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1059 lines
44 KiB
1059 lines
44 KiB
##V2.0
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library(shiny)
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library(reshape2)
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library(openxlsx)
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library(car)
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library(ggbeeswarm)
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library(gtools)
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library(gridExtra)
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source("../../funcions.R")
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library(survminer)
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library(survival)
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library(plotrix)
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library(tidyverse)
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library(ggpubr)
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library(rstatix)
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# Define UI for application
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ui <- fluidPage(
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#Navbar
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navbarPage("Seguimiento in vivos",
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tabPanel("Diseño",
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sidebarPanel(
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fileInput(inputId = "file_sizes", label = "Hoja de tamaños", multiple = F),
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uiOutput('ncages'),
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uiOutput('ntumors'),
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# selectInput(inputId = "measure_sys", "Sistema de medida", selected = "L-W-D", choices = c("L-W-D","Min-Max","Absorbance")),
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uiOutput('day_vol'),
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uiOutput('lowcut'),
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uiOutput('upcut'),
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uiOutput('goButton'),
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uiOutput('iterations'),
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downloadButton("downloadData", "Descargar Excel")
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),
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mainPanel(
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plotOutput("firstPlot"),
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plotOutput("distPlot"),
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tableOutput("distTable"),
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tableOutput("distTableAll")
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)
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),
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tabPanel("Análisis",
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sidebarPanel(
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fileInput(inputId = "file_analy", label = "Hoja de análisis", multiple = F),
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selectInput(inputId = "vacc", "Experimento de Vacunación", selected = "No", choices = c("Sí","No")),
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uiOutput('cutoffUI'),
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checkboxInput("filter_stats","Filtrar Estadística"),
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checkboxInput("increase_volume","Usar Incremento de Volumen"),
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checkboxInput("operated","Cortar al operar", value = TRUE),
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checkboxInput("dead","Eliminar ratones muertos", value = FALSE),
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downloadButton("downloadVolume", "Descargar Volúmenes")
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),
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mainPanel(
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h3('Ratones'),
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tableOutput('ntable'),
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h3('Cinéticas'),
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plotOutput('cin_group'),
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plotOutput('cin_indiv'),
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plotOutput('survival', height="800px"),
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h3('Estadística'),
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verbatimTextOutput('stats'),
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tableOutput('tab_stats')
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)),
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tabPanel("Exportar",
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sidebarPanel(width=2,
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h3('Seleccionar figura'),
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selectInput("fig_id", "", selected="", choices=c("Cinética Grupo", "Cinética Individual", "Survival")),
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h3('Formato'),
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selectInput("unit_fact", "Factor de unidad", choices = c("0.001","1","1000"), selected="1"),
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sliderInput("width", "Ancho", min=1000, max=20000, step=1000, value=10000),
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sliderInput("height", "Altura", min=1000, max=20000, step=1000, value=6000),
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textInput("colors", label="Colors", value=""),
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textInput("xaxis", label="Etiqueta Eje X", value=""),
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textInput("yaxis", label="Etiqueta Eje Y", value=""),
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sliderInput("errorbar-width", "% Ancho errorbars", min=0.0, max=1, step=0.05, value=0.05),
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sliderInput("line-size", "Tamaño línea", min=0.1, max=3, step=0.1, value=0.5),
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sliderInput("point-size", "Tamaño puntos", min=1, max=10, step=1, value=3),
