Question

我甚至不知道如何描述我想要正确生成的情节，这不是一个好的开始。我将首先向您展示我的数据，然后尝试解释/显示具有该元素的图像。

我的数据：

   strain condition count.up count.down
1    phbA  balanced      120       -102
2    phbA   limited      114       -319
3    phbB  balanced      122       -148
4    phbB   limited       97       -201
5   phbAB  balanced      268       -243
6   phbAB   limited      140       -189
7    phbC  balanced       55        -65
8    phbC   limited      104       -187
9    phaZ  balanced       99        -28
10   phaZ   limited      147       -205
11   bdhA  balanced      246       -159
12   bdhA   limited      143       -383
13  acsA2  balanced      491       -389
14  acsA2   limited      131       -295

我有七个样本，每个样本有两个条件。对于这些样本中的每一个，我都有下调基因的数量，以及被上调的基因数量（count.down和count.up）。

我想绘制这个，以便将每个样本分组;因此除了phbA限制之外，phbA平衡被躲过了。每个条形图在图的正面都有一部分（代表count.up＃），在图的负面有一部分（代表count.down＃）。

我希望“平衡”条件下的条形为一种颜色，而“有限”条件下的条形变为另一种颜色。理想情况下，每种颜色会有两个渐变（一个用于count.up，一个用于count.down），只是为了在条形的两个部分之间产生视觉差异。

有些图片中包含我想要组合在一起的元素：

我也尝试应用这个stackoverflow示例的一些部分，但我无法弄清楚如何使它适用于我的数据集。 I like the pos v. neg bars here; a single bar that covers both, and the colour differentiation of it. This does not have the grouping of conditions for one sample, or the colour coding extra layer that differentiates condition

我尝试了很多东西，但我无法做到。我认为我真的很挣扎，因为很多geom_bar示例使用计数数据，该图计算自己，我给它直接计数数据。我似乎无法在我的代码中成功区分，当我转移到stat= "identity"然后一切都变得混乱。任何想法或建议都将非常感谢！

使用建议的链接：所以我一直在玩这个作为模板，但我已经卡住了。

df <- read.csv("countdata.csv", header=T) 
df.m <- melt(df, id.vars = c("strain", "condition")) 
ggplot(df.m, aes(condition)) + geom_bar(subset = ,(variable == "count.up"),    aes(y = value, fill = strain), stat = "identity") + geom_bar(subset = ,(variable == "count.down"), aes(y = -value, fill = strain), stat = "identity") + xlab("") + scale_y_continuous("Export - Import",formatter = "comma")

当我尝试运行ggplot行时，它返回了一个错误：找不到函数“。”。我意识到我没有安装/加载dplyr，所以我做到了。然后我玩了很多，最后得出结论：

library(ggplot2)
library(reshape2)
library(dplyr)
library(plyr)

df <- read.csv("countdata.csv", header=T)
df.m <- melt(df, id.vars = c("strain", "condition"))

#this is what the df.m looks like now (if you look at my initial input df, I    just changed in the numbers in excel to all be positive). Included so you can see what the melt does
df.m =read.table(text = "
strain condition   variable value
1    phbA  balanced   count.up   120
2    phbA   limited   count.up   114
3    phbB  balanced   count.up   122
4    phbB   limited   count.up    97
5   phbAB  balanced   count.up   268
6   phbAB   limited   count.up   140
7    phbC  balanced   count.up    55
8    phbC   limited   count.up   104
9    phaZ  balanced   count.up    99
10   phaZ   limited   count.up   147
11   bdhA  balanced   count.up   246
12   bdhA   limited   count.up   143
13  acsA2  balanced   count.up   491
14  acsA2   limited   count.up   131
15   phbA  balanced count.down   102
16   phbA   limited count.down   319
17   phbB  balanced count.down   148
18   phbB   limited count.down   201
19  phbAB  balanced count.down   243
20  phbAB   limited count.down   189
21   phbC  balanced count.down    65
22   phbC   limited count.down   187
23   phaZ  balanced count.down    28
24   phaZ   limited count.down   205
25   bdhA  balanced count.down   159 
26   bdhA   limited count.down   383
27  acsA2  balanced count.down   389
28  acsA2   limited count.down   295", header = TRUE)

这是根据应变绘制的，在两种条件下的count.up和count.down值

ggplot(df.m, aes(strain)) + geom_bar(subset = .(variable == "count.up"), aes(y = value, fill = condition), stat = "identity") + geom_bar(subset = .(variable == "count.down"), aes(y = -value, fill = condition), stat = "identity") + xlab("") 

#this adds a line break at zero
labels <- gsub("20([0-9]{2})M([0-9]{2})", "\\2\n\\1",
           df.m$strain)


#this adds a line break at zero to improve readability
last_plot() + geom_hline(yintercept = 0,colour = "grey90")

我无法工作的一件事（不幸的是）是如何在每个条形框内显示代表“值”的数字。我已经得到了要显示的数字，但我无法将它们放在正确的位置。我有点疯了！

我的数据与上述相同;这是我的代码在

的地方

我看了很多示例，在躲闪的地块上使用geom_text显示标签。我一直无法成功实施。我得到的最接近的如下 - 任何建议将不胜感激！

library(ggplot2)
library(reshape2)
library(plyr)
library(dplyr)
df <- read.csv("countdata.csv", header=T)
df.m <- melt(df, id.vars = c("strain", "condition"))
ggplot(df.m, aes(strain), ylim(-500:500)) + 
geom_bar(subset = .(variable == "count.up"), 
aes(y = value, fill = condition), stat = "identity", position = "dodge") +
geom_bar(subset = .(variable == "count.down"), 
aes(y = -value, fill = condition), stat = "identity", position = "dodge") + 
geom_hline(yintercept = 0,colour = "grey90")

last_plot() + geom_text(aes(strain, value, group=condition, label=label, ymax = 500, ymin= -500), position = position_dodge(width=0.9),size=4)

这给出了这个：

为什么不对齐！

我怀疑我的问题与我实际绘制的方式有关，或者我没有正确地告诉geom_text命令如何定位自己。有什么想法吗？

Answer 1

试试这个。就像你用两个语句（一个用于正数，一个用于负数）定位条形时，以相同的方式定位文本。然后，使用vjust微调它们的位置（在栏内或栏外）。此外，数据框中没有'label'变量;我认为标签是value。

library(ggplot2)

## Using your df.m data frame
ggplot(df.m, aes(strain), ylim(-500:500)) + 
geom_bar(data = subset(df.m, variable == "count.up"), 
   aes(y = value, fill = condition), stat = "identity", position = "dodge") +
geom_bar(data = subset(df.m, variable == "count.down"), 
   aes(y = -value, fill = condition), stat = "identity", position = "dodge") + 
geom_hline(yintercept = 0,colour = "grey90")


last_plot() + 
   geom_text(data = subset(df.m, variable == "count.up"), 
      aes(strain, value, group=condition, label=value),
        position = position_dodge(width=0.9), vjust = 1.5, size=4) +
    geom_text(data = subset(df.m, variable == "count.down"), 
      aes(strain, -value, group=condition, label=value),
        position = position_dodge(width=0.9), vjust = -.5, size=4) +
    coord_cartesian(ylim = c(-500, 500))

geom_bar ggplot2堆积，分组条形图，正负值 - 金字塔图

1 个答案: