将带有线条的自定义元素添加到 ggplot 对象？
Add a custom element with lines to a ggplot object?
我使用 ggplot2 绘制了 Kaplan Meier 图，表示 3 组患者之间的无病生存率（以 % 为单位）：未暴露于风险因素的患者 (No exposure)，暴露于风险因素 1 (Exposure 1) 或暴露于风险因素 2 (Exposure 2) 的人。数据和图表如下所示：
# Load packages
library(tidyverse)
library(magrittr)
# Get data.
data <-
structure(list(time = c(15.4661190965092, 14.2340862422998, 14.8501026694045,
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"Exposure 3", "Exposure 1", "Exposure 2", "Exposure 2", "Exposure 3",
"Exposure 1", "Exposure 1", "Exposure 3", "Exposure 2", "Exposure 1",
"Exposure 1", "Exposure 1", "Exposure 3", "Exposure 2", "Exposure 3",
"Exposure 3", "Exposure 3", "Exposure 3", "Exposure 1", "Exposure 1",
"Exposure 1", "Exposure 1", "Exposure 1", "Exposure 1", "Exposure 1",
"Exposure 1", "Exposure 1", "Exposure 3", "Exposure 2", "Exposure 1",
"Exposure 1", "Exposure 2", "Exposure 1", "Exposure 2", "Exposure 1",
"Exposure 3", "Exposure 2", "Exposure 1", "Exposure 1", "Exposure 1",
"Exposure 3", "Exposure 2", "Exposure 3", "Exposure 1", "Exposure 1",
"Exposure 1", "Exposure 2", "Exposure 2", "Exposure 2", "Exposure 2",
"Exposure 1", "Exposure 3", "Exposure 1", "Exposure 2", "Exposure 1",
"Exposure 2", "Exposure 1", "Exposure 1", "Exposure 2", "Exposure 1",
"Exposure 1", "Exposure 1", "Exposure 3", "Exposure 3", "Exposure 1",
"Exposure 3", "Exposure 2", "Exposure 1", "Exposure 3", "Exposure 1",
"Exposure 3", "Exposure 3", "Exposure 1", "Exposure 3", "Exposure 1",
"Exposure 2", "Exposure 3", "Exposure 3", "Exposure 2", "Exposure 1",
"Exposure 1", "Exposure 1", "Exposure 1", "Exposure 3", "Exposure 2",
"Exposure 2", "Exposure 3", "Exposure 1", "Exposure 2", "Exposure 3",
"Exposure 3", "Exposure 1", "Exposure 1", "Exposure 2", "Exposure 2",
"Exposure 3", "Exposure 3", "Exposure 2", "Exposure 3", "Exposure 3",
"Exposure 2", "Exposure 1", "Exposure 1", "Exposure 2", "Exposure 3",
"Exposure 1", "Exposure 1", "Exposure 1", "Exposure 1", "Exposure 3",
"Exposure 1", "Exposure 1", "Exposure 1", "Exposure 2", "Exposure 1",
"Exposure 3", "Exposure 2", "Exposure 1", "Exposure 3", "Exposure 1",
"Exposure 2", "Exposure 3", "Exposure 1", "Exposure 2", "Exposure 1",
"Exposure 1", "Exposure 1", "Exposure 2", "Exposure 1", "Exposure 1",
"Exposure 2", "Exposure 2", "Exposure 3", "Exposure 3", "Exposure 1",
"Exposure 1", "Exposure 1", "Exposure 3", "Exposure 3", "Exposure 1",
"Exposure 1", "Exposure 1", "Exposure 1", "Exposure 2", "Exposure 2",
"Exposure 1", "Exposure 3", "Exposure 1", "Exposure 3")), class = "data.frame", row.names = c(NA,
-200L))
# Make the plot:
data %>%
ggplot(aes(x=time, y=surv)) +
geom_line(aes(color=group), size=0.3) +
scale_y_continuous(name="Disease-free survival (%)") +
scale_x_continuous(name="Follow-up time (years)") +
scale_color_manual(name="Groups",
values=c("Exposure 1"="firebrick3", "Exposure 2"="#255B1D", "Exposure 3"="darkblue"),
labels=c("Exposure 1 (p<.01)", "Exposure 2 (p=.02)", "Exposure 3 (p=.03)")) +
