森林图在论文中很常见,多用于表示多因素分析中的变量与结果变量的比值效应,可以用图示的方法比较直观的绘制出来。既往我们在文章《R语言快速绘制多因素回归分析森林图(1)》已经介绍了怎么绘制森林图,但是绘图比较简单,不够美观,不能绘制相对复杂的森林图。今天我们来介绍一下forestploter包,它等于是在forestplot包的基础上进一步强化功能,制作方法也相对简单一点,而且加强了对图形的精细控制,而且可以绘制单组和多组森林图。
我们先导入R包和数据
library(grid)
library(forestploter)
dt<-read.csv("E:/r/test/forest2.csv",sep=',',header=TRUE)
这是一个森林图数据(公众号回复:森林图数据2,可以获得数据)这个数据,嫌麻烦的可以在这里下载:https://download.csdn.net/download/dege857/86945654?spm=1001.2014.3001.5501
前几个变量我解释一下Subgroup:分组,就是的组别和亚组,Treatment:治疗组例数,Placebo:使用安慰剂,也就是对照组的例数。Est:效应值,可以是OR或者HR,low:效应值的最低值,可以认为是可信区间的下限,hi:效应值的最高值,可以认为是可信区间的上限。
我们先来画一个最基础的森林图,后面的几个数据暂时不需要,我们先精简一下数据
dt <- dt[,1:6]
View(dt)
数据变成了一个精简的数据(上图),我们先把数据格式整理一下,先让它缩进一格
dt$Subgroup <- ifelse(is.na(dt$Placebo),
dt$Subgroup,
paste0(" ", dt$Subgroup))
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$est))/1.96
生成一个绘图区间,等下用来绘图
dt$` ` <- paste(rep(" ", 20), collapse = " ")
生成HR和可信区间
dt$`HR (95% CI)` <- ifelse(is.na(dt$se), "",
sprintf("%.2f (%.2f to %.2f)",
dt$est, dt$low, dt$hi))#sprintF返回字符和可变量组合
p <- forest(dt[,c(1:3, 8:9)],
est = dt$est, #效应值
lower = dt$low, #可信区间下限
upper = dt$hi, #可信区间上限
sizes = dt$se, #黑框的大小
ci_column = 4, #在那一列画森林图,要选空的那一列
ref_line = 1,
arrow_lab = c("Placebo Better", "Treatment Better"),
xlim = c(0, 4),
ticks_at = c(0.5, 1, 2, 3),
footnote = "This is the demo data. Please feel free to change\nanything you want.")
p
有些人可能想问,有些森林图是有P值的,这个没有P值怎么办,我们可以给它加上去
dt$p <- paste(rep("<0.05", 22))
重新绘图
p <- forest(dt[,c(1:3, 8:10)],
est = dt$est, #效应值
lower = dt$low, #可信区间下限
upper = dt$hi, #可信区间上限
sizes = dt$se, #黑框的大小
ci_column = 4, #在那一列画森林图,要选空的那一列
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.")
p
这样P值就出来了
生成图形后我们还可以对图形进行细节调整,我们把第一行总病例数放到最后改成汇总,然后把它的名字改成Overall,
dt_tmp <- rbind(dt[-1, ], dt[1, ])
dt_tmp[nrow(dt_tmp), 1] <- "Overall"
forest_theme函数可以对森林图图片的细节进行调整,我们可以在forest_theme函数上设定预定的森林图样式模块,到时直接绘图就好了
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")
设定好模块后直接绘图就可以了
pt <- forest(dt_tmp[,c(1:3, 8:9)],
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)
g <- edit_plot(p, row = 3, gp = gpar(col = "red", fontface = "italic"))
g
g <- edit_plot(g,
row = c(3, 6, 11, 13),
col = 4,
which = "ci",
gp = gpar(col = "green"))
g
g <- edit_plot(g,
row = c(2, 5, 10, 13, 17, 20),
gp = gpar(fontface = "bold"))
g
g <- edit_plot(g, row = 5, which = "background",
gp = gpar(fill = "darkolivegreen1"))
g
g <- insert_text(g,
text = "Treatment group",
col = 2:3,
part = "header",
gp = gpar(fontface = "bold"))
g
g <- add_underline(g, part = "header")
g
g <- insert_text(g,
text = "This is a long text. Age and gender summarised above.\nBMI is next",
row = 10,
just = "left",
gp = gpar(cex = 0.6, col = "green", fontface = "italic"))
g
下面来介绍一下怎么绘制多组的森林图,绘制对组森林图就要涉及多组的数据,我们把数据重新导入一下
dt<-read.csv("E:/r/test/forest2.csv",sep=',',header=TRUE)
设置一下缩进,这样好看一点,这步和前面是一样的
dt$Subgroup <- ifelse(is.na(dt$Placebo),
dt$Subgroup,
paste0(" ", dt$Subgroup))#######如果变量没有缺失,就缩进一格,也就是前进一格
因为是双组变量,所以要设置2个n,这步和前面基本一样
dt$n1 <- ifelse(is.na(dt$Treatment), "", dt$Treatment)###将缺失的部分变为空格
dt$n2 <- ifelse(is.na(dt$Placebo), "", dt$Placebo)
因为是要画两个森林图,所以要增加两个空地方来画图
dt$`CVD outcome` <- paste(rep(" ", 20), collapse = " ")
dt$`COPD outcome` <- paste(rep(" ", 20), collapse = " ")
设置一些森林图的基本参数,这步和前面是一样的
tm <- forest_theme(base_size = 10,
refline_lty = "solid", #参考线类型
ci_pch = c(15, 18),
ci_col = c("#377eb8", "#4daf4a"),
footnote_col = "blue",
legend_name = "Group", #设置标题名字
legend_value = c("Trt 1", "Trt 2"), #设置分组名字
vertline_lty = c("dashed", "dotted"),
vertline_col = c("#d6604d", "#bababa"))
最后绘图,这里我要说一下,ci_column = c(3, 5)是指在第3和5列绘图,est_gp1和est_gp2为一组,est_gp3和est_gp4为一组,其他的依次类推
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)
p