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Function.R
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#Function for Screening----
##Single Variant-Binary Value
Interation_Screening_SV_BV<-
function(InputData,
Set_Column,
Set_Comparison_A,
Set_Comparison_B){
Result_Frame<-
data.frame(
Items=colnames(InputData)[Set_Column],
Pc=NA,
OS.HR.in.Pos=NA,
OS.Pval.in.Pos=NA,
OS.HR.in.Neg=NA,
OS.Pval.in.Neg=NA,
OS.Inter.k=NA,
OS.Inter.Pval=NA,
PFS.HR.in.Pos=NA,
PFS.Pval.in.Pos=NA,
PFS.HR.in.Neg=NA,
PFS.Pval.in.Neg=NA,
PFS.Inter.k=NA,
PFS.Inter.Pval=NA,
OS.HR.Items=NA,
OS.Pval.Items=NA,
PFS.HR.Items=NA,
PFS.Pval.Items=NA,
OS.HR.Items.JS001=NA,
OS.Pval.Items.JS001=NA,
PFS.HR.Items.JS001=NA,
PFS.Pval.Items.JS001=NA
)
for(i in 1:length(Set_Column)){
InputData_Select<-
InputData[c("SUBJID","PFS","PFS.status.","OS","OS.status.",
"Grouping",Result_Frame$Items[i])]%>%unique()
#Frequency
Freq_Table<-
table(InputData_Select[,Result_Frame$Items[i]])%>%
prop.table()%>%as.data.frame()
if(any(Freq_Table$Var1%in%Set_Comparison_A)){
Result_Frame[i,2]<-
Freq_Table[,2][Freq_Table[,1]%in%Set_Comparison_A]%>%sum()
names(InputData_Select)[7]<-"Item"
InputData_Select$Item[
InputData_Select$Item%in%Set_Comparison_B
]<-"Control"
InputData_Select$Item[
InputData_Select$Item%in%Set_Comparison_A
]<-"Pos"
InputData_Select<-
subset(InputData_Select,Item%in%c("Control","Pos"))
InputData_Select$Item<-
factor(InputData_Select$Item,
levels = c("Control","Pos"))
InputData_Select$Grouping<-
factor(InputData_Select$Grouping,
levels = c("Chemotherapy+Placebo","Chemotherapy+Toripalimab"))
if(Result_Frame[i,2]>0.05){
#OS
OS_Summary_IO<-coxph(Surv(`OS`,`OS.status.`)~Grouping,
data = subset(InputData_Select,Item=="Pos"))%>%summary()
Result_Frame[i,3]<-
OS_Summary_IO$coefficients[1,2]
Result_Frame[i,4]<-
OS_Summary_IO$coefficients[1,5]
OS_Summary_Placebo<-coxph(Surv(`OS`,`OS.status.`)~Grouping,
data = subset(InputData_Select,Item=="Control"))%>%summary()
Result_Frame[i,5]<-
OS_Summary_Placebo$coefficients[1,2]
Result_Frame[i,6]<-
OS_Summary_Placebo$coefficients[1,5]
OS_Summary<-coxph(Surv(`OS`,`OS.status.`)~Item+Grouping+Item*Grouping,
data = InputData_Select)%>%summary()
Result_Frame[i,7]<-
OS_Summary$coefficients[3,1]
Result_Frame[i,8]<-
OS_Summary$coefficients[3,5]
#PFS
PFS_Summary_IO<-coxph(Surv(`PFS`,`PFS.status.`)~Grouping,
data = subset(InputData_Select,Item=="Pos"))%>%summary()
Result_Frame[i,9]<-
PFS_Summary_IO$coefficients[1,2]
Result_Frame[i,10]<-
PFS_Summary_IO$coefficients[1,5]
PFS_Summary_Placebo<-coxph(Surv(`PFS`,`PFS.status.`)~Grouping,
data = subset(InputData_Select,Item=="Control"))%>%summary()
Result_Frame[i,11]<-
PFS_Summary_Placebo$coefficients[1,2]
Result_Frame[i,12]<-
PFS_Summary_Placebo$coefficients[1,5]
PFS_Summary<-coxph(Surv(`PFS`,`PFS.status.`)~Item+Grouping+Item*Grouping,
