请查看下面的
我的数据
。请注意,下面的图片是我希望复制的设计示例,并不与我的数据
具体相关。
我的数据
存储在p
中。我有一个连续的协变量p $ ki67pro
,它表示肿瘤样本中活跃分裂细胞的百分比(因此范围从0到100)。我有三个不同的肿瘤阶段,对应于p $ WHO.Grade==1,2,3
。每个样本代表一个肿瘤患者,其中有复发(p $ recurrence==1
)或没有复发(p $ recurrence==0
)。
因此:head(p)
WHO.Grade recurrence ki67pro
1 1 0 1
2 2 0 12
3 1 0 3
9 1 0 3
10 1 0 5
11 1 0 3
我希望能够制作如下的箱线图。您可以看到,每个 p$WHO.Grade
和 All samples
对应着四个点。每个 p$WHO.Grade
+ All
有两个箱线图。
p$WHO.Grade
和All
,我想要一个箱线图来代表复发肿瘤(p$recurrence==1
)的p$ki67pro
,另一个箱线图来代表非复发肿瘤(p$recurrence==0
)的p$ki67pro
。即:
p$ki67pro[p$WHO.Grade==1 & p$recurrence==0]
与p$ki67pro[p$WHO.Grade==1 & p$recurrence==1]
p$ki67pro[p$WHO.Grade==2 & p$recurrence==0]
与p$ki67pro[p$WHO.Grade==2 & p$recurrence==1]
p$ki67pro[p$WHO.Grade==3 & p$recurrence==0]
与p$ki67pro[p$WHO.Grade==3 & p$recurrence==1]
对于All
也是如此。
p$ki67pro[p$recurrence==0]
相对于 p$ki67pro[p$recurrence==1]
我目前使用了以下脚本,但是我不知道如何包含 All
。请注意,只有一种情况是 p$WHO.Grade==3
df <- data.frame(x = as.factor(c(p$WHO.Grade)),
y = c(p$ki67pro),
f = rep(c("ki67pro"), c(nrow(p))))
df <- df[!is.na(df$x),]
ggplot(df) +
geom_boxplot(aes(x, y, fill = f, colour = f), outlier.alpha = 0, position = position_dodge(width = 0.78)) +
scale_x_discrete(name = "", label=c("WHO-I","WHO-II","WHO-III","All")) +
scale_y_continuous(name="x", breaks=seq(0,30,5), limits=c(0,30)) +
stat_boxplot(aes(x, y, colour = f), geom = "errorbar", width = 0.3,position = position_dodge(0.7753)) +
geom_point(aes(x, y, fill = f, colour = f), size = 3, shape = 21, position = position_jitterdodge()) +
scale_fill_manual(values = c("#edf1f9", "#fcebeb"), name = "",
labels = c("", "")) +
scale_colour_manual(values = c("#1C73C2", "red"), name = "",
labels = c("","")) + theme(legend.position="none")
我的数据 p
p <- structure(list(WHO.Grade = c(1L, 2L, 1L, 1L, 1L, 1L, 3L, 2L,
1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
2L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L), recurrence = c(0L, 0L, 0L, 0L, 0L,
0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 1L, 0L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 0L,
1L, 1L, 0L, 1L, 0L, 0L, 1L, 1L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L,
1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L), ki67pro = c(1L, 12L,
3L, 3L, 5L, 3L, 20L, 25L, 7L, 4L, 5L, 12L, 3L, 15L, 4L, 5L, 7L,
8L, 3L, 12L, 10L, 4L, 10L, 7L, 3L, 2L, 3L, 7L, 4L, 7L, 10L, 4L,
5L, 5L, 3L, 5L, 2L, 5L, 3L, 3L, 3L, 4L, 4L, 3L, 2L, 5L, 1L, 5L,
2L, 3L, 1L, 2L, 3L, 3L, 5L, 4L, 20L, 5L, 0L, 4L, 3L, 0L, 3L,
4L, 1L, 2L, 20L, 2L, 3L, 5L, 4L, 8L, 1L, 4L, 5L, 4L, 3L, 6L,
12L, 3L, 4L, 4L, 2L, 5L, 3L, 3L, 3L, 2L, 5L, 4L, 2L, 3L, 4L,
3L, 3L, 2L, 2L, 4L, 7L, 4L, 3L, 4L, 2L, 3L, 6L, 2L, 3L, 10L,
5L, 10L, 3L, 10L, 3L, 4L, 5L, 2L, 4L, 3L, 4L, 4L, 4L, 5L, 3L,
12L, 5L, 4L, 3L, 2L, 4L, 3L, 4L, 2L, 1L, 6L, 1L, 4L, 12L, 3L,
4L, 3L, 2L, 6L, 5L, 4L, 3L, 4L, 4L, 4L, 3L, 5L, 4L, 5L, 4L, 1L,
3L, 3L, 4L, 0L, 3L)), class = "data.frame", row.names = c(1L,
2L, 3L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 18L, 19L, 20L,
21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L,
34L, 35L, 36L, 37L, 38L, 39L, 40L, 41L, 44L, 45L, 46L, 47L, 48L,
49L, 50L, 51L, 52L, 53L, 54L, 55L, 57L, 59L, 60L, 61L, 62L, 63L,
64L, 65L, 66L, 67L, 68L, 69L, 70L, 71L, 72L, 73L, 74L, 75L, 76L,
77L, 78L, 79L, 80L, 81L, 82L, 83L, 84L, 85L, 87L, 89L, 90L, 91L,
92L, 93L, 94L, 96L, 97L, 98L, 99L, 100L, 101L, 102L, 103L, 104L,
105L, 106L, 107L, 109L, 110L, 111L, 112L, 113L, 114L, 115L, 116L,
117L, 118L, 119L, 120L, 121L, 123L, 124L, 125L, 126L, 127L, 128L,
130L, 131L, 132L, 133L, 134L, 135L, 136L, 137L, 138L, 139L, 140L,
141L, 142L, 143L, 144L, 145L, 146L, 147L, 148L, 149L, 150L, 151L,
152L, 153L, 154L, 155L, 156L, 157L, 158L, 159L, 160L, 161L, 162L,
163L, 164L, 165L, 166L, 167L, 168L, 169L, 170L, 171L, 172L, 173L,
174L, 175L))