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Añadido curvas de superviviencia

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marcelcosta
2020-11-13 16:21:12 +01:00
parent 19097d20dc
commit ac2630acd3
1 changed files with 152 additions and 48 deletions
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invivos/app.R
+109 -5
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@@ -8,6 +8,8 @@ library(ggbeeswarm)
library(gtools)
library(gridExtra)
source("../../funcions.R")
library(survminer)
library(survival)
# Define UI for application
ui <- fluidPage(
@@ -34,6 +36,7 @@ ui <- fluidPage(
sidebarPanel(
fileInput(inputId = "file_analy", label = "Hoja de análisis", multiple = F),
selectInput(inputId = "vacc", "Experimento de Vacunación", selected = "No", choices = c("Sí","No")),
sliderInput("cutoff", "Cutoff para Survival", min=100, max=1500, step=50, value=750),
checkboxInput("filter_stats","Filtrar Estadística")
),
mainPanel(
@@ -42,6 +45,7 @@ ui <- fluidPage(
h3('Cinéticas'),
plotOutput('cin_group'),
plotOutput('cin_indiv'),
plotOutput('survival', height="800px"),
h3('Estadística'),
verbatimTextOutput('stats'),
tableOutput('tab_stats')
@@ -248,7 +252,6 @@ server <- function(input, output) {
if ("ID.tumor" %in% colnames(table)){table<-rename(table, "ID tumor"=`ID.tumor`)}
# table[table$ID.tumor == "R","0"]<-NA
col_nodays<-c("ID", "Cage","Group", "ID.animal","ID animal", "ID.tumor", "ID tumor", "TS","DPV", "Absorbance")
print(grep(0, colnames(table)[!colnames(table) %in% col_nodays]))
if (length(grep(0, colnames(table)[!colnames(table) %in% col_nodays])) == 0){
table["0"]<-0
}
@@ -327,6 +330,54 @@ server <- function(input, output) {
}
}
})
output$survival<-renderPlot({
if (!is.null(input$file_analy) & !is.null(analysis$taula_def)){
observeEvent(analysis$taula_def, {})
table<-analysis$taula_def
if (input$vacc == "Sí"){
g<-list()
for (side in c("L","R")){
tableR<-filter(table, `ID tumor` == side) %>% filter(!is.na(Volume))
endtime<-dcast(tableR %>% filter(Volume < cutoff), Cage+`ID animal`+`ID tumor`+Group~., value.var = "Timepoint", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% rename("end"=".")
endtime["Dead"]<-dcast(tableR, Cage+`ID animal`+`ID tumor`+Group~., value.var = "Volume", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% pull(".") > input$cutoff
table_tumor<<-endtime
g[side]<-ggsurvplot(survfit(Surv(table_tumor$end, table_tumor$Dead) ~ table_tumor$Group, data=table_tumor),
pval = T, pval.method = T,
title = side,
# legend.labs = paste(c("< median", ">= median"), "MICA"),
ggtheme=theme_classic(base_size=15)
# conf.int = TRUE,
# Add risk table
# risk.table = TRUE,
# tables.height = 0.2,
# tables.theme = theme_cleantable(),
# Color palettes. Use custom color: c("#E7B800", "#2E9FDF"),
# or brewer color (e.g.: "Dark2"), or ggsci color (e.g.: "jco")
# palette = c("#E7B800", "#2E9FDF")
)
}
do.call(grid.arrange, g)
}else{
tableR<-table %>% filter(!is.na(Volume))
endtime<-dcast(tableR %>% filter(Volume < cutoff), `ID animal`+Group~., value.var = "Timepoint", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% rename("end"=".")
endtime["Dead"]<-dcast(tableR, `ID animal`+Group~., value.var = "Volume", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% pull(".") > input$cutoff
table_tumor<<-endtime
g<-ggsurvplot(survfit(Surv(table_tumor$end, table_tumor$Dead) ~ table_tumor$Group, data=table_tumor),
pval = T, pval.method = T,
# legend.labs = paste(c("< median", ">= median"), "MICA"),
ggtheme=theme_classic(base_size=15)
# palette = c("#E7B800", "#2E9FDF")
)
g
}
}
})
output$stats<-renderPrint({
stattest<-"dunn"
oneside<-""
@@ -409,8 +460,7 @@ server <- function(input, output) {
if (!is.null(input$file_analy) & !is.null(analysis$taula_def)){
table<-analysis$taula_def
print(head(table))
if (input$fig_id %in% c("Cinética Grupo", "Cinética Individual")){
if (input$fig_id == "Cinética Grupo"){
if (input$vacc == "Sí"){
g<-ggplot(table, aes(as.numeric(as.character(Timepoint)), Volume, color=Group, group=Group))+
@@ -459,9 +509,58 @@ server <- function(input, output) {
g<-g+scale_color_manual(values=v_col)+
scale_fill_manual(values=v_col)
}
}else{
gg_color_hue <- function(n, l=65) {
hues <- seq(15, 375, length=n+1)
hcl(h=hues, l=l, c=100)[1:n]
}
if (input$vacc == "Sí"){
g<-list()
count<-1
for (side in c("L","R")){
tableR<-filter(table, `ID tumor` == side) %>% filter(!is.na(Volume))
endtime<-dcast(tableR %>% filter(Volume < cutoff), Cage+`ID animal`+`ID tumor`+Group~., value.var = "Timepoint", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% rename("end"=".")
endtime["Dead"]<-dcast(tableR, Cage+`ID animal`+`ID tumor`+Group~., value.var = "Volume", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% pull(".") > input$cutoff
table_tumor<<-endtime
if (input$colors != ""){
col<-input$colors
}else{
col<-gg_color_hue(length(unique(endtime$Group)))
}
g[[count]]<-ggsurvplot(survfit(Surv(table_tumor$end, table_tumor$Dead) ~ table_tumor$Group, data=table_tumor),
pval = T, pval.method = T,
title = side,
# legend.labs = paste(c("< median", ">= median"), "MICA"),
ggtheme=theme_classic(base_size=input$`font-size`),
palette = col
)
count<-count+1
}
g_surv_vacc<-g
}else{
if (input$colors != ""){
col<-input$colors
}else{
col<-gg_color_hue(length(unique(table_tumor$Group)))
}
g<-ggsurvplot(survfit(Surv(table_tumor$end, table_tumor$Dead) ~ table_tumor$Group, data=table_tumor),
pval = T, pval.method = T,
# legend.labs = paste(c("< median", ">= median"), "MICA"),
ggtheme=theme_classic(base_size=input$`font-size`),
palette = col
)
}
}
if (input$vacc == "Sí" & input$fig_id == "Survival"){
dades$plot<<-g_surv_vacc
arrange_ggsurvplots(g, nrow=2, ncol=1)
}else{
dades$plot<<-g
g
}
}
}, res=72)
output$downloadPicture <- downloadHandler(
@@ -469,11 +568,16 @@ server <- function(input, output) {
paste("Figura", ".png", sep="")
},
content = function(file){
print(file)
# tempReport <- file.path(tempdir(), "elispots.Rmd")
# file.copy("elispots.Rmd", tempReport, overwrite = TRUE)
png(file, width = input$width, height=input$height, units = "px", res=720)
plot(dades$plot)
if (input$fig_id == "Survival"){
if (input$vacc == "Sí"){
arrange_ggsurvplots(dades$plot, nrow=2, ncol=1)
}else{
arrange_ggsurvplots(list(dades$plot), ncol=1)
}
}else{plot(dades$plot)}
dev.off()
})