theme_classic() +
theme(legend.position=c(0.3, 0.3))
这会产生以下情节：
在此图中，p 值表示每组与未暴露组之间的生存差异（使用对数秩检验）。现在我还比较了两个暴露组 Exposure 1 和 Exposure 2 之间的生存率，其 p 值为 p=.01。我想通过以下方式将其添加到情节中：
我已经在 Paint 中完成了这个（非常丑陋的）改编，但我希望能够在 R 中完成。有帮助吗？
也许最简单的方法是绘制您自己的图例，这样您就无需猜测将线条放在哪里，并且在绘图调整大小时相对位置保持不变：
data %>%
ggplot(aes(x=time, y=surv)) +
geom_line(aes(color=group), size=0.3) +
scale_y_continuous(name = "Disease-free survival (%)") +
scale_x_continuous(name = "Follow-up time (years)") +
scale_color_manual(name = "Groups",
values=c("firebrick3", "#255B1D", "darkblue")) +
geom_line(data = data.frame(time = c(3.9, 5, 3.9, 5, 3.9, 5),
surv = c(84, 84, 83, 83, 82, 82),
group = rep(paste('Exposure', 1:3), each = 2)),
aes(color = group)) +
geom_text(data = data.frame(time = c(5.3, 5.3, 5.3, 10),
surv = c(84, 83, 82, 82.5),
group = c("No Exposure", "Exposure 1 (p = 0.02)",
"Exposure 2 (p = 0.03)", "p = 0.01")),
aes(label = group), hjust = 0, size = 3.2) +
geom_path(data = data.frame(time = c(9, 9.5, 9.5, 9),
surv = c(82, 82, 83, 83))) +
annotate('text', x = 3.8, y = 85.2, label = "Groups", hjust = 0, size = 4) +
theme_classic() +
theme(legend.position = 'none')
我使用 ggplot2 绘制了 Kaplan Meier 图，表示 3 组患者之间的无病生存率（以 % 为单位）：未暴露于风险因素的患者 (No exposure)，暴露于风险因素 1 (Exposure 1) 或暴露于风险因素 2 (Exposure 2) 的人。数据和图表如下所示：
# Load packages
library(tidyverse)
library(magrittr)
# Get data.
data <-
structure(list(time = c(15.4661190965092, 14.2340862422998, 14.8501026694045,
9.94934976043806, 4.5119780971937, 7.76454483230664, 12.3121149897331,
11.7344284736482, 15.6030116358658, 11.9123887748118, 13.9493497604381,
3.09377138945927, 9.97672826830938, 6.24229979466119, 11.0362765229295,
12.3805612594114, 9.28405201916495, 3.75633127994524, 6.88021902806297,
14.2614647501711, 1.95208761122519, 13.3744010951403, 10.4804928131417,
12.1149897330595, 11.668720054757, 11.211498973306, 5.50855578370979,
7.61396303901437, 0.939082819986311, 7.0362765229295, 12.911704312115,
16.0574948665298, 5.34702258726899, 13.3032169746749, 5.637234770705,
15.0800821355236, 14.1601642710472, 12.7638603696099, 15.6796714579055,
6.07802874743327, 15.2142368240931, 11.8001368925394, 2.92676249144422,
10.5051334702259, 10.072553045859, 15.9479808350445, 4.84052019164956,
4.36960985626283, 12.7775496235455, 15.0280629705681, 13.8891170431211,
2.2258726899384, 8.90622861054073, 14.7433264887064, 4.61875427789186,
2.81998631074606, 11.0225872689938, 7.67145790554415, 13.9958932238193,
9.27310061601643, 15.4496919917864, 11.8986995208761, 11.9972621492129,
13.7604380561259, 2.8993839835729, 5.82614647501711, 8.0684462696783,
13.4455852156057, 3.06091718001369, 10.9869952087611, 13.1471594798083,
14.1273100616016, 13.7577002053388, 6.88021902806297, 11.7973990417522,
10.3819301848049, 5.47843942505133, 14.2477754962355, 6.94045174537988,
9.94387405886379, 4.54483230663929, 8.18891170431212, 13.7960301163587,
