1. 使用
包绘制森林图
1.1 基本用法
# 安装并加载所需的R包
# install.packages("devtools")
# devtools::install_github("NightingaleHealth/ggforestplot")
# install.packages("tidyverse")
library(ggforestplot)
library(tidyverse)
# 载入示例数据，并过滤示例前30个生物标志物与BMI的关联
df <-
ggforestplot::df_linear_associations %>%
filter(
trait == "BMI", # Nightingale血清生物标志物的名称，有BMI, log(HOMA-IR) 或 fasting glucose
dplyr::row_number() <= 30
)
# 绘制简单的森林图
ggforestplot::forestplot(
df = df,
name = name, # Nightingale血清生物标志物的名称
estimate = beta, # 回归系数
se = se, # 标准偏差
pvalue = pvalue,
psignif = 0.002, # 假设共同的显着性阈值𝛼=0.05，30个测试是独立的，每个单独假设的Bonferroni校正是𝛼=0.05/30≈0.002，不显著的点显示为空心
xlab = "1-SD increment in BMI\nper 1-SD increment in biomarker concentration", # 添加x轴标签
title = "Associations of blood biomarkers to BMI" # 添加标题
)
forestplot-1
1.2 比较多个特征
# 提取生物标志物名称
selected_bmrs <- df %>% pull(name)
# 过滤上述生物标志物和所有三个特征的演示数据集:
# BMI, HOMA-IR and fasting glucose
df_compare_traits <-
ggforestplot::df_linear_associations %>%
filter(name %in% selected_bmrs) %>%
# 将类设置为因子以设置显示顺序.
mutate(
trait = factor(
trait,
levels = c("BMI", "HOMA-IR", "Fasting glucose")
)
)
# 绘图
ggforestplot::forestplot(
df = df_compare_traits,
estimate = beta,
pvalue = pvalue,
psignif = 0.002,
xlab = "1-SD increment in cardiometabolic trait\nper 1-SD increment in biomarker concentration",
title = "Biomarker associations to metabolic traits",
colour = trait
)
forestplot-2
1.3 对生物标志物进行分组
# Install and attach the ggforce library
# install.packages("ggforce")
library(ggforce)
# 过滤包含组的 df_NG_biomarker_metadata，仅针对正在讨论的 30 种生物标志物
df_grouping <-
df_NG_biomarker_metadata %>%
filter(name %in% df_compare_traits$name)
# 加入关联数据框 df_compare_traits 与组数据
df_compare_traits_groups <-
df_compare_traits %>%
dplyr::right_join(., df_grouping, by = "name") %>%
dplyr::mutate(
group = factor(.data$group, levels = unique(.data$group))
)
# 绘图
forestplot(
df = df_compare_traits_groups,
estimate = beta,
pvalue = pvalue,
psignif = 0.002,
xlab = "1-SD increment in cardiometabolic trait\nper 1-SD increment in biomarker concentration",
colour = trait
) +
ggforce::facet_col(
facets = ~group,
scales = "free_y",
space = "free"
)
forestplot-3
2. 使用
包绘制森林图
2.1 基本用法
# 安装并加载所需的R包
# install.packages("forestploter")
# install.packages("devtools")
# devtools::install_github("adayim/forestploter")
dt <- read.csv(system.file("extdata", "example_data.csv", package = "forestploter"))
# 如果placebo列中有数字，则缩进形成子列
dt$Subgroup <- ifelse(is.na(dt$Placebo),
dt$Subgroup,
paste0(" ", dt$Subgroup))
# 将NA值变为空白
dt$Treatment <- ifelse(is.na(dt$Treatment), "", dt$Treatment)
dt$Placebo <- ifelse(is.na(dt$Placebo), "", dt$Placebo)
dt$se <- (log(dt$hi) - log(dt$est))/1.96
# 添加空白列以显示 CI
# 用空格调整列宽
dt$` ` <- paste(rep(" ", 20), collapse = " ")
# 创建要显示的置信区间列，"%.2f"意为保留小数点后两位精度
dt$`HR (95% CI)` <- ifelse(is.na(dt$se), "",
sprintf("%.2f (%.2f to %.2f)",
dt$est, dt$low, dt$hi))
# 定义简单的主题
tm <- forest_theme(base_size = 10,
refline_col = "red",
arrow_type = "closed",
footnote_col = "blue")
p <- forest(dt[,c(1:3, 20:21)],
est = dt$est,
lower = dt$low,
upper = dt$hi,
sizes = dt$se,
ci_column = 4,
ref_line = 1,
arrow_lab = c("Placebo Better", "Treatment Better"),
xlim = c(0, 4),
ticks_at = c(0.5, 1, 2, 3),
footnote = "This is the demo data. Please feel free to change\nanything you want.",
theme = tm)
# 绘图
plot(p)
forestploter-1.png
2.2 其他参数设置
dt_tmp <- rbind(dt[-1, ], dt[1, ])
dt_tmp[nrow(dt_tmp), 1] <- "Overall"
tm <- forest_theme(base_size = 10, #文本的大小
# Confidence interval point shape, line type/color/width
ci_pch = 15, # 可信区间点的形状
ci_col = "#762a83", # CI的颜色
ci_fill = "blue", # CI中se点的颜色填充
ci_alpha = 0.8, # CI透明度
ci_lty = 1, # CI的线型
ci_lwd = 1.5, # CI的线宽
ci_Theight = 0.2, # Set an T end at the end of CI CI的高度，默认是NULL
# Reference line width/type/color 参考线默认的参数，中间的竖的虚线
refline_lwd = 1, #中间的竖的虚线
refline_lty = "dashed",
refline_col = "grey20",
# Vertical line width/type/color 垂直线宽/类型/颜色 可以添加一条额外的垂直线，如果没有就不显示
vertline_lwd = 1, #可以添加一条额外的垂直线，如果没有就不显示
vertline_lty = "dashed",
vertline_col = "grey20",
# Change summary color for filling and borders 更改填充和边框的摘要颜色
summary_fill = "yellow", #汇总部分大菱形的颜色
summary_col = "#4575b4",
# Footnote font size/face/color 脚注字体大小/字体/颜色
footnote_cex = 0.6,
footnote_fontface = "italic",
footnote_col = "red")
pt <- forest(dt_tmp[,c(1:3, 20:21)],
est = dt_tmp$est,
lower = dt_tmp$low,
upper = dt_tmp$hi,
sizes = dt_tmp$se,
is_summary = c(rep(FALSE, nrow(dt_tmp)-1), TRUE),
ci_column = 4,
ref_line = 1,
arrow_lab = c("Placebo Better", "Treatment Better"),
xlim = c(0, 4),
ticks_at = c(0.5, 1, 2, 3),
footnote = "This is the demo data. Please feel free to change\nanything you want.",
theme = tm)
plot(pt)
forestploter-2
2.3.1 多组CI - 简单绘制
dt <- read.csv(system.file("extdata", "example_data.csv", package = "forestploter"))
# indent the subgroup if there is a number in the placebo column
dt$Subgroup <- ifelse(is.na(dt$Placebo),
dt$Subgroup,
paste0(" ", dt$Subgroup))
# 将 NA 转为空白或转换为对应字符
dt$n1 <- ifelse(is.na(dt$Treatment), "", dt$Treatment)
dt$n2 <- ifelse(is.na(dt$Placebo), "", dt$Placebo)
# 为 CI 添加两个空白列
dt$`CVD outcome` <- paste(rep(" ", 20), collapse = " ")
dt$`COPD outcome` <- paste(rep(" ", 20), collapse = " ")
# 设置主题
tm <- forest_theme(base_size = 10,
refline_lty = "solid",
ci_pch = c(15, 18),
ci_col = c("#377eb8", "#4daf4a"),
footnote_col = "blue",
legend_name = "Group",
legend_value = c("Trt 1", "Trt 2"),
vertline_lty = c("dashed", "dotted"),
vertline_col = c("#d6604d", "#bababa"))
p <- forest(dt[,c(1, 19, 21, 20, 22)],
est = list(dt$est_gp1,
dt$est_gp2,
dt$est_gp3,
dt$est_gp4),
lower = list(dt$low_gp1,
dt$low_gp2,
dt$low_gp3,
dt$low_gp4),
upper = list(dt$hi_gp1,
dt$hi_gp2,
dt$hi_gp3,
dt$hi_gp4),
ci_column = c(3, 5),
ref_line = 1,
vert_line = c(0.5, 2),
nudge_y = 0.2,
theme = tm)
plot(p) # 若提供的est,lower和upper大于绘制 CI 的列数，则est,lower和upper 将被重用。故，est_gp1和est_gp2被视为第 1 组，est_gp3和est_gp4被视为第 2 组
forestploter-3
2.3.1 多组CI - 不同的列进行不同的设置
dt$`HR (95% CI)` <- ifelse(is.na(dt$est_gp1), "",
sprintf("%.2f (%.2f to %.2f)",
dt$est_gp1, dt$low_gp1, dt$hi_gp1))
dt$`Beta (95% CI)` <- ifelse(is.na(dt$est_gp2), "",
sprintf("%.2f (%.2f to %.2f)",
dt$est_gp2, dt$low_gp2, dt$hi_gp2))
tm <- forest_theme(arrow_type = "closed",
arrow_label_just = "end")
p <- forest(dt[,c(1, 21, 23, 22, 24)],
est = list(dt$est_gp1,
dt$est_gp2),
lower = list(dt$low_gp1,
dt$low_gp2),
upper = list(dt$hi_gp1,
dt$hi_gp2),
ci_column = c(2, 4),
ref_line = c(1, 0),
vert_line = list(c(0.3, 1.4), c(0.6, 2)),
x_trans = c("log", "none"),
arrow_lab = list(c("L1", "R1"), c("L2", "R2")),
xlim = list(c(0, 3), c(-1, 3)),
ticks_at = list(c(0.1, 0.5, 1, 2.5), c(-1, 0, 2)),
xlab = c("OR", "Beta"),
nudge_y = 0.2,
theme = tm)
plot(p)
forestploter-4
参考：
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