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sliderInput("font-size", "Tamaño textos", min=5, max=30, step=1, value=11),
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checkboxInput(inputId = "logscale", label="Escala logarítmica eje Y", value=F),
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checkboxInput(inputId = "legend", label = "Mostrar llegenda", value = T),
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selectInput("theme", "Seleccionar Tema", selected="BW", choices=c("BW", "Default", "Classic")),
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downloadButton("downloadPicture", "Exportar")
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),
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mainPanel(
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uiOutput("expPlotUI")
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)
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)
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)
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)
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# Define server logic required to draw a histogram
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server <- function(input, output) {
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# Diseño ------------------------------------------------------------------
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# Diseño
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dades<-reactiveValues()
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dades$taula<-NULL
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dades$groups<-NULL
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dades$sex<-NULL
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dades$db<-NULL
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observe({
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if (!is.null(input$file_sizes)){
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table<-read.xlsx(input$file_sizes$datapath, sheet = 1, check.names = F, sep.names = " ", detectDates = T,cols=1:11)
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if("ID.animal" %in% colnames(table)){
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table<-table %>%
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rename(Animal=`ID.animal`, Side=`ID.tumor`)
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table<-table %>% gather(DayPostInoc, Value, which(!is.na(as.numeric(colnames(table))))) %>%
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relocate(DayPostInoc, .before = Group) %>% spread(DPV, Value) %>%
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rename(Long=Major, Wide=Minor) %>%
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add_column(Date="", .after = "Animal") %>%
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add_column(Weight="", .after="Group") %>%
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add_column(Volume="",Observations="") %>%
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relocate(Side, .after = "Group")
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table$DayPostInoc<-as.numeric(table$DayPostInoc)
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}
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table$Date<-format(table$Date, format="%d/%m/%Y")
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if ("sex" %in% colnames(table)){table<-select(table, -sex)}
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for (i in 1:nrow(table)){
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long<-as.numeric(gsub(",",".",strsplit(as.character(table[i,"Long"]),"+", fixed = T)[[1]]))
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wide<-as.numeric(gsub(",",".",strsplit(as.character(table[i,"Wide"]),"+", fixed = T)[[1]]))
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table[i,"Volume"]<-sum(sapply(1:length(long), function(x) (long[x]*wide[x]*wide[x])*(pi/6)))
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}
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table$Volume<-as.numeric(table$Volume)
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if ("Cage" %in% colnames(table)){
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table$Animal<-paste0(table$Cage, table$Animal)
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table<-table[,-which(colnames(table) == "Cage")]
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}
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dades$taula<-table
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dades$groups<-read.xlsx(input$file_sizes$datapath, sheet = "Groups", colNames=F)[,1]
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if (readxl::excel_sheets(input$file_sizes$datapath) %>% length > 2){
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dades$sex<-read.xlsx(input$file_sizes$datapath, sheet = 3, sep.names = " ")
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}
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}
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})
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output$firstPlot <- renderPlot({
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observeEvent(dades$taula, {})
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if (!is.null(dades$taula)){
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ggplot(dades$taula %>% filter(DayPostInoc == input$day_vol), aes(x="1", y=Volume))+
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geom_hline(yintercept = c(input$lowcut, input$upcut), color="red")+
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geom_quasirandom(width=0.2)
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}
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})
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output$day_vol<-renderUI({
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if (!is.null(dades$taula)){
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selectInput("day_vol", "Día para volúmenes", choices = sort(unique(dades$taula$DayPostInoc)))
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}
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})
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output$iterations<-renderUI({
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if (!is.null(dades$taula)){
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sliderInput("iterations", "Iteraciones", min=100, max=2000, step=100, value=100)
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}
