimal DIA Breakpoints for ERB:',D1,D2,'\n')
cat('Number of Isolates: ',N,'\n')
cat('Number Observed Outside One of Intermediate Range: ',N-numwithinOne,'\n')
cat('Number Observed Within One of Intermediate Range: ',numwithinOne,'\n')
temp=matrix(nrow=2,ncol=5)
parms=ERB(D1,D2,MIC,DIA,MICBrkptL,MICBrkptU,VM1,M1,m1,VM2,M2,m2,withinOne)
cat('Index Score = ',parms$idx,'\n \n')
cat('Count (%) \n')
temp[1,2:5]=c(paste(parms$CorrectCount2,' (',round(parms$CorPerc2,digits=2),')',sep=''),
paste(parms$VMCount2,' (',round(parms$VMPerc2,digits=2),')',sep=''),
paste(parms$MCount2,' (',round(parms$MPerc2,digits=2),')',sep=''),
paste(parms$mCount2,' (',round(parms$mPerc2,digits=2),')',sep=''))
temp[2,2:5]=c(paste(parms$CorrectCount1,' (',round(parms$CorPerc1,digits=2),')',sep=''),
paste(parms$VMCount1,' (',round(parms$VMPerc1,digits=2),')',sep=''),
paste(parms$MCount1,' (',round(parms$MPerc1,digits=2),')',sep=''),
paste(parms$mCount1,' (',round(parms$mPerc1,digits=2),')',sep=''))
temp[1:2,1]=c('Within 1','Outside 1')
temp=as.data.frame(temp)
names(temp)=c('Range','Agree','Very Major','Major','Minor')
name.width <- max(sapply(names(temp), nchar))
names(temp) <- format(names(temp), width = name.width, justify = "centre")
print(format(temp, width = name.width, justify = "centre"),row.names=FALSE,quote=FALSE)
if(parms$idx==0) cat('\n \n NOTE: When the index score equals 0, there can be a range of optimal DIA breakpoints. We present the smallest breakpoint in this range.')
return(list(D1=D1,D2=D2))
}
ERBGivenDIA=function(MIC,DIA,MICBrkptL,MICBrkptU,DIABrkptL,DIABrkptU,
VM1=10,M1=10,m1=40,VM2=2,M2=2,m2=5){
MICBrkptL=MICBrkptL
MICBrkptU=MICBrkptU
DIABrkptL=DIABrkptL
DIABrkptU=DIABrkptU
D1=DIABrkptL; D2=DIABrkptU
if(D2<=D1){
stop('Lower DIA Breakpoint must be less than Upper DIA Breakpoint.')
}
N=length(MIC)
withinOne=rep(0,length(MIC))
#observations within one of intermediate range
withinOne=rep(0,length(MIC))
withinOne[which(MIC>=MICBrkptL & MIC<=MICBrkptU)]=1
numwithinOne=sum(withinOne)
cat('Classification for DIA Breakpoints for ERB:',D1,D2,'\n')
cat('Number of Isolates: ',N,'\n')
cat('Number Observed Outside One of Intermediate Range: ',N-numwithinOne,'\n')
cat('Number Observed Within One of Intermediate Range: ',numwithinOne,'\n')
temp=matrix(nrow=2,ncol=5)
parms=ERB(D1,D2,MIC,DIA,MICBrkptL,MICBrkptU,VM1,M1,m1,VM2,M2,m2,withinOne)
cat('Index Score = ',parms$idx,'\n \n')
cat('Count (%) \n')
temp[1,2:5]=c(paste(parms$CorrectCount2,' (',round(parms$CorPerc2,digits=2),')',sep=''),
paste(parms$VMCount2,' (',round(parms$VMPerc2,digits=2),')',sep=''),
paste(parms$MCount2,' (',round(parms$MPerc2,digits=2),')',sep=''),
paste(parms$mCount2,' (',round(parms$mPerc2,digits=2),')',sep=''))
temp[2,2:5]=c(paste(parms$CorrectCount1,' (',round(parms$CorPerc1,digits=2),')',sep=''),
paste(parms$VMCount1,' (',round(parms$VMPerc1,digits=2),')',sep=''),
paste(parms$MCount1,' (',round(parms$MPerc1,digits=2),')',sep=''),
paste(parms$mCount1,' (',round(parms$mPerc1,digits=2),')',sep=''))
