ggplot2 中具有三重图例的散点图
Scatter plot in ggplot2 with triple legend
我想制作一个带有形状、颜色和填充的散点图作为我的数据的编码。一切看起来形状和颜色都很好，但是填充选项似乎没有响应。我已经检查过与该主题类似的其他帖子，但仍然无法弄清楚如何处理这个问题。在我的案例中，我想要的是根据两种不同的过滤器尺寸（0.22=空心，0.45=实心）填充的过滤器列，以及根据我的时间着色的所有内容。
请找到我使用的数据集和代码，
Samples Filter Type Time Coord1 Coord2
45P116 0.45 Oil Incubation 16 -0.177125327477 0.0329641384336
22P264 0.22 Oil Incubation 64 -0.036421737819 0.41278336259
45P113 0.45 Oil Incubation 13 -0.183501817053 -0.0333774595889
45BL30 0.45 Control 30 -0.0169216562011 -0.160467270544
22P231 0.22 Oil Incubation 30 -0.0742549515959 0.134945242558
22P116 0.22 Oil Incubation 16 -0.168257444167 0.0425318235085
22P164 0.22 Oil Incubation 64 -0.0995650111648 0.321208450137
22BL64 0.22 Control 64 0.344181403614 0.011496893707
45P29 0.45 Oil Incubation 9 -0.139337303592 -0.154032242023
22P216 0.22 Oil Incubation 16 -0.182624942475 0.036656544869
22P30 0.22 Oil Incubation 0 0.232890938751 -0.0365286035332
45P23 0.45 Oil Incubation 3 0.335212340096 0.00229714294784
22P364 0.22 Oil Incubation 64 -0.0265850037098 0.267838399813
45P26 0.45 Oil Incubation 6 -0.0663530024752 -0.123614294282
45P316 0.45 Oil Incubation 16 -0.180387066353 0.0244231332556
22P16 0.22 Oil Incubation 6 -0.0938690796601 -0.123292570064
22P13 0.22 Oil Incubation 3 -0.000929711149241 -0.0840936522112
22P36 0.22 Oil Incubation 6 -0.0846096566973 -0.126315336717
22P39 0.22 Oil Incubation 9 -0.145400678025 -0.171058987178
45P164 0.45 Oil Incubation 64 -0.160359423757 0.439794230436
22P19 0.22 Oil Incubation 9 -0.138575642598 -0.151960075733
45P313 0.45 Oil Incubation 13 -0.176079013758 0.050997652543
45BL64 0.45 Control 64 0.0288347544654 -0.1458771364
45P330 0.45 Oil Incubation 30 -0.11228777477 0.204236728786
45P36 0.45 Oil Incubation 6 -0.0761185616066 -0.121261486374
45P130 0.45 Oil Incubation 30 -0.094228858564 0.100652965768
22BL0 0.22 Control 0 0.239232948872 -0.036785772233
22P213 0.22 Oil Incubation 13 -0.18113904214 -0.0287178094404
22BL6 0.22 Control 6 -0.0600555194535 -0.194650371605
45P33 0.45 Oil Incubation 3 0.340399779328 0.0171852693215
45P30 0.45 Oil Incubation 0 0.431938929593 0.0196841881272
45BL6 0.45 Control 6 0.357256101911 -0.0188140900434
45BL9 0.45 Control 9 0.303457604982 -0.0443188527517
22P316 0.22 Oil Incubation 16 -0.164460159926 -0.0129812590712
22P313 0.22 Oil Incubation 13 -0.188614376178 0.00058901489101
45P39 0.45 Oil Incubation 9 -0.149217759045 -0.167311625113
22P131 0.22 Oil Incubation 30 -0.0651994575885 0.0656871734895
22BL31 0.22 Control 30 0.335856403002 0.0724160545763
45P19 0.45 Oil Incubation 9 -0.142421940226 -0.160880360066
22P331 0.22 Oil Incubation 30 -0.0500301022508 0.0416246477279
45BL0 0.45 Control 0 0.381611397751 0.0200030589204
22P113 0.22 Oil Incubation 13 -0.192581008392 -0.00938532222554
45P16 0.45 Oil Incubation 6 -0.085999339488 -0.121939087208
45BL3 0.45 Control 3 0.332023830601 0.036732406277