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})
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output$lowcut<-renderUI({
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if (!is.null(dades$taula)){
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taula<-dades$taula %>% filter(DayPostInoc == input$day_vol)
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cut.max<-round(max(taula$Volume, na.rm = T), 2)
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step<-round(max(taula$Volume, na.rm = T)/100, 2)
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sliderInput("lowcut", "Corte inferior", min=0, max=cut.max, step=step, value=0)
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}
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})
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output$upcut<-renderUI({
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if (!is.null(dades$taula)){
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taula<-dades$taula %>% filter(DayPostInoc == input$day_vol)
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cut.max<-round(max(taula$Volume, na.rm = T), 2)+0.01
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step<-round(max(taula$Volume, na.rm = T)/20, 2)
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sliderInput("upcut", "Corte superior", min=0, max=cut.max, step=step, value=cut.max)
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}
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})
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output$goButton<-renderUI({
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if (!is.null(dades$taula)){
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actionButton("goButton", "Selecciona")
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}
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})
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output$ncages<-renderUI({
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if (is.null(dades$taula)){
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sliderInput("ncages", "Cajas", min=1, max=10, value=1)
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}
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})
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output$ntumors<-renderUI({
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if (is.null(dades$taula)){
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selectInput("ntumors", "Tumores por ratón", choices = c(1,2), selected = 2)
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}
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})
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grafic<-eventReactive(input$goButton,{
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df<-dades$taula %>% filter(DayPostInoc == input$day_vol)
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# print(df)
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df<-df[!is.na(df$Volume),]
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up_cuttof<-input$upcut
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low_cuttof<-input$lowcut
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df<-df[df$Volume < up_cuttof & df$Volume >= low_cuttof,]
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if (is.null(dades$sex)){
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df<-add_column(df, sex="undefined")
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}else{
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df<-merge(df, dades$sex)
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}
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# df["Mouse"]<-gsub("[a-zA-Z]", "", df$MouseID)
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s<-shapiro.test(df$Volume)[[2]]
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ngroup<-length(dades$groups)
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df_def<-list()
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for (sex.var in unique(df$sex)){
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df_sex<-df %>% filter(`sex` == sex.var)
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ind.list<-list()
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pval.list<-list()
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lvn.list<-list()
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test.list<-list()
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for (data in 1:input$iterations){
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interr=T
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while(interr == T){
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ind<-sample(rep(dades$groups, each=ceiling(length(unique(df_sex$Animal))/ngroup)), length(unique(df_sex$Animal)))
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df_sex<-merge(df_sex[,c("Animal", "Side","Volume")], data.frame("Animal"=unique(df_sex$Animal), "group"=as.factor(ind),check.names=F))
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# print(df_sex)
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if ((nrow(df_sex)/ngroup) %% 2 == 0){
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interr<-any(table(df_sex$group) < floor(nrow(df_sex)/ngroup) | table(df_sex$group) > ceiling(nrow(df_sex)/ngroup))
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}else{
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# interr<-any(table(df_sex$group) < (floor(nrow(df_sex)/ngroup)-1) | table(df_sex$group) > (ceiling(nrow(df_sex)/ngroup)+1))
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interr<-diff(range(table(ind))) > 1
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}
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}
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ind.list[[data]]<-df_sex[,c("Animal","Side","group","Volume")]
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lvn.list[data]<-leveneTest(Volume ~ group, data = df_sex[,3:4])[[2]][1]
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if (s < 0.05){
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k<-kruskal.test(df_sex$Volume,df_sex$group)
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test.list[data]<-k[[1]][1]
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pval.list[data]<-k[[3]][1]
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}else{
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res.aov<-aov(Volume~group, data=df_sex)