8.27104722792608, 14.2422997946612, 14.5325119780972, 14.3655030800821,
14.072553045859, 3.64681724845996, 6.3791923340178, 10.5434633812457,
11.378507871321, 14.9322381930185, 14.0123203285421, 2.48323066392882,
14.8583162217659, 9.88364134154689, 12.145106091718, 15.5838466803559,
2.80082135523614, 12.9007529089665, 3.50718685831622, 13.3771389459274,
10.5379876796715, 15.2525667351129, 16.2299794661191, 16.1779603011636,
8.2217659137577, 15.315537303217, 11.7289527720739, 10.9568788501027,
13.2676249144422, 7.32375085557837, 11.6112251882272, 5.66735112936345,
15.7782340862423, 10.113620807666, 9.5523613963039, 1.83983572895277,
13.5003422313484, 9.6208076659822, 13.9575633127995, 10.9377138945927,
3.63860369609856, 10.4284736481862, 10.9678302532512, 13.4209445585216,
15.233401779603, 4.70088980150582, 12.4024640657084, 14.6830937713895,
13.2977412731006, 0.717316906228611, 12.9691991786448, 7.9315537303217,
15.6386036960986, 5.82340862422998, 1.0321697467488, 9.89459274469541,
15.0280629705681, 13.4483230663929, 10.6639288158795, 3.39493497604381,
12.3203285420945, 4.47364818617385, 14.839151266256, 14.2669404517454,
6.12183436002738, 13.2101300479124, 3.39493497604381, 15.9671457905544,
15.9479808350445, 11.9753593429158, 5.46475017111567, 15.9425051334702,
7.35934291581109, 5.87268993839836, 9.12525667351129, 15.2717316906229,
6.80082135523614, 14.8583162217659, 12.974674880219, 14.6967830253251,
13.5797399041752, 11.1321013004791, 3.87679671457906, 14.8336755646817,
12.5585215605749, 15.6988364134155, 7.60574948665298, 3.40041067761807,
15.9288158795346, 14.9733059548255, 15.066392881588, 10.2067077344285,
13.223819301848, 5.34976043805613, 12.0766598220397, 10.9787816563997,
11.9123887748118, 11.0581793292266, 14.5763175906913, 14.0533880903491,
4.95003422313484, 4.75290896646133, 14.009582477755, 11.2087611225188,
14.6776180698152, 15.4086242299795, 10.4421629021218, 6.7378507871321,
13.9466119096509, 4.22724161533196, 13.7960301163587, 15.7399041752225,
10.92128678987, 10.425735797399, 11.772758384668, 7.86036960985626,
2.16837782340862), surv = c(78.895930965634, 82.939817991606,
81.5385905661846, 90.8500347161838, 96.6504495720828, 91.58932785697,
84.5274669486008, 87.864369728858, 78.895930965634, 84.8697422025156,
85.3203796168142, 98.3662199572867, 90.7869444142976, 94.5490389303011,
89.2078379065114, 84.5274669486008, 90.2944085152522, 98.1562293390666,
93.3334692912905, 82.939817991606, 98.985749325359, 82.1548721677423,
90.2111674121547, 84.7006789710365, 87.9377122745415, 86.4721601677476,
95.7331254544023, 93.6935385308075, 99.6460813737672, 94.5056490644159,
83.2922253942863, 78.4769648802248, 95.964924789643, 87.1373174726556,
95.3815962299675, 80.6002593845599, 84.7887574138549, 83.4729026727989,
80.6002593845599, 95.9831917973004, 80.6002593845599, 89.7929243747343,
99.0875137586307, 90.2111674121547, 90.7238102387661, 76.5051451787966,
96.3102631366802, 97.7311888493258, 86.0777214686932, 78.895930965634,
