如何使用soverminer :: ggforest绘制彩色图片？

Question

我想知道如何使用soverminer :: ggforest绘制彩色图片。 目前，默认值是黑色和白色。我已经看到了详细的参数，没有颜色主题的选项，只能更改基础代码。我是新手，请帮助我。只要看起来不错，最好选择一些适合出版的颜色。感谢您的帮助

train_ggforest＆lt; -ggforest（model = multi_variate_cox，data = train_tpm，main ='候选基因的危险比率'））

multi_variate_cox = surch（未来，fustat）〜a +b +c，data = train_tpm）

Answer 1

答案是在评论中
学习编程就像学习英语。 （来自母语不是英语的大学生）

ggforest2 <-
  function (model,
            data = NULL,
            main = "Hazard ratio",
            cpositions = c(0.02,
                           0.22, 0.4),
            fontsize = 0.7,
            refLabel = "reference",
            noDigits = 2)
  {
    conf.high <- conf.low <- estimate <- NULL
    stopifnot(inherits(model, "coxph"))
    data <- .get_data(model, data = data)
    terms <- attr(model$terms, "dataClasses")[-1]
    coef <- as.data.frame(tidy(model, conf.int = TRUE))
    gmodel <- glance(model)
    allTerms <- lapply(seq_along(terms), function(i) {
      var <- names(terms)[i]
      if (terms[i] %in% c("factor", "character")) {
        adf <- as.data.frame(table(data[, var]))
        cbind(var = var, adf, pos = 1:nrow(adf))
      }
      else if (terms[i] == "numeric") {
        data.frame(
          var = var,
          Var1 = "",
          Freq = nrow(data),
          pos = 1
        )
      }
      else {
        vars = grep(paste0("^", var, "*."), coef$term, value = TRUE)
        data.frame(
          var = vars,
          Var1 = "",
          Freq = nrow(data),
          pos = seq_along(vars)
        )
      }
    })
    allTermsDF <- do.call(rbind, allTerms)
    colnames(allTermsDF) <- c("var", "level", "N", "pos")
    inds <- apply(allTermsDF[, 1:2], 1, paste0, collapse = "")
    rownames(coef) <- gsub(coef$term, pattern = "`", replacement = "")
    toShow <- cbind(allTermsDF, coef[inds,])[, c("var",
                                                 "level",
                                                 "N",
                                                 "p.value",
                                                 "estimate",
                                                 "conf.low",
                                                 "conf.high",
                                                 "pos")]
    toShowExp <- toShow[, 5:7]
    toShowExp[is.na(toShowExp)] <- 0
    toShowExp <- format(exp(toShowExp), digits = noDigits)
    toShowExpClean <- data.frame(toShow, pvalue = signif(toShow[,
                                                                4], noDigits + 1), toShowExp)
    toShowExpClean$stars <- paste0(
      round(toShowExpClean$p.value,
            noDigits + 1),
      " ",
      ifelse(toShowExpClean$p.value < 0.05,
             "*", ""),
      ifelse(toShowExpClean$p.value < 0.01, "*",
             ""),
      ifelse(toShowExpClean$p.value < 0.001, "*", "")
    )
    toShowExpClean$ci <- paste0("(", toShowExpClean[, "conf.low.1"],
                                " - ", toShowExpClean[, "conf.high.1"], ")")
    toShowExpClean$estimate.1[is.na(toShowExpClean$estimate)] = refLabel
    toShowExpClean$stars[which(toShowExpClean$p.value < 0.001)] = "<0.001 ***"
    toShowExpClean$stars[is.na(toShowExpClean$estimate)] = ""
    toShowExpClean$ci[is.na(toShowExpClean$estimate)] = ""
    toShowExpClean$estimate[is.na(toShowExpClean$estimate)] = 0
    toShowExpClean$var = as.character(toShowExpClean$var)
    toShowExpClean$var[duplicated(toShowExpClean$var)] = ""
    toShowExpClean$N <- paste0("(N=", toShowExpClean$N, ")")
    toShowExpClean <- toShowExpClean[nrow(toShowExpClean):1,]
    rangeb <-
      range(toShowExpClean$conf.low, toShowExpClean$conf.high,
            na.rm = TRUE)
    breaks <- axisTicks(rangeb / 2, log = TRUE, nint = 7)
    rangeplot <- rangeb
    rangeplot[1] <- rangeplot[1] - diff(rangeb)
    rangeplot[2] <- rangeplot[2] + 0.15 * diff(rangeb)
    width <- diff(rangeplot)
    y_variable <- rangeplot[1] + cpositions[1] * width
    y_nlevel <- rangeplot[1] + cpositions[2] * width