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pval.list[data]<-summary(res.aov)[[1]][[5]][1]
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test.list[data]<-summary(res.aov)[[1]][[4]][1]
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}
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}
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index<-which(unlist(lvn.list) == min(unlist(lvn.list)[which(unlist(pval.list) %in% sort(unlist(pval.list), decreasing = T)[1:20])]))[1]
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# print(df_sex)
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df_def[[sex.var]]<-merge(df_sex %>% select(-group), ind.list[[index]])
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}
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df_def<-do.call(rbind, c(df_def, make.row.names=F))
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# lapply(df_def, function(x) x %>% as_tibble %>% print(n=Inf))
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# df_def<-rbind(df_def[[1]], df_def[[2]], make.row.names=F)
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if ("Group" %in% colnames(df_def)){
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df_def<-df_def %>% select(-"Group")
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}
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df_def<-merge(
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if(!is.null(dades$sex)){merge(dades$taula %>% filter(DayPostInoc == input$day_vol), dades$sex)%>% select(-Group)}else{
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dades$taula %>% filter(DayPostInoc == input$day_vol) %>% add_column(sex="undefined")} %>% select(-Group),
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df_def[,c("Animal", "group")] %>% unique, all=T, by="Animal")
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df_def<-df_def %>% rename(Group=group)
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df_def<-select(df_def, Animal, sex, Date, DayPostInoc, Group, Side, Weight, Long, Wide, Volume, Observations)
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# if("DPV" %in% colnames(df_def)){df_def<-select(df_def, c(`ID animal`, `sex`,`ID tumor`, Volume, Cage, Major, Minor, group))}
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# if("TS-Deep" %in% colnames(df_def)){df_def<-select(df_def, c(`ID animal`, `sex`,`ID tumor`, Volume, Cage, `TS-Deep`,`TS-Length`,`TS-Width`, group))}
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df_def[!paste0(df_def$Animal, df_def$Side) %in% paste0(df$Animal, df$Side),"Group"]<-NA
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dades$db<-df_def
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if (is.null(dades$sex)){
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ggplot(df_def, aes(Group, Volume))+
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geom_boxplot(outlier.alpha = F)+
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geom_jitter(width=0.25)+
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geom_point(stat="summary", color="blue", size=3)+
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theme(axis.text.x = element_text(angle=90, hjust=1, vjust=0.5))
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}else{
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ggarrange(
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ggplot(df_def, aes(Group, Volume))+
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geom_boxplot(outlier.alpha = F)+
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geom_jitter(width=0.25, aes(color=sex))+
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geom_point(stat="summary", color="blue", size=3)+
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theme(axis.text.x = element_text(angle=90, hjust=1, vjust=0.5)),
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# lims(y=c(0,max(df_def$Volume)+10))
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ggarrange(
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ggplot(df_def, aes(sex, Volume))+
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geom_boxplot(outlier.alpha = F)+
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geom_quasirandom(width=0.3),
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ggplot(df_def, aes(Group, fill=sex))+
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geom_bar(stat="count", color="black", position="dodge")+
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guides(fill="none")+
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theme(axis.text.x = element_text(angle=90, hjust=1, vjust=0.5)), ncol = 1, heights = c(0.35, 0.65)),
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nrow = 1, aligh="h", widths = c(0.65, 0.35))
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}
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})
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output$distPlot <- renderPlot({
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observeEvent(dades$taula, {})
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if (!is.null(dades$taula)){
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grafic()
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}
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})
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output$distTable <- renderTable({
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observeEvent(dades$db, {})
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if (!is.null(dades$db)){
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df<-dades$db
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df_sum<-dcast(df, Group~., value.var = "Volume", fun.aggregate = mean, na.rm=T) %>% rename("Mean"=".")
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df_sum["SEM"]<-dcast(df, Group~., value.var = "Volume", fun.aggregate = std.error, na.rm=T) %>% pull(`.`)
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df_sum
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}
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})
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output$distTableAll <- renderTable({
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observeEvent(dades$db, {})
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if (!is.null(dades$db)){
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df<-dades$db
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df %>% arrange(Group)
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}
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})