83.8785010948376, 98.314751291989, 92.5659794066876, 83.781286869923,
98.2869267301137, 97.7713225402138, 89.2078379065114, 93.6351988430548,
81.2409555449192, 93.1602670358451, 80.6002593845599, 87.4920568725144,
87.3419845128403, 81.9494849873229, 99.0875137586307, 95.2639863702512,
91.0806705136385, 82.1548721677423, 97.661713434227, 89.2078379065114,
85.655814846093, 83.3214762866605, 84.4919464607611, 94.7936368159517,
87.7902851000815, 90.2763488914987, 96.7044696855362, 82.939817991606,
93.3334692912905, 92.5628179141593, 97.5706519561467, 93.1645493591,
86.0531379063549, 93.1645493591, 84.1840815183361, 82.3344918532314,
80.6200719805773, 84.7887574138549, 98.1562293390666, 95.363640324494,
90.1453198447006, 85.9984807940096, 83.781286869923, 81.2409555449192,
98.6774838813241, 81.5385905661846, 90.8500347161838, 88.9048039353159,
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82.1548721677423, 90.1453198447006, 83.781286869923, 78.4769648802248,
83.781286869923, 93.1645493591, 80.6002593845599, 89.7929243747343,
89.2760917993244, 85.2219677930458, 94.1584114615132, 85.2009723473868,
95.3815962299675, 80.6002593845599, 88.6666313027254, 92.7135716892638,
99.0367729074855, 82.1548721677423, 91.1603170857887, 81.2409555449192,
86.9365304945406, 98.1562293390666, 87.9644206553892, 89.2760917993244,
86.2760734967859, 78.895930965634, 96.3102631366802, 88.346042509788,
81.9649615708496, 85.1341100942901, 99.7978010383687, 85.9104175149211,
91.3354416199704, 83.781286869923, 97.331847814204, 99.2663520529959,
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83.781286869923, 91.129896217454, 90.2763488914987, 85.0368086241741,
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0.890969865852105, 0.88957952958382, 0.848186186145897, 0.997626828642714,
0.966575416650932, 0.930091761922735, 0.850013119366769, 0.986323210100933,
0.906857623787338, 0.873985856457408, 0.852605393948829, 0.863258994078296,
0.958092905110497, 0.893731093471867, 0.916737513612901, 0.975085413821684,
0.849191835758465, 0.949955393697625, 0.94513147369813, 0.982593420791875,
0.943309840601488, 0.888356323643571, 0.943309840601488, 0.8725021668835,
0.843895824110921, 0.836875343643832, 0.87753718628127, 0.987548441774093,
0.963209640942235, 0.91552718100721, 0.884544590766402, 0.869382689764604,
0.842011296235924, 0.991837766792364, 0.837232495866684, 0.922039251916947,
0.913219619173031, 0.869382689764604, 0.997626828642714, 0.904976959388002,
0.987548441774093, 0.850013119366769, 0.91552718100721, 0.869382689764604,
0.822834317521706, 0.869382689764604, 0.943309840601488, 0.830171586937913,
0.921001646781718, 0.907489287802726, 0.869981755030479, 0.952354822262432,
0.877359215164471, 0.967572522789849, 0.830171586937913, 0.908525095500321,
0.946438504405819, 0.994687377501161, 0.850013119366769, 0.924906149140602,
0.842011296235924, 0.892967267947796, 0.987548441774093, 0.902211540982596,