45P13 0.45 Oil Incubation 3 0.315664193595 0.0248256483492
45P216 0.45 Oil Incubation 16 -0.172909653606 0.030607355003
45P213 0.45 Oil Incubation 13 -0.18326004657 0.00570693606563
22P29 0.22 Oil Incubation 9 -0.150029591452 -0.16569360913
22P26 0.22 Oil Incubation 6 -0.110220935459 -0.134301793132
45P364 0.45 Oil Incubation 64 -0.100468231806 0.248528601323
45BL16 0.45 Control 16 0.341331109786 0.00915399605284
45BL13 0.45 Control 13 0.155782679403 -0.17960863481
45P230 0.45 Oil Incubation 30 -0.0452735875021 0.0316966419992
和代码：
PCoA <- read.delim(file.choose(), header=T)
attach(PCoA)
library(ggplot2)
PCoA$Time <- as.character(PCoA$Time)
PCoA$Filter <- as.character(PCoA$Filter)
cols <- c("0" = "red","3" = "blue","6" = "brown", "9" = "hotpink", "13" = "orange","16" = "olivedrab","30" = "azure3", "64" = "purple")
ggplot(PCoA, aes(x=Coord1, y=Coord2, shape=Type, colour=Time)) +
scale_colour_manual(values = cols, breaks=c("0","3","6","9","13","16","30","64")) +
geom_point(size=7) + xlab("PC1 (39.7%)") + ylab("PC2 (20.2%)") +
geom_hline(aes(yintercept=0)) + geom_vline(aes(xintercept=0)) +
theme(legend.text = element_text(size = 16),
legend.title = element_text(size=18),
axis.title.x = element_text(size=18, vjust=-0.7),
axis.title.y = element_text(size=18, vjust=2)) +
theme(axis.text = element_text(colour = "black", size="16")) +
theme(panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank(),
axis.line = element_line(colour = "white"))
你需要用对shapes (21:25) and to specify your fill. This post有一些很好的提示。虽然在这一点上，您的数据变得越来越难以用不同的轮廓和填充颜色来说明。 （也许可以将 Time 编码为填充，并为一个滤镜使用较浅的色调，为另一个滤镜使用较暗的色调 - 或者 - 使 Filter 键入轮廓颜色).
这是你编辑的图表：
- 数据格式编码
as.character() 在 ggplot 中而不是在
原始数据框。
scale_parameter_manual()- 填充定义在
aes()
- shape 和 fill 添加为最后一行
- 填充 使用
override.aes 修复的图例
ggplot(PCoA, aes(x=Coord1, y=Coord2, shape=as.character(Type), colour=as.character(Time), fill=as.character(Filter) )) + #Edit
scale_colour_manual(name="Time", values = cols, breaks=c("0","3","6","9","13","16","30","64")) + #Edit
geom_point(size=7) + xlab("PC1 (39.7%)") + ylab("PC2 (20.2%)") +
geom_hline(aes(yintercept=0)) + geom_vline(aes(xintercept=0)) +
theme(legend.text = element_text(size = 16),
legend.title = element_text(size=18),
axis.title.x = element_text(size=18, vjust=-0.7),
axis.title.y = element_text(size=18, vjust=2)) +
theme(axis.text = element_text(colour = "black", size="16")) +
theme(panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank(),
axis.line = element_line(colour = "white")) +
scale_shape_manual(name="Type", values=c(21,24)) + #Edit
scale_fill_manual(name="Filter", values=c("black", "white")) + #Edit
guides(fill = guide_legend(override.aes = list( #Edit
fill = c("black", "white"), #Edit
shape=22, #Edit
colour="black") )) #Edit
你的原图+编辑图：
编辑
OP询问如何对填充进行微调，使变量1定义的填充由变量2决定，即如果变量2是A，则点被颜色填充，但如果变量2是B，则所有的点都是白色的。由于第三个变量决定了形状，这增加了额外的复杂性。
有几个可能的解决方案：
- 通过