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output$downloadData <- downloadHandler(
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filename = function() {
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paste("invivo", ".xlsx", sep="")
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},
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content = function(file){
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ncages<-input$ncages
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nrat_cage<-5
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id_tumors<-c("L","R")[1:as.numeric(input$ntumors)]
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# timepoint<-c(7,10,13,16,19,22,25)
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if (!is.null(input$file_sizes)){
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template<-dades$db %>% filter(!is.na(Group)) %>%
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select(Animal, Group) %>% unique()
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dtemplate<-merge(dades$taula %>% select(-Group), template) %>%
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arrange(DayPostInoc, Animal, Side) %>%
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select(Animal, Date, DayPostInoc, Group, Side,
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Weight, Long, Wide, Volume, Observations)
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}else{
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template<-data.frame(
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Cage=rep(LETTERS[1:ncages], each=nrat_cage*as.numeric(input$ntumors)),
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Animal=rep(1:(nrat_cage*ncages), each=as.numeric(input$ntumors)),
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Date="",
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DayPostInoc="",
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Group="",
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Side=rep(id_tumors, nrat_cage*ncages),
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Weight="",
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Long="",
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Wide="",
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Volume="",
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Observations=""
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)
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template<-template %>% mutate(Animal=paste0(Cage,Animal)) %>% select(-Cage)
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dtemplate<-template
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}
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write.xlsx(list("Measures"=dtemplate, "Groups"=NULL,"Sex"=NULL), file)
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}
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)
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# Análisis ----------------------------------------------------------------
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analysis<-reactiveValues()
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analysis$taula<-NULL
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analysis$taula_def<-NULL
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analysis$taula_vol<-NULL
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observe({
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if (!is.null(input$file_analy)){
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table<-read.xlsx(input$file_analy$datapath, sheet = 1, check.names = F, sep.names = " ", detectDates = T,cols=1:11)
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if("ID.animal" %in% colnames(table)){
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table<-table %>%
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rename(Animal=`ID.animal`, Side=`ID.tumor`)
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table<-table %>% gather(DayPostInoc, Value, which(!is.na(as.numeric(colnames(table))))) %>%
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relocate(DayPostInoc, .before = Group) %>% spread(DPV, Value) %>%
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rename(Long=Major, Wide=Minor) %>%
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add_column(Date="", .after = "Animal") %>%
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add_column(Weight="", .after="Group") %>%
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add_column(Volume="",Observations="") %>%
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relocate(Side, .after = "Group")
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table$DayPostInoc<-as.numeric(table$DayPostInoc)
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}
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table$Date<-format(table$Date, format="%d/%m/%Y")
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if ("sex" %in% colnames(table)){table<-select(table, -sex)}
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for (i in 1:nrow(table)){
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long<-as.numeric(gsub(",",".",strsplit(as.character(table[i,"Long"]),"+", fixed = T)[[1]]))
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wide<-as.numeric(gsub(",",".",strsplit(as.character(table[i,"Wide"]),"+", fixed = T)[[1]]))
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table[i,"Volume"]<-sum(sapply(1:length(long), function(x) (long[x]*wide[x]*wide[x])*(pi/6)))
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}
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table$Volume<-as.numeric(table$Volume)
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if ("Cage" %in% colnames(table)){
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table$Animal<-paste0(table$Cage, table$Animal)
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table<-table[,-which(colnames(table) == "Cage")]
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}
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## Autocompletado de grupo
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table_group<-merge(
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table %>% select(Animal, Group) %>% unique() %>% group_by(Animal) %>% count(),
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table %>% select(Animal, Group) %>% unique()
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) %>% filter(!is.na(Group) | Group != "") %>% select(-n)