temp[1:2,1]=c('Within 1','Outside 1')
temp=as.data.frame(temp)
names(temp)=c('Range','Agree','Very Major','Major','Minor')
name.width <- max(sapply(names(temp), nchar))
names(temp) <- format(names(temp), width = name.width, justify = "centre")
print(format(temp, width = name.width, justify = "centre"),row.names=FALSE,quote=FALSE)
invisible()
}
#plot single scatterplot
plotBrkPtsERB=function(MIC,DIA,xcens,ycens,MICBrkptL,MICBrkptU,DIABrkptL,DIABrkptU,MICXaxis,log2MIC){
M1=MICBrkptL; M2=MICBrkptU
D1=DIABrkptL; D2=DIABrkptU
MIC1=MIC
DIA1=DIA
MIC[xcens==1 & MIC==max(MIC)]=max(MIC)+1
MIC[xcens==-1 & MIC==min(MIC)]=min(MIC)-1
DIA[ycens==1 & DIA==max(DIA)]=max(DIA)+1
DIA[ycens==-1 & DIA==min(DIA)]=min(DIA)-1
n=length(MIC); classification=rep(NA,n)
for (i in 1:n){
#SS
if(MIC[i]<=M1 & DIA[i]>=D2)classification[i]='Correct'
#intermediate
else if ((MIC[i]>M1 & MIC[i]<M2) & (DIA[i]>D1 & DIA[i]<D2)) classification[i]='Correct'
#resistant
else if(MIC[i]>=M2 & DIA[i]<=D1)classification[i]='Correct'
#I MIC S DIA
else if((MIC[i]>M1 & MIC[i]<M2) & DIA[i]>=D2)classification[i]='Minor'
#R MIC S DIA
else if(MIC[i]>=M2 & DIA[i]>=D2)classification[i]='Very Major'
#S MIC I DIA
else if(MIC[i]<=M1 & (DIA[i]>D1 & DIA[i]<D2))classification[i]='Minor'
#R MIC I DIA
else if(MIC[i]>=M2 & (DIA[i]>D1 & DIA[i]<D2))classification[i]='Minor'
#S MIC R DIA
else if(MIC[i]<=M1 & DIA[i]<=D1)classification[i]='Major'
#I MIC R DIA
else if((MIC[i]>M1 & MIC[i]<M2) & DIA[i]<=D1)classification[i]='Minor'
}
a1=data.frame(MIC,DIA,classification,stringsAsFactors=FALSE)
a1 = a1 %>% group_by(MIC,DIA,classification) %>% summarize(Freq=n())
a1$classification=factor(a1$classification,levels=c("Correct", "Minor", "Major","Very Major"))
MICBrkptL=MICBrkptL+.5
MICBrkptU=MICBrkptU-.5
DIABrkptL=DIABrkptL+.5
DIABrkptU=DIABrkptU-.5
if(log2MIC==FALSE){
MICBrkptL=2^MICBrkptL
MICBrkptU=2^MICBrkptU
MIC2=MIC1
a1$MIC=2^a1$MIC
MICTemp=c(min(MIC1)-1,min(MIC1):max(MIC1),max(MIC1)+1)
MICTemp=2^MICTemp
x=2^(min(MIC1):max(MIC1))
}
if(MICXaxis==TRUE && log2MIC==TRUE){
fit=ggplot(a1,aes(MIC,DIA))+geom_text(aes(label=Freq,color=factor(classification)),size=4)+
geom_point(aes(group=factor(classification),color=factor(classification)),size=-1)+
geom_vline(xintercept=MICBrkptL,lty=2,alpha=.4)+
geom_vline(xintercept=MICBrkptU,lty=2,alpha=.4)+
geom_hline(yintercept=DIABrkptL,lty=2,alpha=.4)+
geom_hline(yintercept=DIABrkptU,lty=2,alpha=.4)+
labs(x='MIC (Dilution Test in log(ug/mL))',y='DIA (Diffusion Test in mm)')+
scale_x_continuous(breaks = seq(min(MIC1)-1,max(MIC1)+1,by=1),
labels = c(paste("<",min(MIC1),sep=''),seq(min(MIC1),max(MIC1),by=1), paste(">",max(MIC1),sep='')),
limits = c(min(MIC1)-1,max(MIC1)+1))+
scale_y_continuous(breaks = seq(min(DIA1)-1,max(DIA1)+1,by=1),
labels = c(paste("<",min(DIA1),sep=''),seq(min(DIA1),max(DIA1),by=1), paste(">",max(DIA1),sep='')),
limits = c(min(DIA1)-1,max(DIA1)+1))+
scale_color_manual(values=c('Correct'='Black','Minor'='blue','Major'='#CC9900','Very Major'='red'))+