aes(shape=interaction(Variable2, Variable3)) 组合变量并指定仅允许颜色 (15:20) 和颜色+填充 (21:25) 的形状。
- 比 #1 更精简但控制更少的是指定具有空心中心 (0:6) 而不是填充中心 (21:25) 的形状。那么
fill就不用定义了。
- 加载库（缩放）并设置填充 alpha 属性（最后一个示例 here），即
scale_fill_manual(values = alpha(c("blue", "red"), .3))
（此解决方案对于此示例可能不可行。）
- 分别绘制点和美学：即
geom_point(data= subset, aes())
方法 #1：
ggplot(PCoA, aes(x=Coord1, y=Coord2,
shape=interaction(as.character(Type), Filter),
colour=as.character(Time),
fill=as.character(Time) )) + #Edit
scale_colour_manual(name="Time", values = cols,
breaks=c("0","3","6","9","13","16","30","64")) + #Edit
geom_point(size=7) + xlab("PC1 (39.7%)") + ylab("PC2 (20.2%)") +
geom_hline(aes(yintercept=0)) + geom_vline(aes(xintercept=0)) +
theme(legend.text = element_text(size = 16),
legend.title = element_text(size=18),
axis.title.x = element_text(size=18, vjust=-0.7),
axis.title.y = element_text(size=18, vjust=2),
legend.key = element_rect(fill=NA)) + #Edit
theme(axis.text = element_text(colour = "black", size="16")) +
theme(panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank(),
axis.line = element_line(colour = "white")) +
scale_shape_manual(name="Type/Filter", values=c(21, 16, 24, 17),
labels=c("Control, 0.22", "Incubation, 0.22",
"Control, 0.45", "Incubation, 0.45") ) + #Edit
scale_fill_manual(name="Filter", values=rep("white", length(cols)), guide=FALSE ) #Edit
我想制作一个带有形状、颜色和填充的散点图作为我的数据的编码。一切看起来形状和颜色都很好，但是填充选项似乎没有响应。我已经检查过与该主题类似的其他帖子，但仍然无法弄清楚如何处理这个问题。在我的案例中，我想要的是根据两种不同的过滤器尺寸（0.22=空心，0.45=实心）填充的过滤器列，以及根据我的时间着色的所有内容。 请找到我使用的数据集和代码，
Samples Filter Type Time Coord1 Coord2
45P116 0.45 Oil Incubation 16 -0.177125327477 0.0329641384336
22P264 0.22 Oil Incubation 64 -0.036421737819 0.41278336259
45P113 0.45 Oil Incubation 13 -0.183501817053 -0.0333774595889
45BL30 0.45 Control 30 -0.0169216562011 -0.160467270544
22P231 0.22 Oil Incubation 30 -0.0742549515959 0.134945242558
22P116 0.22 Oil Incubation 16 -0.168257444167 0.0425318235085
22P164 0.22 Oil Incubation 64 -0.0995650111648 0.321208450137
22BL64 0.22 Control 64 0.344181403614 0.011496893707
45P29 0.45 Oil Incubation 9 -0.139337303592 -0.154032242023
22P216 0.22 Oil Incubation 16 -0.182624942475 0.036656544869
22P30 0.22 Oil Incubation 0 0.232890938751 -0.0365286035332
45P23 0.45 Oil Incubation 3 0.335212340096 0.00229714294784
22P364 0.22 Oil Incubation 64 -0.0265850037098 0.267838399813
45P26 0.45 Oil Incubation 6 -0.0663530024752 -0.123614294282
45P316 0.45 Oil Incubation 16 -0.180387066353 0.0244231332556
22P16 0.22 Oil Incubation 6 -0.0938690796601 -0.123292570064
22P13 0.22 Oil Incubation 3 -0.000929711149241 -0.0840936522112
22P36 0.22 Oil Incubation 6 -0.0846096566973 -0.126315336717
22P39 0.22 Oil Incubation 9 -0.145400678025 -0.171058987178
45P164 0.45 Oil Incubation 64 -0.160359423757 0.439794230436
22P19 0.22 Oil Incubation 9 -0.138575642598 -0.151960075733
45P313 0.45 Oil Incubation 13 -0.176079013758 0.050997652543
