r - 如何调整geom_point()的scale_alpha？

Question

我制作了这个火山图:

我希望彩色 geom_point() 的 alpha 值不断增加，例如-log(P-value) ~2.3 处的值对应于 alpha = 0.75，而 -log(P-value) 上的最大值-scale 对应于alpha = 1。这应该会使阅读浓缩区域中的文本变得更容易。

预期输出手动绘制，并使用两个 geom_point() 示例手动绘制，说明我正在尝试完成的图形输出。

脚本

ggplot(BT_Ctrl, aes(x = diff, y = logp)) + 
  geom_point(data = filter(BT_Ctrl, 
                           (logp > 0 & logp < (-log(0.1))) | (logp > (-log(0.1)) & diff > (-1) & diff < 0) 
  ), aes(alpha = logp),
  size = 3, color = "grey50", fill = "grey60", shape=21, stroke = 1) +
  
  scale_alpha_continuous(range = c(0.05, .25)) + 

  
  geom_point(data = filter(BT_Ctrl,
                           (logp > (-log(0.1)) & diff < (-1)) | (logp > (-log(0.1)) & diff > 0)) %>%
               mutate(group = ifelse(diff > 0, "Tumor", "Ctrl")),
             aes(color = group, fill = group, size = logp, alpha = logp), alpha = .25, shape = 21, stroke = 1.5) +
  
  
  scale_size(range = c(3.5,8.5)) +
  
  scale_fill_manual(values = alpha(c("#D1B551", "#678F53"), 0.2),
                    name = "",
                    labels = c("Low abundant", 
                               "High abundant")) +
  scale_colour_manual(values = c("#D1B551", "#678F53"),
                      name = "",
                      labels = c("Low abundant", 
                                 "High abundant")) +
  
  scale_x_continuous(breaks = seq(-3, 4, 1),
                     name = "**Difference on log<sub>2</sub>-scale**") +
  scale_y_continuous(breaks = seq(0, 8, 1),
                     name = "**-log**(*P*-value)") +
  coord_cartesian(ylim = c(0, 8),
                  xlim = c(-3.5, 4)) +
  
  guides(colour = guide_legend(override.aes = list(size = 10)),
         size = "none",
         alpha = "none") +
  
  theme(axis.line = element_line(colour = "black", 
                                 size = .6),
        panel.grid.major = element_line(colour = "gray95"),
        panel.grid.minor = element_line(colour = "gray95"),
        panel.border = element_blank(),
        panel.background = element_blank(),
        axis.text.x = element_text(color = "grey20", size = 16), 
        axis.title.x = ggtext::element_markdown(color = "grey20", size = 22, 
                                                margin = ggplot2::margin(t = 10)),
        axis.text.y = element_text(color = "grey20", size = 16), 
        axis.title.y = ggtext::element_markdown(color = "grey20", size = 25, 
                                                margin = ggplot2::margin(r = 8)),
        legend.key = element_rect(fill = "white"),
        plot.title = ggtext::element_markdown(color = "grey20", 
                                              size = 20, hjust = 0),
        plot.subtitle = element_text(hjust = 0.5),
        legend.text = ggtext::element_markdown(size = 30), 
        legend.title = element_text(size = 20, hjust = 0.5),
        legend.position = "bottom")

尝试

我尝试添加到aes(alpha=logp)，例如:

  geom_point(data = filter(BT_Ctrl,
                           (logp > (-log(0.1)) & diff < (-1)) | (logp > (-log(0.1)) & diff > 0)) %>%
               mutate(group = ifelse(diff > 0, "Tumor", "Ctrl")),
             aes(color = group, fill = group, size = logp, alpha = logp), shape = 21, stroke = 1.5) +

哪种方式做到了:

但是，我无法弄清楚如何手动调整/编辑以使高 -log(P-values) 变得更加可见/不太透明。

我尝试了不同版本的 scale_alpha_continuous(range = c(0.75, 1)) +，这弄乱了填充。

数据

BT_Ctrl <- structure(list(diff = c(1.56649042, -1.87675892, -1.80424434, 
1.72693416, 1.5787399, -1.86329892, -1.6789665, -1.6568188, -1.86840369, 
1.39048414, 1.84550897, 1.38801267, -1.80942931, 1.78143388, 
1.69846066, 1.56978846, 1.77520343, -1.55898508, 1.79985492, 
2.17939968, -1.57936357, -1.89272256, 1.72693416, -1.98373825, 
2.01700136, 1.40530492, -1.84020557, -1.84425835, -2.60720077, 
-2.08867432, -1.84536301, 1.5702918, -1.77541872, -1.44684146, 
-2.06145142, -1.84536301, 1.67972282, -1.77577326, -1.63510231, 
1.34901378, 1.89824526, -2.02095109, 2.36706042, -1.73584855, 
1.36028805, 1.59969963, 1.75797169, 1.77520343, 2.45895289, -1.77541872, 
-1.62727675, 1.43298941, -1.55898508, 1.77236427, -1.58338037, 
-1.6589846, -1.64190355, -2.2859511, -2.2871833, -1.95949086, 
1.77520343, -2.27851687, 1.5787399, -1.62727675, 3.1597624, -1.59762678, 
1.93588366, -1.80424434, -2.2871833, 2.44329109, -2.60720077, 
-1.73584855, -1.77876207, 1.72096759, 1.96423548, 1.7674994, 
2.33708957, 1.84550897, -2.02085819, 1.67972282, 1.89824526, 
2.17943425, 1.96427512, 2.47608359, -2.08867432, 2.44329109, 
1.77520343, -2.2859511, -2.06145142, -1.55898508, -1.59762678, 
-1.8741578, 2.18772316, -1.69511194, 2.35213644, 1.59062826, 
-1.82735184, -1.59762678, -1.55143048, 1.78143388), logp = c(3.16307, 
2.183779, 2.481417, 2.213655, 2.225182, 2.175182, 2.33327, 2.076203, 
3.048191, 2.639413, 2.415948, 2.424919, 2.275779, 2.454661, 2.507648, 
2.716042, 2.628121, 2.056823, 2.690471, 3.260036, 2.911379, 2.155653, 
2.213655, 2.175591, 3.429587, 2.244559, 2.165071, 2.327765, 3.174527, 
2.48279, 2.461853, 2.366302, 2.20657, 2.231255, 3.239911, 2.461853, 
2.199472, 2.370887, 2.28479, 2.290686, 3.111832, 2.966969, 3.623449, 
2.325613, 2.1868, 2.049223, 2.065346, 2.628121, 3.364917, 2.20657, 
2.113838, 2.412649, 2.056823, 2.263531, 2.102176, 2.539142, 3.330895, 
3.094797, 3.31816, 2.776573, 2.628121, 3.002339, 2.225182, 2.113838, 
7.517751, 3.690766, 3.759602, 2.481417, 3.31816, 4.018759, 3.174527, 
2.325613, 2.245998, 2.477856, 2.353492, 3.37967, 3.957788, 2.415948, 
2.39418, 2.199472, 3.111832, 3.659539, 2.911672, 4.604996, 2.48279, 
4.018759, 2.628121, 3.094797, 3.239911, 2.056823, 3.690766, 2.369712, 
3.320643, 2.075087, 4.50423, 2.330635, 2.416558, 3.690766, 2.115206, 
2.454661)), row.names = c(NA, -100L), class = c("tbl_df", "tbl", 
"data.frame"))  

Answer 1

根据 @tjebo 的答案，这是否能满足您的需求？

我向数据中添加了一个规范化的“强度”变量，并使用了它。通过使用 rescale() 值，您可以更改 Alpha 的强度，并获得“~2.3 = 0.75 强度”关系。

library(tidyverse)

data_grey <- BT_Ctrl %>%
  filter(logp > 0 & logp < (-log(0.1)) | (logp > (-log(0.1)) & diff > (-1) & diff < 0)) %>% 
  mutate(intensity = 0.05)

data_color <-  BT_Ctrl %>%
  filter(logp > (-log(0.1)) & diff < (-1) | (logp > (-log(0.1)) & diff > 0)) %>%
  mutate(group = ifelse(diff > 0, "Tumor", "Ctrl")) %>% 
  mutate(intensity = scales::rescale(x = exp(logp), to = c(0.05, 30)))

ggplot(mapping = aes(x = diff, y = logp)) +
  geom_point(data = data_color, shape = 21, aes(fill = group, size = logp, alpha = intensity)) + 
  geom_point(data = data_grey, alpha = 0.1, shape = 21, fill = "grey50") +
  scale_alpha_identity(guide = "none") +
  scale_y_continuous(limits = c(0, 8))