    y_cistring <- rangeplot[1] + cpositions[3] * width
    y_stars <- rangeb[2]
    x_annotate <- seq_len(nrow(toShowExpClean))
    annot_size_mm <-
      fontsize * as.numeric(convertX(unit(theme_get()$text$size,
                                          "pt"), "mm"))
    p <- ggplot(toShowExpClean, aes(seq_along(var), exp(estimate))) +
      geom_rect(
        aes(
          xmin = seq_along(var) - 0.5,
          xmax = seq_along(var) +
            0.5,
          ymin = exp(rangeplot[1]),
          ymax = exp(rangeplot[2]),
          fill = ordered(seq_along(var) %% 2 + 1)
        )
      ) + 
      ##Here are two staggered body color combinations
      scale_fill_manual(values = c("#ecf0fb","#c6d4f3"), guide = "none") +
      #This is the color of the squares ( risk value )
      geom_point(pch = 15,size = 3,color="#fc7748") + 
      #This is the color of the errorbar 
      geom_errorbar(aes(ymin = exp(conf.low), ymax = exp(conf.high)),width = 0.15,color="#e889bd" ) + 
      scale_colour_distiller(palette = "Spectral")+
      #This is the color setting for the risk demarcation line (set to 1 here)
      geom_hline(yintercept = 1, linetype = 3,color ="red", size = 1.5) +
      coord_flip(ylim = exp(rangeplot)) + ggtitle(main) + scale_y_log10(
        name = "",
        labels = sprintf("%g", breaks),
        expand = c(0.02, 0.02),
        breaks = breaks
      ) + theme_light() + theme(
        panel.grid.minor.y = element_blank(),
        panel.grid.minor.x = element_blank(),
        panel.grid.major.y = element_blank(),
        legend.position = "none",
        panel.border = element_blank(),
        axis.title.y = element_blank(),
        axis.text.y = element_blank(),
        axis.ticks.y = element_blank(),
        plot.title = element_text(hjust = 0.5)
      ) +
      xlab("") + annotate(
        geom = "text",
        x = x_annotate,
        y = exp(y_variable),
        label = toShowExpClean$var,
        fontface = "bold",
        hjust = 0,
        size = annot_size_mm
      ) + annotate(
        geom = "text",
        x = x_annotate,
        y = exp(y_nlevel),
        hjust = 0,
        label = toShowExpClean$level,
        vjust = -0.1,
        size = annot_size_mm
      ) + annotate(
        geom = "text",
        x = x_annotate,
        y = exp(y_nlevel),
        label = toShowExpClean$N,
        fontface = "italic",
        hjust = 0,
        vjust = ifelse(toShowExpClean$level ==
                         "", 0.5, 1.1),
        size = annot_size_mm
      ) + annotate(
        geom = "text",
        x = x_annotate,
        y = exp(y_cistring),
        label = toShowExpClean$estimate.1,
        size = annot_size_mm,
        vjust = ifelse(toShowExpClean$estimate.1 ==
                         "reference", 0.5,-0.1)
      ) + annotate(
        geom = "text",
        x = x_annotate,
        y = exp(y_cistring),
        label = toShowExpClean$ci,
        size = annot_size_mm,
        vjust = 1.1,
        fontface = "italic"
      ) +
      annotate(
        geom = "text",
        x = x_annotate,
        y = exp(y_stars),
        label = toShowExpClean$stars,
        size = annot_size_mm,
        hjust = -0.2,
        fontface = "italic"
      ) + annotate(
        geom = "text",
        x = 0.5,
        y = exp(y_variable),
        label = paste0(
          "# Events: ",
          gmodel$nevent,
          "; Global p-value (Log-Rank): ",
          format.pval(gmodel$p.value.log,
                      eps = ".001"),
          " \nAIC: ",
          round(gmodel$AIC,
                2),
          "; Concordance Index: ",
          round(gmodel$concordance,
                2)
        ),
        size = annot_size_mm,
        hjust = 0,
        vjust = 1.2,
        fontface = "italic"
      ) +theme(text = element_text(family = "Times")) 
    gt <- ggplot_gtable(ggplot_build(p))
    gt$layout$clip[gt$layout$name == "panel"] <- "off"
    ggpubr::as_ggplot(gt)
  }