0.907489287802726, 0.890295659392204, 0.823717623193319, 0.975361120861275,
0.908326732466828, 0.840763169181104, 0.869170760069249, 0.999959484216824,
0.876336530756437, 0.932357022337168, 0.869382689764604, 0.984927637444616,
0.998093202674114, 0.922039251916947, 0.869382689764604, 0.850013119366769,
0.896974925284878, 0.988425715717517, 0.886716877859586, 0.993118901629567,
0.869382689764604, 0.839581954218875, 0.961503231045787, 0.901434657413618,
0.986323210100933, 0.823926502204367, 0.869382689764604, 0.88957952958382,
0.975565398383733, 0.869382689764604, 0.941268118848152, 0.972180082048895,
0.935063228824689, 0.830171586937913, 0.959126319042212, 0.823717623193319,
0.875557284612824, 0.840763169181104, 0.86416647611313, 0.929830429674193,
0.987106633980016, 0.823717623193319, 0.908326732466828, 0.830171586937913,
0.937961306403804, 0.988425715717517, 0.869382689764604, 0.823717623193319,
0.830171586937913, 0.94513147369813, 0.87159289389749, 0.976997640745795,
0.888875756734311, 0.93127100659334, 0.890969865852105, 0.906218647708942,
0.869382689764604, 0.87753718628127, 0.974407271055667, 0.975361120861275,
0.854677357338004, 0.903001357728714, 0.842411155753018, 0.823717623193319,
0.902211540982596, 0.959641198780709, 0.856688513674614, 0.984868490477327,
0.862339457520645, 0.869382689764604, 0.932698114912117, 0.916737513612901,
0.875881267415946, 0.945463531021287, 0.991369769199295), group = c("Exposure 3",
"Exposure 1", "Exposure 1", "Exposure 1", "Exposure 3", "Exposure 3",
"Exposure 3", "Exposure 1", "Exposure 3", "Exposure 3", "Exposure 2",
"Exposure 1", "Exposure 1", "Exposure 3", "Exposure 1", "Exposure 3",
"Exposure 3", "Exposure 1", "Exposure 3", "Exposure 1", "Exposure 1",
"Exposure 3", "Exposure 1", "Exposure 3", "Exposure 1", "Exposure 3",
"Exposure 3", "Exposure 1", "Exposure 1", "Exposure 1", "Exposure 3",
"Exposure 1", "Exposure 3", "Exposure 2", "Exposure 3", "Exposure 1",
"Exposure 2", "Exposure 3", "Exposure 1", "Exposure 1", "Exposure 1",
"Exposure 2", "Exposure 2", "Exposure 1", "Exposure 1", "Exposure 3",
"Exposure 3", "Exposure 1", "Exposure 1", "Exposure 3", "Exposure 1",
"Exposure 3", "Exposure 1", "Exposure 2", "Exposure 2", "Exposure 3",
"Exposure 1", "Exposure 1", "Exposure 3", "Exposure 2", "Exposure 1",
"Exposure 1", "Exposure 1", "Exposure 3", "Exposure 2", "Exposure 3",
"Exposure 3", "Exposure 3", "Exposure 3", "Exposure 1", "Exposure 1",
"Exposure 1", "Exposure 1", "Exposure 1", "Exposure 1", "Exposure 1",
"Exposure 1", "Exposure 1", "Exposure 3", "Exposure 2", "Exposure 1",
"Exposure 1", "Exposure 2", "Exposure 1", "Exposure 2", "Exposure 1",
"Exposure 3", "Exposure 2", "Exposure 1", "Exposure 1", "Exposure 1",
"Exposure 3", "Exposure 2", "Exposure 3", "Exposure 1", "Exposure 1",
"Exposure 1", "Exposure 2", "Exposure 2", "Exposure 2", "Exposure 2",
"Exposure 1", "Exposure 3", "Exposure 1", "Exposure 2", "Exposure 1",
