使用ggplot / stat_summary为两个单独的组添加多行均值

Question

新手来了。

我正在尝试创建两个不同基因的基因表达式2^-DCT值(数据框中的p2ndCt)的抖动图，以及表示平均值的两条单独的线。我的样本是一系列有序的细胞系。我将数据放在data.frame中，如下所示：

       Sample  gene   dCt       p2ndCt
1  K562 naive e14a2 -1.34 2.531513e+00
2   DMSO ctrl e14a2 -0.40 1.319508e+00
3      0.5 nM e14a2 -1.93 3.810552e+00
4        1 nM e14a2 -3.06 8.339726e+00
5        2 nM e14a2 -4.17 1.800094e+01
6      3.5 nM e14a2 -4.70 2.599208e+01
7        5 nM e14a2 -3.58 1.195879e+01

..。

67       5 nM  e6a2 -2.06 4.169863e+00
68      10 nM  e6a2 -0.02 1.013959e+00
69      15 nM  e6a2  7.52 5.448217e-03
70      25 nM  e6a2  0.75 5.946036e-01

我想让stat_summary()在每个样本中分离e14a2均值和e6a2均值，但是我不确定如何在现有的data.frame中做到这一点。我尝试过以下代码：

##BCR-ABL1 dCt qPCR graph
BCRABL1_dCt <- read.csv('~/Manjaro/workspace/BCR-ABL1_dCt.csv')
BCRABL1_dCt$Sample <- factor(BCRABL1_dCt$Sample, levels = c('K562 naive', 'DMSO ctrl', '0.5 nM', '1 nM', '2 nM', '3.5 nM', '5 nM', '10 nM', '15 nM', '25 nM', '50 nM', '200 nM'))

BCRABL1_dCt_plot <- ggplot(BCRABL1_dCt, aes(x = Sample, y = p2ndCt, color = gene)) + geom_jitter(width = 0.1, height = 0) + stat_summary(aes(y = p2ndCt, group = 1), fun = mean, geom = 'line', size = 1, color = 'red')
e14a2_dCt_plot

...which只给了我一条线，平均了这两个基因。我读到过，我可以把这些基因放在不同的data.frames中，但最好是全部放在一个one里。提前感谢您的帮助！

Answer 1

使用所提供的数据片段运行您的代码，Sample提供了一种方法

library(ggplot2)

ggplot(BCRABL1_dCt, aes(x = Sample, y = p2ndCt, color = gene)) + 
  geom_jitter(width = 0.1, height = 0) + 
  stat_summary(aes(y = p2ndCt, group = 1), fun = mean, geom = 'line', size = 1, color = 'red')

​

​

但是，使用group=gene而不是group=1为每个gene提供了一系列方法

ggplot(BCRABL1_dCt, aes(x = Sample, y = p2ndCt, color = gene)) + 
  geom_jitter(width = 0.1, height = 0) + 
  stat_summary(aes(y = p2ndCt, group = gene), fun = mean, geom = 'line', size = 1, color = 'red')

​

​

DATA

BCRABL1_dCt <- read.table(text = "       Sample  gene   dCt       p2ndCt
1  K562_naive e14a2 -1.34 2.531513e+00
2   DMSO_ctrl e14a2 -0.40 1.319508e+00
3      0.5_nM e14a2 -1.93 3.810552e+00
4        1_nM e14a2 -3.06 8.339726e+00
5        2_nM e14a2 -4.17 1.800094e+01
6      3.5_nM e14a2 -4.70 2.599208e+01
7        5_nM e14a2 -3.58 1.195879e+01
67       5_nM  e6a2 -2.06 4.169863e+00
68      10_nM  e6a2 -0.02 1.013959e+00
69      15_nM  e6a2  7.52 5.448217e-03
70      25_nM  e6a2  0.75 5.946036e-01", header = TRUE)

BCRABL1_dCt$Sample <- gsub("_", " ", BCRABL1_dCt$Sample)
BCRABL1_dCt$Sample <- factor(BCRABL1_dCt$Sample, levels = c('K562 naive', 'DMSO ctrl', '0.5 nM', '1 nM', '2 nM', '3.5 nM', '5 nM', '10 nM', '15 nM', '25 nM', '50 nM', '200 nM'))