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table<-merge(
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table %>% select(-Group),
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table_group
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) %>% relocate(Group, .after = DayPostInoc) %>%
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arrange(DayPostInoc, Animal, Side)
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if("Groups" %in% readxl::excel_sheets(input$file_analy$datapath)){
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levels<-read.xlsx(input$file_analy$datapath, sheet = "Groups", colNames=F)[,1]
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print(levels)
|
|
table$Group<-factor(table$Group, levels=levels)
|
|
table<-filter(table, !is.na(Group))
|
|
}else(table$Group<-factor(table$Group))
|
|
print(str(table))
|
|
analysis$taula<-table
|
|
}
|
|
})
|
|
output$cutoffUI<-renderUI({
|
|
if (!is.null(analysis$taula)){
|
|
observeEvent(analysis$taula, {})
|
|
max_val<-max(analysis$taula$Volume, na.rm = T)
|
|
# print(max_val)
|
|
sliderInput("cutoff", "Cutoff para Survival", min=0, max=round(max_val, digits=2), step=round(max_val, digits=2)/200, value=max_val)
|
|
}
|
|
})
|
|
output$ntable<-renderTable({
|
|
if (!is.null(input$file_analy)){
|
|
observeEvent(analysis$taula, {})
|
|
stattest<-"dunn"
|
|
oneside<-""
|
|
|
|
table<-analysis$taula
|
|
table<-table %>% filter(!is.na(Group))
|
|
if (input$increase_volume){
|
|
timepoints<-unique(table$Timepoint)
|
|
table<-table %>% select(-Major, -Minor) %>%
|
|
spread(Timepoint, Volume) %>%
|
|
mutate(across(all_of(timepoints), function(x){(x*100/`0`)-100})) %>%
|
|
gather(Timepoint, Volume, -`ID animal`, -`ID tumor`, -Group) %>%
|
|
mutate(Volume=case_when(Volume < 0 ~ 0, T~Volume))
|
|
}
|
|
table %>% group_by(Group, DayPostInoc, Side) %>% count() %>% spread(DayPostInoc, n)
|
|
}
|
|
})
|
|
|
|
output$cin_group<-renderPlot({
|
|
if (!is.null(input$file_analy) & !is.null(analysis$taula)){
|
|
observeEvent(analysis$taula, {})
|
|
table<-analysis$taula
|
|
|
|
print(table)
|
|
animals<-unique(table$Animal)
|
|
sides<-unique(table$Side)
|
|
groups<-table %>% select(Animal, Group) %>% unique() %>% pull(Group)
|
|
basal<-data.frame(
|
|
Animal=rep(animals, each=length(sides)),
|
|
Date="",
|
|
DayPostInoc=0,
|
|
Group=rep(groups, each=length(sides)),
|
|
Side=rep(sides, length(animals)),
|
|
Weight="",
|
|
Long="",
|
|
Wide="",
|
|
Volume=0,
|
|
Observations=""
|
|
)
|
|
if (!(0 %in% table$DayPostInoc) | sum(table[test$DayPostInoc == 0,"Volume"],na.rm = T) == 0){
|
|
table<-rbind(table, basal)
|
|
}
|
|
|
|
if (input$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))
|
|
deadmice<-filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "+") %>%
|
|
pull(Animal)
|
|
print(deadmice)
|
|
if (input$operated == TRUE & nrow(firstoper) > 0){
|
|
for (i in 1:nrow(firstoper)){
|
|
table<-table %>% filter(DayPostInoc < firstoper$FirstOper[i] | Side != firstoper$Side[i])
|
|
}
|
|
}else{
|
|
if(input$dead == TRUE){
|
|
table<-table %>% filter(!Animal %in% deadmice)
|
|
}
|
|
}
|
|
|
|
ggplot(table, aes(DayPostInoc, Volume, color=Group, group=Group))+
|
|
geom_errorbar(stat="summary", width=0.05)+
|
|
geom_line(stat="summary")+
|
|
geom_point(stat="summary")+
|
|
facet_grid(factor(Side, labels = c("Vaccination", "Rechallenge"))~., scale="free_y")+
|
|
labs(x="Days after tumor inoculation")+
|
|
scale_y_continuous(expand = expansion(mult = c(0,0.05)))+
|
|
scale_x_continuous(expand = expansion(mult = c(0,0.05)), limits = c(0, (round(max(table$DayPostInoc) / 5)+1)*5))+
|
|
theme_bw()
|
|
}else{
|
|
|
|
firstoper<- filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "*") %>%
|
|
pull(DayPostInoc) %>% min(na.rm = T)
|
|
if (firstoper == Inf){firstoper<-c()}
|
|
|
|
if (input$operated == TRUE & length(firstoper) > 0){
|
|
table<-table %>% filter(DayPostInoc < firstoper)
|
|
}else{
|
|
deadmice<-filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "+") %>%
|
|
pull(Animal)
|
|
if(input$dead == TRUE){
|
|
table<-table %>% filter(!Animal %in% deadmice)
|
|
}
|
|
}
|
|
|
|
ggplot(table, aes(DayPostInoc, Volume, color=Group, group=Group))+
|
|
geom_errorbar(stat="summary",width=0.05)+
|
|
geom_line(stat="summary")+
|
|
geom_point(stat="summary")+
|
|
labs(x="Days after tumor challenge")+
|
|
scale_y_continuous(expand = expansion(mult = c(0,0.05)))+
|
|
theme_bw()+
|
|
theme(axis.text.x=element_text(angle=45, hjust=1))
|
|
}
|
|
|
|
}
|
|
})
|
|
output$cin_indiv<-renderPlot({
|
|
if (!is.null(input$file_analy) & !is.null(analysis$taula)){
|
|
observeEvent(analysis$taula, {})
|
|
table<-analysis$taula
|
|
|
|
animals<-unique(table$Animal)
|
|
sides<-unique(table$Side)
|
|
groups<-table %>% select(Animal, Group) %>% unique() %>% pull(Group)
|
|
basal<-data.frame(
|
|
Animal=rep(animals, each=length(sides)),
|
|
Date="",
|
|
DayPostInoc=0,
|
|
Group=rep(groups, each=length(sides)),
|
|
Side=rep(sides, length(animals)),
|
|
Weight="",
|
|
Long="",
|
|
Wide="",
|
|
Volume=0,
|
|
Observations=""
|
|
)
|
|
if (!(0 %in% table$DayPostInoc) | sum(test[table$DayPostInoc == 0,"Volume"],na.rm = T) == 0){
|
|
table<-rbind(table, basal)
|
|
}
|
|
|
|
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 & nrow(firstoper) > 0){
|
|
for (i in 1:nrow(firstoper)){
|
|
table<-table %>% filter(DayPostInoc < firstoper$FirstOper[i] | Side != firstoper$Side[i])
|
|
}
|
|
}else{
|
|
if(input$dead == TRUE){
|
|
deadmice<-filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "+") %>%
|
|
pull(Animal)
|
|
table<-table %>% filter(!Animal %in% deadmice)
|
|
}
|
|
}
|
|
ggplot(table, aes(DayPostInoc, Volume, color=Group, group=Animal))+
|
|
# geom_errorbar(stat="summary", width=0.05)+
|
|
geom_line()+
|
|
geom_point()+
|
|
scale_y_continuous(expand = expansion(mult = c(0,0.05)))+
|
|
scale_x_continuous(expand = expansion(mult = c(0,0.05)), limits = c(0, (round(max(table$DayPostInoc) / 5)+1)*5))+
|
|
facet_grid(factor(Side, labels = c("Vaccination", "Rechallenge"))~Group, scale="free_y")+
|
|
labs(x="Days after tumor inoculation")+
|
|
theme_bw()
|
|
}else{
|
|
firstoper<- filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "*") %>%
|
|
pull(DayPostInoc) %>% min(na.rm = T)
|
|
if (firstoper == Inf){firstoper<-c()}
|
|
|
|
if (input$operated == TRUE & length(firstoper) > 0){
|
|
table<-table %>% filter(DayPostInoc < firstoper)
|
|
}else{
|
|
deadmice<-filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "+") %>%
|
|
pull(Animal)
|
|
if(input$dead == TRUE){
|
|
table<-table %>% filter(!Animal %in% deadmice)
|
|
}
|
|
}
|
|
ggplot(table, aes(DayPostInoc, Volume, color=Group, group=paste0(Animal, Side)))+
|
|
# geom_errorbar(stat="summary", width=0.05)+
|
|
geom_line()+
|
|
geom_point()+
|
|
scale_y_continuous(expand = expansion(mult = c(0,0.05)))+
|
|
# scale_x_continuous(expand = expansion(mult = c(0,0.05)), limits = c(0, (round(max(as.numeric(as.character(table$Timepoint))) / 5)+1)*5))+
|
|
facet_wrap(.~Group)+
|
|
labs(x="Days after tumor inoculation")+
|
|
theme_bw()+
|
|
theme(axis.text.x=element_text(angle=45, hjust=1))
|
|
}
|
|
}
|
|
})
|
|
|
|
output$survival<-renderPlot({
|
|
if (!is.null(input$file_analy) & !is.null(analysis$taula)){
|
|
observeEvent(analysis$taula, {})
|
|
table<-analysis$taula
|
|
if (input$vacc == "Sí"){
|
|
firstoper<- filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "*") %>%
|
|
select(DayPostInoc, Side) %>% unique() %>%
|
|
if (firstoper == Inf){firstoper<-c()}
|
|
|
|
if (input$operated == TRUE & length(firstoper) > 0){
|
|
for (i in 1:nrow(firstoper)){
|
|
table<-table %>% filter(DayPostInoc < firstoper$FirstOper[i] | Side != firstoper$Side[i])
|
|
}
|
|
}else{
|
|
if(input$dead == TRUE){
|
|
deadmice<-filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "+") %>%
|
|
pull(Animal)
|
|
table<-table %>% filter(!Animal %in% deadmice)
|
|
}
|
|
}
|
|
g<-list()
|
|
for (side in c("L","R")){
|
|
tableR<-filter(table, Side == side) %>% filter(!is.na(Volume))
|
|
endtime<-dcast(tableR %>% filter(Volume < input$cutoff), 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$cutoff
|
|
table_tumor<<-endtime
|
|
|
|
g[side]<-ggsurvplot(survfit(Surv(end, Dead) ~ Group, data=table_tumor),
|
|
pval = T, pval.method = T,
|
|
title = side,
|
|
# legend.labs = paste(c("< median", ">= median"), "MICA"),
|
|
ggtheme=theme_classic(base_size=15)
|
|
# conf.int = TRUE,
|
|
# Add risk table
|
|
# risk.table = TRUE,
|
|
# tables.height = 0.2,
|
|
# tables.theme = theme_cleantable(),
|
|
|
|
# Color palettes. Use custom color: c("#E7B800", "#2E9FDF"),
|
|
# or brewer color (e.g.: "Dark2"), or ggsci color (e.g.: "jco")
|
|
# palette = c("#E7B800", "#2E9FDF")
|
|
)
|
|
}
|
|
do.call(grid.arrange, g)
|
|
|
|
}else{
|
|
firstoper<- filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "*") %>%
|
|
pull(DayPostInoc) %>% min(na.rm = T)
|
|
print(firstoper)
|
|
|
|
if (input$operated == TRUE & nrow(firstoper) > 0){
|
|
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(end, Dead) ~ 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$stats<-renderPrint({
|
|
stattest<-"dunn"
|
|
oneside<-""
|
|
if (!is.null(input$file_analy) & !is.null(analysis$taula)){
|
|
observeEvent(analysis$taula, {})
|
|
table<-analysis$taula
|
|
if (input$vacc == "No"){
|
|
table<-filter(table, !is.na(Volume))
|
|
summary(aov(Volume~Group+DayPostInoc+Error(Animal+Side), data=table))
|
|
}else{
|
|
for (side in c("L","R")){
|
|
tableR<-filter(table, Side == side) %>% filter(!is.na(Volume))
|
|
if (length(unique(tableR$Volume)) > 1 & length(unique(tableR$DayPostInoc)) > 1){
|
|
print(paste0("Side: ",side))
|
|
print(summary(aov(Volume~Group+DayPostInoc+Error(Animal), data=tableR)))
|
|
}
|
|
}
|
|
}
|
|
}
|
|
})
|
|
output$tab_stats<-renderTable({
|
|
stattest<-"dunn"
|
|
oneside<-""
|
|
if (!is.null(input$file_analy) & !is.null(analysis$taula)){
|
|
table<-analysis$taula
|
|
table_stats<-list()
|
|
if (input$vacc == "No"){
|
|
table<-table%>%filter(!is.na(Volume))
|
|
if (length(unique(table$Volume)) > 1){
|
|
table_stats<-multi_stats(table, "Volume", "DayPostInoc", "Group", stat.test=stattest)
|
|
}
|
|
table_kw<-as.data.frame(matrix(nrow=0, ncol=2))
|
|
for (point in unique(table$DayPostInoc)){
|
|
len_group<-length(unique(table %>% filter(DayPostInoc == point) %>% pull(Group)))
|
|
if (len_group > 1){
|
|
table_kw<-rbind(table_kw, data.frame(point,kruskal.test(table %>% filter(DayPostInoc == point) %>% pull(Volume), table %>% filter(DayPostInoc == point) %>% pull(Group))[3][[1]]))
|
|
}
|
|
}
|
|
colnames(table_kw)<-c("DayPostInoc", "KW-p.val")
|
|
table_stats<-merge(table_stats, table_kw)
|
|
|
|
}else{
|
|
for (side in c("L","R")){
|
|
tableR<-filter(table, Side == side) %>% filter(!is.na(Volume))
|
|
if (length(unique(tableR$Volume)) > 1){
|
|
table_stats[[side]]<-multi_stats(tableR, "Volume", "DayPostInoc", "Group", stat.test=stattest)
|
|
}
|
|
table_kw<-as.data.frame(matrix(nrow=0, ncol=2))
|
|
for (point in unique(tableR$DayPostInoc)){
|
|
len_group<-length(unique(tableR %>% filter(DayPostInoc == point) %>% pull(Group)))
|
|
if (len_group > 1){
|
|
table_kw<-rbind(table_kw, data.frame(point,kruskal.test(tableR %>% filter(DayPostInoc == point) %>% pull(Volume), tableR %>% filter(DayPostInoc == point) %>% pull(Group))[3][[1]]))
|
|
}
|
|
}
|
|
colnames(table_kw)<-c("DayPostInoc", "KW-p.val")
|
|
table_stats[[side]]<-merge(table_stats[[side]], table_kw)
|
|
}
|
|
}
|
|
table_stats_def<-bind_rows(table_stats, .id = "Side")
|
|
if (input$filter_stats == T){
|
|
table_stats_def %>% filter(p.adj < 0.05)
|
|
}else{
|
|
table_stats_def
|
|
}
|
|
}
|
|
})
|
|
|
|
output$downloadVolume <- downloadHandler(
|
|
|
|
filename = function() {
|
|
paste("invivo-vols", ".xlsx", sep="")
|
|
},
|
|
content = function(file){
|
|
dtemplate<-analysis$taula
|
|
# print(str(dtemplate))
|
|
write.xlsx(dtemplate,file, )
|
|
}
|
|
)
|
|
|
|
|
|
# Exportar ----------------------------------------------------------------
|
|
|
|
output$expPlotUI<- renderUI({
|
|
observeEvent(analysis$taula, {})
|
|
if (!is.null(input$file_analy) & !is.null(analysis$taula)){
|
|
plotOutput("expPlot", width=paste0(input$width/10,"px"), height = paste0(input$height/10, "px"))
|
|
}
|
|
})
|
|
|
|
output$expPlot <- renderPlot({
|
|
observeEvent(analysis$taula, {})
|
|
if (!is.null(input$file_analy) & !is.null(analysis$taula)){
|
|
table<-analysis$taula
|
|
table$Volume<-table$Volume*as.numeric(input$unit_fact)
|
|
animals<-unique(table$Animal)
|
|
sides<-unique(table$Side)
|
|
groups<-table %>% select(Animal, Group) %>% unique() %>% pull(Group)
|
|
basal<-data.frame(
|
|
Animal=rep(animals, each=length(sides)),
|
|
Date="",
|
|
DayPostInoc=0,
|
|
Group=rep(groups, each=length(sides)),
|
|
Side=rep(sides, length(animals)),
|
|
Weight="",
|
|
Long="",
|
|
Wide="",
|
|
Volume=0,
|
|
Observations=""
|
|
)
|
|
table<-rbind(table, basal)
|
|
if (input$fig_id %in% c("Cinética Grupo", "Cinética Individual")){
|
|
if (input$fig_id == "Cinética Grupo"){
|
|
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$dead == TRUE){
