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Corrección del Survival y implementación de corte de operados y eliminación de muertes.

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marcelcosta
2023-10-05 17:30:36 +02:00
parent 16088aac2b
commit 9f0cda73eb
1 changed files with 59 additions and 4 deletions
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invivos/app.R
+59 -4
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@@ -587,6 +587,20 @@ server <- function(input, output) {
observeEvent(analysis$taula, {})
table<-analysis$taula
if (input$vacc == "Sí"){
firstoper<- filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "*") %>%
select(DayPostInoc, Side) %>% unique() %>%
group_by(Side) %>% summarise(FirstOper=min(DayPostInoc))
if (input$operated == TRUE){
for (i in 1:nrow(firstoper)){
table<-table %>% filter(DayPostInoc < firstoper$FirstOper[i] | Side != firstoper$Side[i])
}
}else{
if(input$dead == TRUE){
deadmice<-filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "+") %>%
pull(Animal)
table<-table %>% filter(!Animal %in% deadmice)
}
}
g<-list()
for (side in c("L","R")){
tableR<-filter(table, Side == side) %>% filter(!is.na(Volume))
@@ -594,7 +608,7 @@ server <- function(input, output) {
endtime["Dead"]<-dcast(tableR, Cage+Animal+Side+Group~., value.var = "Volume", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% pull(".") > input$cutoff
table_tumor<<-endtime
g[side]<-ggsurvplot(survfit(Surv(table_tumor$end, table_tumor$Dead) ~ table_tumor$Group, data=table_tumor),
g[side]<-ggsurvplot(survfit(Surv(end, Dead) ~ Group, data=table_tumor),
pval = T, pval.method = T,
title = side,
# legend.labs = paste(c("< median", ">= median"), "MICA"),
@@ -613,13 +627,27 @@ server <- function(input, output) {
do.call(grid.arrange, g)
}else{
firstoper<- filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "*") %>%
pull(DayPostInoc) %>% min(na.rm = T)
print(firstoper)
if (input$operated == TRUE){
table<-table %>% filter(DayPostInoc < firstoper)
}else{
deadmice<-filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "+") %>%
pull(Animal)
if(input$dead == TRUE){
table<-table %>% filter(!Animal %in% deadmice)
}
}
tableR<-table %>% filter(!is.na(Volume))
endtime<-dcast(if(length(unique(tableR$DayPostInoc)) > 1){tableR %>% filter(Volume < input$cutoff)}else{tableR}, Animal+Side+Group~.,
value.var = "DayPostInoc", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% rename("end"=".")
endtime["Dead"]<-dcast(tableR, Animal+Side+Group~., value.var = "Volume", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% pull(".") >= input$cutoff
table_tumor<<-endtime
g<-ggsurvplot(survfit(Surv(table_tumor$end, table_tumor$Dead) ~ table_tumor$Group, data=table_tumor),
g<-ggsurvplot(survfit(Surv(end, Dead) ~ Group, data=table_tumor),
pval = T, pval.method = T,
# legend.labs = paste(c("< median", ">= median"), "MICA"),
ggtheme=theme_classic(base_size=15)
@@ -901,6 +929,20 @@ server <- function(input, output) {
}
if (input$vacc == "Sí"){
firstoper<- filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "*") %>%
select(DayPostInoc, Side) %>% unique() %>%
group_by(Side) %>% summarise(FirstOper=min(DayPostInoc))
if (input$operated == TRUE){
for (i in 1:nrow(firstoper)){
table<-table %>% filter(DayPostInoc < firstoper$FirstOper[i] | Side != firstoper$Side[i])
}
}else{
if(input$dead == TRUE){
deadmice<-filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "+") %>%
pull(Animal)
table<-table %>% filter(!Animal %in% deadmice)
}
}
g<-list()
count<-1
for (side in c("L","R")){
@@ -914,7 +956,7 @@ server <- function(input, output) {
col<-gg_color_hue(length(unique(endtime$Group)))
}
table_tumor$Group<-factor(table_tumor$Group, levels = levels(analysis$taula$Group))
g[[count]]<-ggsurvplot(survfit(Surv(table_tumor$end, table_tumor$Dead) ~ Group, data=table_tumor),
g[[count]]<-ggsurvplot(survfit(Surv(end, Dead) ~ Group, data=table_tumor),
pval = T, pval.method = T,
title = side,
ggtheme=theme_classic(base_size=input$`font-size`),
@@ -925,6 +967,19 @@ server <- function(input, output) {
g_surv_vacc<-g
}else{
firstoper<- filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "*") %>%
pull(DayPostInoc) %>% min(na.rm = T)
print(firstoper)
if (input$operated == TRUE){
table<-table %>% filter(DayPostInoc < firstoper)
}else{
deadmice<-filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "+") %>%
pull(Animal)
if(input$dead == TRUE){
table<-table %>% filter(!Animal %in% deadmice)
}
}
tableR<-table %>% filter(!is.na(Volume))
endtime<-dcast(tableR %>% filter(Volume < (input$cutoff*as.numeric(input$unit_fact))), Animal+Group~., value.var = "DayPostInoc", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% rename("end"=".")
endtime["Dead"]<-dcast(tableR, Animal+Group~., value.var = "Volume", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% pull(".") > (input$cutoff*as.numeric(input$unit_fact))
@@ -935,7 +990,7 @@ server <- function(input, output) {
col<-gg_color_hue(length(unique(table_tumor$Group)))
}
table_tumor$Group<-factor(table_tumor$Group, levels = levels(analysis$taula$Group))
g<-ggsurvplot(survfit(Surv(table_tumor$end, table_tumor$Dead) ~ Group, data=table_tumor),
g<-ggsurvplot(survfit(Surv(end, Dead) ~ Group, data=table_tumor),
pval = T, pval.method = T,
# ggtheme=theme_classic(base_size=input$`font-size`),
palette = col