ggcor包的安装与绘图示例

最新推荐文章于 2024-09-12 08:01:40 发布

原创最新推荐文章于 2024-09-12 08:01:40 发布 · 5.1k 阅读

14 ·

CC 4.0 BY-SA版权

本文介绍了如何在R中安装已下架的ggcor包，并提供了该包的使用示例，包括Correlation plot、Mantel test plot、Circular heatmap和General heatmap的绘制，帮助用户进行相关性分析。

最近有小伙伴问到带mantel test检验的相关性矩阵怎么画，于是小编就在网上找到了相关的绘图示例，整理了网上各位大神关于ggcor包的下载以及该包自带的示例代码供各位小伙伴参考使用~

首先是要安装ggcor这个包。由于该包的作者已经下架了这个包，所以只能自己下载压缩包本地安装，小编主要参考的是这篇文章：
https://www.zhihu.com/question/409189621/answer/1842210647

示例代码
ggcor包自带的几个绘图示例

Correlation plot

library(ggplot2)
library(ggcor)
set_scale()
quickcor(mtcars) + geom_square()
quickcor(mtcars, type = "upper") + geom_circle2()
quickcor(mtcars, cor.test = TRUE) +
  geom_square(data = get_data(type = "lower", show.diag = FALSE)) +
  geom_mark(data = get_data(type = "upper", show.diag = FALSE), size = 2.5) +
  geom_abline(slope = -1, intercept = 12)

在这里插入图片描述
Mantel test plot

library(dplyr)
library(ggplot2)
library(ggcor)

data("varechem", package = "vegan")
data("varespec", package = "vegan")

mantel <- mantel_test(varespec, varechem,
                      spec.select = list(Spec01 = 1:7,
                                         Spec02 = 8:18,
                                         Spec03 = 19:37,
                                         Spec04 = 38:44)) %>% 
  mutate(rd = cut(r, breaks = c(-Inf, 0.2, 0.4, Inf),
                  labels = c("< 0.2", "0.2 - 0.4", ">= 0.4")),
         pd = cut(p.value, breaks = c(-Inf, 0.01, 0.05, Inf),
                  labels = c("< 0.01", "0.01 - 0.05", ">= 0.05")))

quickcor(varechem, type = "upper") +
  geom_square() +
  anno_link(aes(colour = pd, size = rd), data = mantel) +
  scale_size_manual(values = c(0.5, 1, 2)) +
  scale_colour_manual(values = c("#D95F02", "#1B9E77", "#A2A2A288")) +
  guides(size = guide_legend(title = "Mantel's r",
                             override.aes = list(colour = "grey35"), 
                             order = 2),
         colour = guide_legend(title = "Mantel's p", 
                               override.aes = list(size = 3), 
                               order = 1),
         fill = guide_colorbar(title = "Pearson's r", order = 3))

在这里插入图片描述
Circular heatmap

rand_correlate(100, 8) %>% ## require ambient packages
  quickcor(circular = TRUE, cluster = TRUE, open = 45) +
  geom_colour(colour = "white", size = 0.125) +
  anno_row_tree() +
  anno_col_tree() +
  set_p_xaxis() +
  set_p_yaxis()

在这里插入图片描述
General heatmap

d1 <- rand_dataset(20, 30) %>% 
  gcor_tbl(cluster = TRUE)
p <- matrix(sample(LETTERS[1:4], 90, replace = TRUE), nrow = 30,
             dimnames = list(paste0("sample", 1:30), paste0("Type", 1:3))) %>% 
  gcor_tbl(name = "Type", row.order = d1) %>% 
  qheatmap(aes(fill = Type)) + coord_fixed() + remove_y_axis()
d2 <- data.frame(x = sample(paste0("var", 1:20), 200, replace = TRUE))

set_scale()
quickcor(d1) +
  geom_colour(aes(fill = value)) +
  anno_hc_bar(width = 1) +
  anno_row_custom(p) +
  anno_row_tree() +
  anno_hc_bar(pos = "top") +
  anno_bar(d2, aes(x = x), height = 0.12) +
  anno_col_tree(height = 0.12)