我正在绘制不同细胞因子水平的浓度，这些浓度在范围上有很大差异。来自scales::pretty_breaks在y轴上的结果是不可取的。有两个问题。
设置n=2时，某些图形仅显示1个刻度，而不显示2个。
y轴刻度文本未正确对齐其图形。
dput()输出：
structure(list(Group = c(4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 8L,
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L,
8L, 8L, 8L, 8L, 8L, 8L, 8L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L,
19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L,
19L, 19L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L,
26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L), Cytokine = structure(c(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, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L), .Label = c("IL-1a",
"IL-1B", "IL-6", "MCP-1", "MIP-2", "TNFa"), class = "factor"),
Condition = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L,
3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 4L, 4L, 4L, 4L, 4L, 4L,
1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L,
2L, 2L, 2L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L, 1L,
3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 4L, 4L, 4L,
4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L,
2L, 2L, 2L, 2L, 2L, 2L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 1L,
1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L,
4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L,
3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 4L, 4L, 4L, 4L, 4L, 4L
), .Label = c("Ctrl", "T", "C", "T+C"), class = "factor"),
Replicate = structure(c(1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L,
1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L,
1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L,
1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L,
1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L,
1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L,
1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L,
1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L,
1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L,
1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L
), .Label = c("R1", "R2", "R3"), class = "factor"), CC = c(10.72,
11.22, 9.85, 10.55, 11.19, 10.32, 4.61, 11.47, 9.98, 21.26,
15.79, 15.79, 38.99, 36.52, 29.03, 11.47, 15.79, 10.73, 64.62,
65.26, 68.5, 15.79, 18.56, 12.94, 0, 0, 0, 0, 0, 0, 1.1,
11.74, 4.23, 2.44, 2.89, 3.33, 232.19, 265.2, 235.07, 69,
62.14, 64.89, 368.75, 392.6, 369.79, 93.46, 97.5, 80.59,
42.01, 39.91, 42.23, 40.67, 42.61, 37.33, 103.81, 44.19,
103.81, 243.55, 537.84, 124.58, 2173.46, 2548.97, 2185.7,
963.54, 1003.78, 850.73, 3775.81, 3599.65, 3677.04, 1056.31,
1222.84, 1043.28, 895.51, 896.82, 889.58, 926.93, 904.52,
907.48, 909.06, 936.17, 905.15, 928.47, 938.09, 865.52, 6024.45,
6204.68, 5986.87, 5019.31, 4750.06, 5062.42, 6624.21, 7237,
6808.59, 5490.35, 5790.21, 5210.26, 0, 0, 0, 0, 0, 0, 44.35,
44.35, 43.84, 53.25, 56.1, 55.63, 2927.83, 2978.39, 3205.55,
1976.48, 2001.29, 2029, 4563.38, 4556.54, 4694.97, 2470.94,
2479.96, 2396.81, 1.82, 2.32, 1.82, 2.19, 1.46, 1.42, 2.28,
2.32, 2.48, 0.4, 0.68, 0.31, 141.01, 149.87, 126.84, 64.72,
61.14, 63.1, 191.72, 189.05, 176.85, 80.3, 82.16, 70.85),
RK = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L,
2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L,
1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L,
2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L,
1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L,
2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L,
1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L,
2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L,
1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L,
2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L), .Label = c("0",
"6"), class = "factor")), row.names = c(NA, -144L), class = "data.frame")
图形代码：
ggplot(cytokineMain.df, aes(Condition, CC, fill=factor(RK)))+
geom_bar(position = "dodge", stat="summary", fun.y="mean", colour="black")+
facet_wrap(vars(Cytokine), ncol=2, scales="free_y")+
scale_x_discrete(breaks=c("Ctrl", "T", "C", "T+C"))+
scale_y_continuous(breaks = scales::pretty_breaks(2),expand = expand_scale(mult = c(.05, .25)))+
scale_fill_brewer(palette="Paired")+
theme_bw()+
theme(strip.background = element_rect(fill="white"))+
theme(
plot.title = element_text(hjust = 0.5),
panel.grid.major.x = element_blank(),
axis.title.x = element_blank(),
axis.text.x = element_text(),
axis.text.y = element_text(angle = 90),
axis.ticks = element_blank(),
axis.title.y = element_blank(),
legend.position = "none"
)
我希望所有图和y轴文本都具有更好的y轴折点，以使其与其对应的图正确对齐。
谢谢您的帮助。