guides(colour = guide_legend(override.aes = list(size=3,alpha = 1)))+theme_dbets()+
theme(
legend.position='top',
legend.title=element_blank(),
legend.key=element_rect(fill="gray95",colour="white"),
legend.text = element_text(size = 15))
}
if(MICXaxis==TRUE && log2MIC==FALSE){
fit=ggplot(a1,aes(MIC,DIA))+geom_text(aes(label=Freq,color=factor(classification)),size=4)+
geom_point(aes(group=factor(classification),color=factor(classification)),size=-1)+
geom_vline(xintercept=MICBrkptL,lty=2,alpha=.4)+
geom_vline(xintercept=MICBrkptU,lty=2,alpha=.4)+
geom_hline(yintercept=DIABrkptL,lty=2,alpha=.4)+
geom_hline(yintercept=DIABrkptU,lty=2,alpha=.4)+
labs(x='MIC (Dilution Test in ug/mL)',y='DIA (Diffusion Test in mm)')+
scale_x_continuous(trans=log2_trans(),
limits=c(min(MICTemp),max(MICTemp)),
breaks=MICTemp,
labels=c(paste("<",min(x),sep=''),sort(unique(x)), paste(">",max(x),sep='')))+
scale_y_continuous(breaks = seq(min(DIA1)-1,max(DIA1)+1,by=1),
labels = c(paste("<",min(DIA1),sep=''),seq(min(DIA1),max(DIA1),by=1), paste(">",max(DIA1),sep='')),
limits = c(min(DIA1)-1,max(DIA1)+1))+
scale_color_manual(values=c('Correct'='Black','Minor'='blue','Major'='#CC9900','Very Major'='red'))+
guides(colour = guide_legend(override.aes = list(size=3,alpha = 1)))+theme_dbets()+
theme(
legend.position='top',
legend.title=element_blank(),
legend.key=element_rect(fill="gray95",colour="white"),
legend.text = element_text(size = 14))
}
if(MICXaxis==FALSE && log2MIC==TRUE){
fit=ggplot(a1,aes(DIA,MIC))+geom_text(aes(label=Freq,color=factor(classification)),size=4)+
geom_point(aes(group=factor(classification),color=factor(classification)),size=-1)+
geom_hline(yintercept=MICBrkptL,lty=2,alpha=.4)+
geom_hline(yintercept=MICBrkptU,lty=2,alpha=.4)+
geom_vline(xintercept=DIABrkptL,lty=2,alpha=.4)+
geom_vline(xintercept=DIABrkptU,lty=2,alpha=.4)+
labs(y='MIC (Dilution Test in log(ug/mL))',x='DIA (Diffusion Test in mm)')+
scale_y_continuous(breaks = seq(min(MIC1)-1,max(MIC1)+1,by=1),
labels = c(paste("<",min(MIC1),sep=''),seq(min(MIC1),max(MIC1),by=1), paste(">",max(MIC1),sep='')),
limits = c(min(MIC1)-1,max(MIC1)+1))+
scale_x_continuous(breaks = seq(min(DIA1)-1,max(DIA1)+1,by=1),
labels = c(paste("<",min(DIA1),sep=''),seq(min(DIA1),max(DIA1),by=1), paste(">",max(DIA1),sep='')),
limits = c(min(DIA1)-1,max(DIA1)+1))+
scale_color_manual(values=c('Correct'='Black','Minor'='blue','Major'='#CC9900','Very Major'='red'))+
guides(colour = guide_legend(override.aes = list(size=3,alpha = 1)))+theme_dbets()+
theme(
legend.position='top',
legend.title=element_blank(),
legend.key=element_rect(fill="gray95",colour="white"),
legend.text = element_text(size = 14))
}
if(MICXaxis==FALSE && log2MIC==FALSE){
fit=ggplot(a1,aes(DIA,MIC))+geom_text(aes(label=Freq,color=factor(classification)),size=4)+
geom_point(aes(group=factor(classification),color=factor(classification)),size=-1)+
geom_hline(yintercept=MICBrkptL,lty=2,alpha=.4)+
geom_hline(yintercept=MICBrkptU,lty=2,alpha=.4)+