45BL64 0.45 Control 64 0.0288347544654 -0.1458771364
45P330 0.45 Oil Incubation 30 -0.11228777477 0.204236728786
45P36 0.45 Oil Incubation 6 -0.0761185616066 -0.121261486374
45P130 0.45 Oil Incubation 30 -0.094228858564 0.100652965768
22BL0 0.22 Control 0 0.239232948872 -0.036785772233
22P213 0.22 Oil Incubation 13 -0.18113904214 -0.0287178094404
22BL6 0.22 Control 6 -0.0600555194535 -0.194650371605
45P33 0.45 Oil Incubation 3 0.340399779328 0.0171852693215
45P30 0.45 Oil Incubation 0 0.431938929593 0.0196841881272
45BL6 0.45 Control 6 0.357256101911 -0.0188140900434
45BL9 0.45 Control 9 0.303457604982 -0.0443188527517
22P316 0.22 Oil Incubation 16 -0.164460159926 -0.0129812590712
22P313 0.22 Oil Incubation 13 -0.188614376178 0.00058901489101
45P39 0.45 Oil Incubation 9 -0.149217759045 -0.167311625113
22P131 0.22 Oil Incubation 30 -0.0651994575885 0.0656871734895
22BL31 0.22 Control 30 0.335856403002 0.0724160545763
45P19 0.45 Oil Incubation 9 -0.142421940226 -0.160880360066
22P331 0.22 Oil Incubation 30 -0.0500301022508 0.0416246477279
45BL0 0.45 Control 0 0.381611397751 0.0200030589204
22P113 0.22 Oil Incubation 13 -0.192581008392 -0.00938532222554
45P16 0.45 Oil Incubation 6 -0.085999339488 -0.121939087208
45BL3 0.45 Control 3 0.332023830601 0.036732406277
45P13 0.45 Oil Incubation 3 0.315664193595 0.0248256483492
45P216 0.45 Oil Incubation 16 -0.172909653606 0.030607355003
45P213 0.45 Oil Incubation 13 -0.18326004657 0.00570693606563
22P29 0.22 Oil Incubation 9 -0.150029591452 -0.16569360913
22P26 0.22 Oil Incubation 6 -0.110220935459 -0.134301793132
45P364 0.45 Oil Incubation 64 -0.100468231806 0.248528601323
45BL16 0.45 Control 16 0.341331109786 0.00915399605284
45BL13 0.45 Control 13 0.155782679403 -0.17960863481
45P230 0.45 Oil Incubation 30 -0.0452735875021 0.0316966419992
和代码：
PCoA <- read.delim(file.choose(), header=T)
attach(PCoA)
library(ggplot2)
PCoA$Time <- as.character(PCoA$Time)
PCoA$Filter <- as.character(PCoA$Filter)
cols <- c("0" = "red","3" = "blue","6" = "brown", "9" = "hotpink", "13" = "orange","16" = "olivedrab","30" = "azure3", "64" = "purple")
ggplot(PCoA, aes(x=Coord1, y=Coord2, shape=Type, colour=Time)) +
scale_colour_manual(values = cols, breaks=c("0","3","6","9","13","16","30","64")) +
geom_point(size=7) + xlab("PC1 (39.7%)") + ylab("PC2 (20.2%)") +
geom_hline(aes(yintercept=0)) + geom_vline(aes(xintercept=0)) +
theme(legend.text = element_text(size = 16),
legend.title = element_text(size=18),
axis.title.x = element_text(size=18, vjust=-0.7),
axis.title.y = element_text(size=18, vjust=2)) +
theme(axis.text = element_text(colour = "black", size="16")) +
theme(panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank(),
axis.line = element_line(colour = "white"))
你需要用对shapes (21:25) and to specify your fill. This post有一些很好的提示。虽然在这一点上，您的数据变得越来越难以用不同的轮廓和填充颜色来说明。 （也许可以将 Time 编码为填充，并为一个滤镜使用较浅的色调，为另一个滤镜使用较暗的色调 - 或者 - 使 Filter 键入轮廓颜色).