data = InputData_Select)%>%summary()
Result_Frame[i,13]<-
PFS_Summary$coefficients[3,1]
Result_Frame[i,14]<-
PFS_Summary$coefficients[3,5]
#All
OS_Summary<-coxph(Surv(`OS`,`OS.status.`)~Item,
data = InputData_Select)%>%summary()
Result_Frame[i,15]<-
OS_Summary$coefficients[1,2]
Result_Frame[i,16]<-
OS_Summary$coefficients[1,5]
PFS_Summary<-coxph(Surv(`PFS`,`PFS.status.`)~Item,
data = InputData_Select)%>%summary()
Result_Frame[i,17]<-
PFS_Summary$coefficients[1,2]
Result_Frame[i,18]<-
PFS_Summary$coefficients[1,5]
#JS001
OS_Summary<-coxph(Surv(`OS`,`OS.status.`)~Item,
data = subset(InputData_Select,Grouping=="Chemotherapy+Toripalimab"))%>%summary()
Result_Frame[i,19]<-
OS_Summary$coefficients[1,2]
Result_Frame[i,20]<-
OS_Summary$coefficients[1,5]
PFS_Summary<-coxph(Surv(`PFS`,`PFS.status.`)~Item,
data = subset(InputData_Select,Grouping=="Chemotherapy+Toripalimab"))%>%summary()
Result_Frame[i,21]<-
PFS_Summary$coefficients[1,2]
Result_Frame[i,22]<-
PFS_Summary$coefficients[1,5]
}
}
}
return(Result_Frame)
}
Interation_Screening_SV_BV_ForKvalue<-
function(InputData,
Set_Column,
Set_Comparison_A,
Set_Comparison_B){
Result_Frame<-
data.frame(
Items=colnames(InputData)[Set_Column],
Pc=NA,
OS.Inter.k=NA,
OS.Inter.Pval=NA,
OS.Inter.k.Up=NA,
OS.Inter.k.Down=NA,
PFS.Inter.k=NA,
PFS.Inter.Pval=NA,
PFS.Inter.k.Up=NA,
PFS.Inter.k.Down=NA
)
for(i in 1:length(Set_Column)){
InputData_Select<-
InputData[c("SUBJID","PFS","PFS.status.","OS","OS.status.",
"Grouping",Result_Frame$Items[i])]%>%unique()
#Frequency
Freq_Table<-
table(InputData_Select[,Result_Frame$Items[i]])%>%
prop.table()%>%as.data.frame()
if(any(Freq_Table$Var1%in%Set_Comparison_A)){
Result_Frame[i,2]<-
Freq_Table[,2][Freq_Table[,1]%in%Set_Comparison_A]%>%sum()
names(InputData_Select)[7]<-"Item"
InputData_Select$Item[
InputData_Select$Item%in%Set_Comparison_B
]<-"Control"
InputData_Select$Item[
InputData_Select$Item%in%Set_Comparison_A
]<-"Pos"
InputData_Select<-
subset(InputData_Select,Item%in%c("Control","Pos"))
InputData_Select$Item<-
factor(InputData_Select$Item,
levels = c("Control","Pos"))
InputData_Select$Grouping<-
factor(InputData_Select$Grouping,
levels = c("Chemotherapy+Placebo","Chemotherapy+Toripalimab"))
if(Result_Frame[i,2]>0.05){
#OS
OS_Summary<-coxph(Surv(`OS`,`OS.status.`)~Item+Grouping+Item*Grouping,
data = InputData_Select)%>%summary()
Result_Frame[i,3]<-
OS_Summary$coefficients[3,1]
Result_Frame[i,4]<-
OS_Summary$coefficients[3,5]
Result_Frame[i,5]<-
OS_Summary$conf.int[3,4]%>%log()
Result_Frame[i,6]<-
OS_Summary$conf.int[3,3]%>%log()
#PFS
PFS_Summary<-coxph(Surv(`PFS`,`PFS.status.`)~Item+Grouping+Item*Grouping,
data = InputData_Select)%>%summary()
Result_Frame[i,7]<-
PFS_Summary$coefficients[3,1]
Result_Frame[i,8]<-
PFS_Summary$coefficients[3,5]
Result_Frame[i,9]<-
PFS_Summary$conf.int[3,4]%>%log()
Result_Frame[i,10]<-
PFS_Summary$conf.int[3,3]%>%log()
#All
}
}
}
return(Result_Frame)
}
##ForrestPlot----
SubgroupHR_Plot<-
function(InputData,
Set_Column,
Set_Comparison_Group,
Range=c(0.2,5)){
ForrestPlot_Data_OS<-
data.frame(
Items=c(names(InputData)[Set_Column],
Set_Comparison_Group),
`HR (95% CI)`=NA,
HR_exact=NA,
Up_CI=NA,
Low_CI=NA,
Pvalue=NA,
Freq=NA
)
ForrestPlot_Data_PFS<-
data.frame(
Items=c(names(InputData)[Set_Column],
Set_Comparison_Group),
`HR (95% CI)`=NA,
HR_exact=NA,
Up_CI=NA,
Low_CI=NA,
Pvalue=NA,
Freq=NA
)
InputData_Select<-
InputData[c("SUBJID","PFS","PFS.status.","OS","OS.status.",
"Grouping",names(InputData)[Set_Column])]%>%unique()
names(InputData_Select)[7]<-"Item"
InputData_Select$Grouping<-
factor(InputData_Select$Grouping,
levels=c("Chemotherapy+Placebo","Chemotherapy+Toripalimab"))
ForrestPlot_Data_PFS$Freq[-1]<-
table(InputData_Select$Item)%>%as.data.frame()%>%FeaturetoRow()%>%
.[as.character(Set_Comparison_Group),]
ForrestPlot_Data_OS$Freq[-1]<-
table(InputData_Select$Item)%>%as.data.frame()%>%FeaturetoRow()%>%
.[as.character(Set_Comparison_Group),]
for(i in Set_Comparison_Group){
PFS_Summary_IO<-coxph(Surv(PFS,`PFS.status.`)~Grouping,
data = subset(InputData_Select,Item==i))%>%summary()
OS_Summary_IO<-coxph(Surv(OS,`OS.status.`)~Grouping,
data = subset(InputData_Select,Item==i))%>%summary()
ForrestPlot_Data_PFS$HR_exact[which(ForrestPlot_Data_PFS$Items==i)]<-
PFS_Summary_IO$coefficients[1,2]
ForrestPlot_Data_PFS$Pvalue[which(ForrestPlot_Data_PFS$Items==i)]<-
PFS_Summary_IO$coefficients[1,5]%>%
round(.,digits = 3)
ForrestPlot_Data_PFS$Up_CI[which(ForrestPlot_Data_PFS$Items==i)]<-
PFS_Summary_IO$conf.int[1,4]
ForrestPlot_Data_PFS$Low_CI[which(ForrestPlot_Data_PFS$Items==i)]<-
PFS_Summary_IO$conf.int[1,3]
ForrestPlot_Data_OS$HR_exact[which(ForrestPlot_Data_OS$Items==i)]<-
OS_Summary_IO$coefficients[1,2]
ForrestPlot_Data_OS$Pvalue[which(ForrestPlot_Data_OS$Items==i)]<-
OS_Summary_IO$coefficients[1,5]%>%
round(.,digits = 3)
ForrestPlot_Data_OS$Up_CI[which(ForrestPlot_Data_OS$Items==i)]<-
OS_Summary_IO$conf.int[1,4]
ForrestPlot_Data_OS$Low_CI[which(ForrestPlot_Data_OS$Items==i)]<-
OS_Summary_IO$conf.int[1,3]
}
ForrestPlot_Data_PFS$HR..95..CI.<-
paste(round(ForrestPlot_Data_PFS$HR_exact,digits = 2),"(",
round(ForrestPlot_Data_PFS$Low_CI,digits = 2)," to ",
round(ForrestPlot_Data_PFS$Up_CI,digits = 2),")",sep = "")
ForrestPlot_Data_OS$HR..95..CI.<-
paste(round(ForrestPlot_Data_OS$HR_exact,digits = 2),"(",
round(ForrestPlot_Data_OS$Low_CI,digits = 2)," to ",
round(ForrestPlot_Data_OS$Up_CI,digits = 2),")",sep = "")
ForrestPlot_Data_PFS[1,c(2,6,7)]<-
c("HR(95% CI)","P-value","Freq")
PFS_Plot<-
forestplot(as.matrix(ForrestPlot_Data_PFS[c(1,2,7,6)]),
ForrestPlot_Data_PFS$HR_exact,ForrestPlot_Data_PFS$Low_CI,ForrestPlot_Data_PFS$Up_CI,
xlog = TRUE,
zero = 1,