geom_vline(xintercept=DIABrkptL,lty=2,alpha=.4)+
geom_vline(xintercept=DIABrkptU,lty=2,alpha=.4)+
labs(y='MIC (Dilution Test in ug/mL)',x='DIA (Diffusion Test in mm)')+
scale_y_continuous(trans=log2_trans(),
limits=c(min(MICTemp),max(MICTemp)),
breaks=MICTemp,
labels=c(paste("<",min(x),sep=''),sort(unique(x)), paste(">",max(x),sep='')))+
scale_x_continuous(breaks = seq(min(DIA1)-1,max(DIA1)+1,by=1),
labels = c(paste("<",min(DIA1),sep=''),seq(min(DIA1),max(DIA1),by=1), paste(">",max(DIA1),sep='')),
limits = c(min(DIA1)-1,max(DIA1)+1))+
scale_color_manual(values=c('Correct'='Black','Minor'='blue','Major'='#CC9900','Very Major'='red'))+
guides(colour = guide_legend(override.aes = list(size=3,alpha = 1)))+theme_dbets()+
theme(
legend.position='top',
legend.title=element_blank(),
legend.key=element_rect(fill="gray95",colour="white"),
legend.text = element_text(size = 14))+
guides(colour = guide_legend(override.aes = list(size=3,alpha = 1)))
}
return(fit)
}
bootStrapERB=function(MIC,DIA,MICBrkptL,MICBrkptU,VM1=10,M1=10,m1=40,VM2=2,M2=2,m2=5,
minWidth=3,maxWidth=10){
a1=data.frame(MIC=MIC,DIA=DIA)
DIABrkptL=rep(NA,5000)
DIABrkptU=rep(NA,5000)
n=nrow(a1)
for(i in 1:5000){
tmp=sample_n(a1,n,replace=TRUE)
parms=findBrkptsERBC(tmp$MIC,tmp$DIA,VM1,M1,m1,VM2,M2,m2,MICBrkptL,MICBrkptU,minWidth,maxWidth)
DIABrkptL[i]=parms$D1
DIABrkptU[i]=parms$D2
}
#print results
tab=table(DIABrkptL,DIABrkptU)
a1=tab/margin.table(tab)*100
a1=as.data.frame(a1)
a1=a1[order(a1$Freq,decreasing=T),]
a1=a1[a1$Freq!=0,]
a2=a1
a2$CumFreq=cumsum(a2$Freq)
a2[,3]=round(a2[,3],2)
a2[,4]=round(a2[,4],2)
cat('Bootstrap samples = 5000 \n')
cat('\n-------DIA Breakpoints by Confidence--------\n')
temp=data.frame(DIABrkptL=a2[,1],DIABrkptU=a2[,2],Percent=a2[,3],Cumulative=a2[,4])
temp[,1:4] = apply(temp[,1:4], 2, function(x) as.character(x));
name.width <- max(sapply(names(temp), nchar))
names(temp) <- format(names(temp), width = name.width, justify = "centre")
print(format(temp, width = name.width, justify = "centre"),row.names=FALSE,quote=FALSE)
return(a1)
}
plotBootDataERB=function(bootData){
bootData$cumFreq=cumsum(bootData$Freq)
bootData[,1]=as.numeric(as.character(bootData[,1]))
bootData[,2]=as.numeric(as.character(bootData[,2]))
D1=bootData[,1]
D2=bootData[,2]
idx=max(which(bootData$cumFreq<95))
a1=bootData[1:(idx+1),]
if((idx+1)!=nrow(bootData))
a2=bootData[(idx+2):nrow(bootData),]
a1$Freq=format(round(a1$Freq, 1), nsmall = 1)
fit=ggplot(data=a1,aes(x=DIABrkptL,y=DIABrkptU,label=Freq))+geom_text(size=6.5)+
scale_x_continuous(breaks = seq(min(D1),max(D1),by=1),
limits = c(min(D1),max(D1)))+
scale_y_continuous(breaks = seq(min(D2),max(D2),by=1),
limits = c(min(D2),max(D2)))+
labs(x='Lower DIA Breakpoint',y='Upper DIA Breakpoint',
title="DIA Breakpoint Distribution", subtitle="Black points are outside 95% confidence")+
theme_dbets()
if((idx+1)!=nrow(bootData))
fit=fit+geom_point(data=a2,(aes(x=DIABrkptL,y=DIABrkptU)),size=2.5)
print(fit)
invisible()
}
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