这是你编辑的图表：
- 数据格式编码
as.character()在 ggplot 中而不是在 原始数据框。 scale_parameter_manual() 中指定的图例名称
- 填充定义在
aes() - shape 和 fill 添加为最后一行
- 填充 使用
override.aes 修复的图例
ggplot(PCoA, aes(x=Coord1, y=Coord2, shape=as.character(Type), colour=as.character(Time), fill=as.character(Filter) )) + #Edit
scale_colour_manual(name="Time", values = cols, breaks=c("0","3","6","9","13","16","30","64")) + #Edit
geom_point(size=7) + xlab("PC1 (39.7%)") + ylab("PC2 (20.2%)") +
geom_hline(aes(yintercept=0)) + geom_vline(aes(xintercept=0)) +
theme(legend.text = element_text(size = 16),
legend.title = element_text(size=18),
axis.title.x = element_text(size=18, vjust=-0.7),
axis.title.y = element_text(size=18, vjust=2)) +
theme(axis.text = element_text(colour = "black", size="16")) +
theme(panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank(),
axis.line = element_line(colour = "white")) +
scale_shape_manual(name="Type", values=c(21,24)) + #Edit
scale_fill_manual(name="Filter", values=c("black", "white")) + #Edit
guides(fill = guide_legend(override.aes = list( #Edit
fill = c("black", "white"), #Edit
shape=22, #Edit
colour="black") )) #Edit
你的原图+编辑图：
编辑
OP询问如何对填充进行微调，使变量1定义的填充由变量2决定，即如果变量2是A，则点被颜色填充，但如果变量2是B，则所有的点都是白色的。由于第三个变量决定了形状，这增加了额外的复杂性。
有几个可能的解决方案：
- 通过
aes(shape=interaction(Variable2, Variable3))组合变量并指定仅允许颜色 (15:20) 和颜色+填充 (21:25) 的形状。 - 比 #1 更精简但控制更少的是指定具有空心中心 (0:6) 而不是填充中心 (21:25) 的形状。那么
fill就不用定义了。 - 加载库（缩放）并设置填充 alpha 属性（最后一个示例 here），即
scale_fill_manual(values = alpha(c("blue", "red"), .3))（此解决方案对于此示例可能不可行。） - 分别绘制点和美学：即
geom_point(data= subset, aes())
方法 #1：
ggplot(PCoA, aes(x=Coord1, y=Coord2,
shape=interaction(as.character(Type), Filter),
colour=as.character(Time),
fill=as.character(Time) )) + #Edit
scale_colour_manual(name="Time", values = cols,
breaks=c("0","3","6","9","13","16","30","64")) + #Edit
geom_point(size=7) + xlab("PC1 (39.7%)") + ylab("PC2 (20.2%)") +
geom_hline(aes(yintercept=0)) + geom_vline(aes(xintercept=0)) +
theme(legend.text = element_text(size = 16),
legend.title = element_text(size=18),
axis.title.x = element_text(size=18, vjust=-0.7),
axis.title.y = element_text(size=18, vjust=2),
legend.key = element_rect(fill=NA)) + #Edit
theme(axis.text = element_text(colour = "black", size="16")) +
theme(panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank(),
axis.line = element_line(colour = "white")) +
scale_shape_manual(name="Type/Filter", values=c(21, 16, 24, 17),
labels=c("Control, 0.22", "Incubation, 0.22",
"Control, 0.45", "Incubation, 0.45") ) + #Edit
scale_fill_manual(name="Filter", values=rep("white", length(cols)), guide=FALSE ) #Edit