|
|
deadmice<-filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "+") %>%
|
|
pull(Animal)
|
|
table<-table %>% filter(!Animal %in% deadmice)
|
|
}
|
|
}
|
|
std<-function(x, na.rm=T){sd(x, na.rm=na.rm)/sqrt(length(x))}
|
|
errbar<-table %>% group_by(Group,Side,DayPostInoc) %>%
|
|
summarise(mean=mean(Volume, na.rm=T), std=std(Volume)) %>%
|
|
mutate(Timepoint2=as.numeric(as.character(DayPostInoc))) %>%
|
|
mutate(x=Timepoint2-input$`errorbar-width`, xend=Timepoint2+input$`errorbar-width`)
|
|
|
|
g<-ggplot(table, aes(DayPostInoc, Volume, color=Group, group=Group))+
|
|
geom_errorbar(stat="summary", width=0.05)+
|
|
geom_line(stat="summary")+
|
|
geom_point(stat="summary")+
|
|
facet_grid(factor(Side, labels = c("Vaccination", "Rechallenge"))~., scale="free_y")+
|
|
labs(x="Days after tumor inoculation")+
|
|
scale_y_continuous(expand = expansion(mult = c(0,0.05)))+
|
|
scale_x_continuous(expand = expansion(mult = c(0,0.05)), limits = c(0, (round(max(table$DayPostInoc) / 5)+1)*5))+
|
|
theme_bw()+
|
|
geom_segment(data=errbar, aes(y=mean, yend=mean+std, x=Timepoint2, xend=Timepoint2))+
|
|
geom_segment(data=errbar, aes(y=mean+std, yend=mean+std,
|
|
x=x,xend=xend))
|
|
}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)
|
|
}
|
|
}
|
|
|
|
std<-function(x, na.rm=T){sd(x, na.rm=na.rm)/sqrt(length(x))}
|
|
errbar<-table %>% group_by(Group, DayPostInoc) %>%
|
|
summarise(mean=mean(Volume, na.rm=T), std=std(Volume)) %>%
|
|
mutate(Timepoint2=as.numeric(as.character(DayPostInoc))) %>%
|
|
mutate(x=Timepoint2-input$`errorbar-width`, xend=Timepoint2+input$`errorbar-width`)
|
|
|
|
g<-ggplot(table, aes(DayPostInoc, Volume, color=Group, group=Group))+
|
|
geom_errorbar(stat="summary",width=0.05)+
|
|
geom_line(stat="summary")+
|
|
geom_point(stat="summary")+
|
|
labs(x="Days after tumor challenge")+
|
|
scale_y_continuous(expand = expansion(mult = c(0,0.05)))+
|
|
theme_bw()+
|
|
theme(axis.text.x=element_text(angle=45, hjust=1))+
|
|
geom_segment(data=errbar, aes(y=mean, yend=mean+std, x=Timepoint2, xend=Timepoint2))+
|
|
geom_segment(data=errbar, aes(y=mean+std, yend=mean+std,
|
|
x=x,xend=xend))
|
|
}
|
|
}
|
|
if (input$fig_id == "Cinética Individual"){
|
|
if (input$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<-ggplot(table, aes(as.numeric(as.character(DayPostInoc)), Volume, color=Group, group=Animal))+
|
|
scale_x_continuous(expand = expansion(mult = c(0,0.0)),
|
|
breaks=sort(unique(as.numeric(as.character(table$DayPostInoc)))),
|
|
limits = c(0, (round(max(as.numeric(as.character(table$DayPostInoc))) / 5)+1)*5))+
|
|
facet_grid(factor(Side, labels = c("Vaccination", "Rechallenge"))~Group, scale="free_y")+
|
|
theme_bw()
|
|
}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)
|
|
}
|
|
}
|
|
|
|
g<-ggplot(table, aes(as.numeric(as.character(DayPostInoc)), Volume, color=Group, group=Animal))+
|
|
scale_x_continuous(expand = expansion(mult = c(0,0.0)),
|
|
breaks=sort(unique(as.numeric(as.character(table$DayPostInoc)))),
|
|
limits = c(0,max(as.numeric(as.character(table$DayPostInoc)))*1.1))+
|
|
facet_wrap(.~Group)+
|
|
theme_bw()
|
|
}
|
|
}
|
|
|
|
g<-g+
|
|
# geom_errorbar(stat="summary", width=input$`errorbar-width`)+
|
|
geom_line(stat="summary", size=input$`line-size`)+
|
|
geom_point(stat="summary", size=input$`point-size`)+
|
|
labs(x="Days after tumor challenge")+
|
|
scale_y_continuous(expand = expansion(mult = c(0,0.05)))
|
|
|
|
if (input$theme == "BW"){
|
|
g<-g+theme_bw(base_size = input$`font-size`)
|
|
}
|
|
if (input$xaxis != ""){
|
|
g<-g+xlab(input$xaxis)
|
|
}
|
|
if (input$yaxis != ""){
|
|
g<-g+ylab(input$yaxis)
|
|
}
|
|
if (input$theme == "Classic"){
|
|
g<-g+theme_classic(base_size = input$`font-size`)
|
|
}
|
|
if (input$theme == "Default"){
|
|
g<-g+theme_gray(base_size = input$`font-size`)
|
|
}
|
|
# g<-g+theme(axis.text.x=element_text(angle=45, hjust=1))
|
|
if (input$legend == F){
|
|
g<-g+guides(color=FALSE, fill=FALSE)
|
|
}
|
|
if (input$colors != ""){
|
|
v_col<-strsplit(input$colors, ",")[[1]]
|
|
g<-g+scale_color_manual(values=v_col)+
|
|
scale_fill_manual(values=v_col)
|
|
}
|
|
if (input$logscale == T){
|
|
g<-g+scale_y_log10()
|
|
}
|
|
}else{
|
|
gg_color_hue <- function(n, l=65) {
|
|
hues <- seq(15, 375, length=n+1)
|
|
hcl(h=hues, l=l, c=100)[1:n]
|
|
}
|
|
|
|
if (input$vacc == "Sí"){
|
|
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")){
|
|
tableR<-filter(table, Side == side) %>% filter(!is.na(Volume))
|
|
endtime<-dcast(tableR %>% filter(Volume < (input$cutoff*as.numeric(input$unit_fact))), 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$cutoff*as.numeric(input$unit_fact))
|
|
table_tumor<-endtime
|
|
if (input$colors != ""){
|
|
col<-strsplit(input$colors, ",")[[1]]
|
|
}else{
|
|
col<-gg_color_hue(length(unique(endtime$Group)))
|
|
}
|
|
table_tumor$Group<-factor(table_tumor$Group, levels = levels(analysis$taula$Group))
|
|
g[[count]]<-ggsurvplot(survfit(Surv(end, Dead) ~ Group, data=table_tumor),
|
|
pval = T, pval.method = T,
|
|
title = side,
|
|
ggtheme=theme_classic(base_size=input$`font-size`),
|
|
palette = col
|
|
)
|
|
count<-count+1
|
|
}
|
|
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))
|
|
table_tumor<-endtime
|
|
if (input$colors != ""){
|
|
col<-strsplit(input$colors, ",")[[1]]
|
|
}else{
|
|
col<-gg_color_hue(length(unique(table_tumor$Group)))
|
|
}
|
|
table_tumor$Group<-factor(table_tumor$Group, levels = levels(analysis$taula$Group))
|
|
g<-ggsurvplot(survfit(Surv(end, Dead) ~ Group, data=table_tumor),
|
|
pval = T, pval.method = T,
|
|
# ggtheme=theme_classic(base_size=input$`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$downloadPicture <- downloadHandler(
|
|
filename = function() {
|
|
paste("Figura", ".zip", sep="")
|
|
},
|
|
content = function(file){
|
|
# tempReport <- file.path(tempdir(), "elispots.Rmd")
|
|
# file.copy("elispots.Rmd", tempReport, overwrite = TRUE)
|
|
png("invivo.png", width = input$width, height=input$height, units = "px", res=720)
|
|
if (input$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()
|
|
if (input$fig_id == "Survival"){
|
|
if (input$vacc == "Sí"){
|
|
invivo.plot<-arrange_ggsurvplots(dades$plot, nrow=2, ncol=1)
|
|
}else{
|
|
invivo.plot<-arrange_ggsurvplots(list(dades$plot), ncol=1)
|
|
}
|
|
}else{invivo.plot<-dades$plot}
|
|
save(invivo.plot, file="invivoplot.RObject")
|
|
zip(file,
|
|
c("invivo.png", "invivoplot.RObject")
|
|
)
|
|
})
|
|
|
|
|
|
}
|
|
|
|
# Run the application
|
|
shinyApp(ui = ui, server = server)
|