xticks = c(Range[1],1,Range[2]),
colgap = unit(10,"mm"),
graphwidth=unit(50,"mm"),
lineheight = unit(1,"cm"),
graph.pos = 4,
col = fpColors(lines="#0177BF", box="#0177BF",zero = "BLACK"),
boxsize = 0.4,
ci.vertices = F,
lty.ci = 1,
lwd.ci = 1.5,
lwd.zero=0.4,
lty.zero=3,
txt_gp=fpTxtGp(label = gpar(cex=0.8),
ticks = gpar(cex=0.8)), is.summary = c(rep(FALSE,19)),
fn.ci_norm = fpDrawNormalCI,
hrzl_lines=list("1" = gpar(lwd=1, col="black")))
ForrestPlot_Data_OS[1,c(2,6,7)]<-
c("HR(95% CI)","P-value","Freq")
OS_Plot<-
forestplot(as.matrix(ForrestPlot_Data_OS[c(1,2,7,6)]),
ForrestPlot_Data_OS$HR_exact,ForrestPlot_Data_OS$Low_CI,ForrestPlot_Data_OS$Up_CI,
xlog = TRUE,
zero = 1,
xticks = c(Range[1],1,Range[2]),
colgap = unit(10,"mm"),
graphwidth=unit(50,"mm"),
lineheight = unit(1,"cm"),
graph.pos = 4,
col = fpColors(lines="#0177BF", box="#0177BF",zero = "BLACK"),
boxsize = 0.4,
ci.vertices = F,
lty.ci = 1,
lwd.ci = 1.5,
lwd.zero=0.4,
lty.zero=3,
txt_gp=fpTxtGp(label = gpar(cex=0.8),
ticks = gpar(cex=0.8)), is.summary = c(rep(FALSE,19)),
fn.ci_norm = fpDrawNormalCI,
hrzl_lines=list("1" = gpar(lwd=1, col="black")))
return(list(Data_PFS=ForrestPlot_Data_PFS,
Data_OS=ForrestPlot_Data_OS,
PFS=PFS_Plot,
OS=OS_Plot))
}
#Plot----
GeomSplitViolin <- ggproto("GeomSplitViolin", GeomViolin,
draw_group = function(self, data, ..., draw_quantiles = NULL) {
data <- transform(data, xminv = x - violinwidth * (x - xmin), xmaxv = x + violinwidth * (xmax - x))
grp <- data[1, "group"]
newdata <- plyr::arrange(transform(data, x = if (grp %% 2 == 1) xminv else xmaxv), if (grp %% 2 == 1) y else -y)
newdata <- rbind(newdata[1, ], newdata, newdata[nrow(newdata), ], newdata[1, ])
newdata[c(1, nrow(newdata) - 1, nrow(newdata)), "x"] <- round(newdata[1, "x"])
if (length(draw_quantiles) > 0 & !scales::zero_range(range(data$y))) {
stopifnot(all(draw_quantiles >= 0), all(draw_quantiles <=
1))
quantiles <- ggplot2:::create_quantile_segment_frame(data, draw_quantiles)
aesthetics <- data[rep(1, nrow(quantiles)), setdiff(names(data), c("x", "y")), drop = FALSE]
aesthetics$alpha <- rep(1, nrow(quantiles))
both <- cbind(quantiles, aesthetics)
quantile_grob <- GeomPath$draw_panel(both, ...)
ggplot2:::ggname("geom_split_violin", grid::grobTree(GeomPolygon$draw_panel(newdata, ...), quantile_grob))
}
else {
ggplot2:::ggname("geom_split_violin", GeomPolygon$draw_panel(newdata, ...))
}
})
geom_split_violin <- function(mapping = NULL, data = NULL, stat = "ydensity", position = "identity", ...,
draw_quantiles = NULL, trim = TRUE, scale = "area", na.rm = FALSE,
show.legend = NA, inherit.aes = TRUE) {
layer(data = data, mapping = mapping, stat = stat, geom = GeomSplitViolin,
position = position, show.legend = show.legend, inherit.aes = inherit.aes,
params = list(trim = trim, scale = scale, draw_quantiles = draw_quantiles, na.rm = na.rm, ...))
}