server.R

library(shiny)
library(survminer)
library(survival)
library(readxl)
library(purrr)
library(tidyr)
library(dplyr)
library(readr)

shinyServer(function(input, output) {
    v <- reactiveValues(data = NULL)
    observeEvent(input$Run, {
        v$data <- read_delim(file = input$file5, delim = "\t") %>%
            dplyr::mutate(across(everything(), ~ replace_na(.x, 0)))
    })

    NCOL <- reactive({
        ncol(v$data)
    })
    file3 <- reactive({
        purrr::map_df(2:NCOL(), ~ tibble(time = rep(dplyr::pull(v$data, 1), dplyr::pull(v$data, .x)), event = 1, group = names(v$data)[.x]))
    })
    nms <- reactive({
        names(v$data)[-1] %>% as.vector()
    })

    table1 <- reactive({
        FormatPv <- function(i) {
            c <- file3() %>%
                dplyr::filter(group == nms()[1] | group == nms()[i]) %>%
                surv_fit(Surv(time, event) ~ group, data = .) %>%
                surv_pvalue(.) %>%
                dplyr::pull(2) %>%
                ROUND(3)
            if (c < 0.0001) {
                c <- "< 0.0001"
            }
            return(as.character(c))
        }
        ref <- file3() %>%
            dplyr::filter(group == names(v$data)[2]) %>%
            dplyr::pull(1) %>%
            mean()
        d <- file3() %>%
            dplyr::group_by(group) %>%
            dplyr::mutate(group = factor(group, levels = nms())) %>%
            summarise(
                meanse = paste0(ROUND(mean(time), 3), "±", ROUND(SE(time), 3)),
                PLC = ROUND((mean(time) / ref - 1) * 100, 3), N = n()
            ) %>%
            dplyr::mutate(pv = c("", map_chr(2:(NCOL() - 1), FormatPv)), .before = "PLC")
        d[[4]][1] <- ""
        d
    })
    plot1 <- reactive({
        p1 <- ggsurvplot(surv_fit(Surv(time, event)~group, data = file3()),
            axes.offset = F,
            xlim = c(0, ceiling(max(dplyr::pull(file3(),1))/5)*5+1),
            xlab = expression("Days at 20" ~ degree * C),
            ylab = "Fraction survival",
            break.x.by = 10, # 设置x轴刻度间距
            break.y.by = .2, # 设置y轴刻度间距
            legend = "none",
            size = 1, # line size,
            pval.size = 3,
            palette = c("black", "red", "green", "brown", "blue", "pink", "purple","salmon"), # line colours
            pval = ifelse(NCOL() > 3, F, T)
        )

        p1$plot <- p1$plot %+%
            theme(
                axis.title.x = element_text(size = 10),
                axis.title.y = element_text(size = 10),
                axis.text.x = element_text(size = 8),
                axis.text.y = element_text(size = 8),
                # plot.margin = margin(.5,.5,.5,.5,unit = "cm"),
                axis.line = element_line(size = .5),
                # axis.ticks = element_text(size = 1),
                axis.ticks.length = unit(.1, "cm"),
                text=element_text("sans")
            )
        p1$plot
    })
    # main output
    output$table1 <- renderTable(
        {
            if (is.null(v$data)) {
                return()
            }
            table1()
        },
        align = "c"
    )
    output$plot1 <- renderPlot({
        if (is.null(v$data)) {
            return()
        }
        plot1()
    })
    # Download
    output$downspss <- downloadHandler(
        filename = function() {
            paste0(nms()[1], ".spss.txt")
        },
        content = function(file) {
            write_delim(file3(), file, delim = "\t")
        }
    )
    output$downtable <- downloadHandler(
        filename = function() {
            paste0(nms()[1], ".txt")
        },
        content = function(file) {
            write_delim(table1(), file, delim = "\t")
        }
    )
    output$downplot <- downloadHandler(
        filename = function() {
            paste0(nms()[1], ".pdf")
        },
        content = function(file) {
          ggsave(plot=plot1(),file,width = 50,height = 50,units="mm")
        }
    )
})