"Exposure 2", "Exposure 1", "Exposure 1", "Exposure 2", "Exposure 1",
"Exposure 1", "Exposure 1", "Exposure 3", "Exposure 3", "Exposure 1",
"Exposure 3", "Exposure 2", "Exposure 1", "Exposure 3", "Exposure 1",
"Exposure 3", "Exposure 3", "Exposure 1", "Exposure 3", "Exposure 1",
"Exposure 2", "Exposure 3", "Exposure 3", "Exposure 2", "Exposure 1",
"Exposure 1", "Exposure 1", "Exposure 1", "Exposure 3", "Exposure 2",
"Exposure 2", "Exposure 3", "Exposure 1", "Exposure 2", "Exposure 3",
"Exposure 3", "Exposure 1", "Exposure 1", "Exposure 2", "Exposure 2",
"Exposure 3", "Exposure 3", "Exposure 2", "Exposure 3", "Exposure 3",
"Exposure 2", "Exposure 1", "Exposure 1", "Exposure 2", "Exposure 3",
"Exposure 1", "Exposure 1", "Exposure 1", "Exposure 1", "Exposure 3",
"Exposure 1", "Exposure 1", "Exposure 1", "Exposure 2", "Exposure 1",
"Exposure 3", "Exposure 2", "Exposure 1", "Exposure 3", "Exposure 1",
"Exposure 2", "Exposure 3", "Exposure 1", "Exposure 2", "Exposure 1",
"Exposure 1", "Exposure 1", "Exposure 2", "Exposure 1", "Exposure 1",
"Exposure 2", "Exposure 2", "Exposure 3", "Exposure 3", "Exposure 1",
"Exposure 1", "Exposure 1", "Exposure 3", "Exposure 3", "Exposure 1",
"Exposure 1", "Exposure 1", "Exposure 1", "Exposure 2", "Exposure 2",
"Exposure 1", "Exposure 3", "Exposure 1", "Exposure 3")), class = "data.frame", row.names = c(NA,
-200L))
# Make the plot:
data %>%
ggplot(aes(x=time, y=surv)) +
geom_line(aes(color=group), size=0.3) +
scale_y_continuous(name="Disease-free survival (%)") +
scale_x_continuous(name="Follow-up time (years)") +
scale_color_manual(name="Groups",
values=c("Exposure 1"="firebrick3", "Exposure 2"="#255B1D", "Exposure 3"="darkblue"),
labels=c("Exposure 1 (p<.01)", "Exposure 2 (p=.02)", "Exposure 3 (p=.03)")) +
theme_classic() +
theme(legend.position=c(0.3, 0.3))
这会产生以下情节：
在此图中，p 值表示每组与未暴露组之间的生存差异（使用对数秩检验）。现在我还比较了两个暴露组 Exposure 1 和 Exposure 2 之间的生存率，其 p 值为 p=.01。我想通过以下方式将其添加到情节中：
我已经在 Paint 中完成了这个（非常丑陋的）改编，但我希望能够在 R 中完成。有帮助吗？
也许最简单的方法是绘制您自己的图例，这样您就无需猜测将线条放在哪里，并且在绘图调整大小时相对位置保持不变：
data %>%
ggplot(aes(x=time, y=surv)) +
geom_line(aes(color=group), size=0.3) +
scale_y_continuous(name = "Disease-free survival (%)") +
scale_x_continuous(name = "Follow-up time (years)") +
scale_color_manual(name = "Groups",
values=c("firebrick3", "#255B1D", "darkblue")) +
geom_line(data = data.frame(time = c(3.9, 5, 3.9, 5, 3.9, 5),
surv = c(84, 84, 83, 83, 82, 82),
group = rep(paste('Exposure', 1:3), each = 2)),
aes(color = group)) +
geom_text(data = data.frame(time = c(5.3, 5.3, 5.3, 10),
surv = c(84, 83, 82, 82.5),
group = c("No Exposure", "Exposure 1 (p = 0.02)",
"Exposure 2 (p = 0.03)", "p = 0.01")),
aes(label = group), hjust = 0, size = 3.2) +
geom_path(data = data.frame(time = c(9, 9.5, 9.5, 9),
surv = c(82, 82, 83, 83))) +
annotate('text', x = 3.8, y = 85.2, label = "Groups", hjust = 0, size = 4) +
theme_classic() +
theme(legend.position = 'none')