geom_bar ggplot2 具有正值和负值的堆叠、分组条形图 - 金字塔图
geom_bar ggplot2 stacked, grouped bar plot with positive and negative values - pyramid plot
我什至不知道如何正确描述我试图生成的情节，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/展示包含其中元素的图像。
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，每个样本有两种情况。对于这些样本中的每一个，我都有下调的基因数量和上调的基因数量（count.down 和 count.up）。
我想绘制此图以便将每个样本分组；所以 phbA balanced 在 phbA limited 旁边被闪避了。每个条在图的正侧有一部分（代表 count.up #），在图的负侧有一部分（代表 count.down #）。
我希望 'balanced' 条件下的条形是一种颜色，'limited' 条件下的条形是另一种颜色。理想情况下，每种颜色会有两种渐变（一种用于 count.up，一种用于 count.down），只是为了在条形的两个部分之间形成视觉差异。
一些包含我试图整合的元素的图像：
我也尝试过应用这个 Whosebug 示例的一些部分，但我不知道如何让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，但就是做不好。我认为我真的很挣扎，因为很多 geom_bar 示例使用计数数据，该图会自行计算，而我直接给它提供计数数据。我似乎无法在我的代码中成功地进行区分，当我转移到 stat= "identity" 时，一切都变得一团糟。任何想法或建议将不胜感激！
使用 link 建议：
所以我一直在用它作为模板，但我被卡住了。
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，它返回错误：找不到函数“.”。我意识到我没有 dplyr installed/loaded，所以我这样做了。
然后我玩了很多，最后得出：
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)
此图按应变绘制，count.up 和 count.down 两种条件下的值
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")
我无法开始工作的一件事（不幸的是）是如何在每个条形框中显示代表 'value' 的数字。我已经得到要显示的数字，但我无法将它们放在正确的位置。我要疯了！
我的数据和上面一样；这是我的代码所在的位置
我看过大量在闪避图上使用 geom_text 显示标签的示例。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，或者我没有正确告诉 geom_text 命令如何定位自己。有什么想法吗？
试试这个。正如您用两个陈述（一个表示正面，一个表示负面）定位条一样，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；我假设标签是 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))
我什至不知道如何正确描述我试图生成的情节，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/展示包含其中元素的图像。
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，每个样本有两种情况。对于这些样本中的每一个，我都有下调的基因数量和上调的基因数量（count.down 和 count.up）。
我想绘制此图以便将每个样本分组；所以 phbA balanced 在 phbA limited 旁边被闪避了。每个条在图的正侧有一部分（代表 count.up #），在图的负侧有一部分（代表 count.down #）。
我希望 'balanced' 条件下的条形是一种颜色，'limited' 条件下的条形是另一种颜色。理想情况下，每种颜色会有两种渐变（一种用于 count.up，一种用于 count.down），只是为了在条形的两个部分之间形成视觉差异。
一些包含我试图整合的元素的图像：
我也尝试过应用这个 Whosebug 示例的一些部分，但我不知道如何让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，但就是做不好。我认为我真的很挣扎，因为很多 geom_bar 示例使用计数数据，该图会自行计算，而我直接给它提供计数数据。我似乎无法在我的代码中成功地进行区分，当我转移到 stat= "identity" 时，一切都变得一团糟。任何想法或建议将不胜感激！
使用 link 建议： 所以我一直在用它作为模板，但我被卡住了。
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，它返回错误：找不到函数“.”。我意识到我没有 dplyr installed/loaded，所以我这样做了。 然后我玩了很多，最后得出：
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)
此图按应变绘制，count.up 和 count.down 两种条件下的值
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")
我无法开始工作的一件事（不幸的是）是如何在每个条形框中显示代表 'value' 的数字。我已经得到要显示的数字，但我无法将它们放在正确的位置。我要疯了！
我的数据和上面一样；这是我的代码所在的位置
我看过大量在闪避图上使用 geom_text 显示标签的示例。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，或者我没有正确告诉 geom_text 命令如何定位自己。有什么想法吗？
试试这个。正如您用两个陈述（一个表示正面，一个表示负面）定位条一样，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；我假设标签是 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))