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我使用以下代码生成感兴趣的对比

Gene1.emmeans1 <- emmeans(Gene1.lm, pairwise ~ Treatment | Status)
Gene1.emmeans2 <- emmeans(Gene1.lm, pairwise ~ Status | Treatment, adjust="tukey")
Gene1.treatpval <- as.data.frame(Gene1.emmeans1$contrasts)
Gene1.statuspval <- as.data.frame(Gene1.emmeans2$contrasts)

> Gene1.treatpval
     contrast      Status   estimate        SE df    t.ratio    p.value
1 None - Treat1     Control -0.1951810 0.4243245 38 -0.4599806 0.64815130
2 None - Treat1 Subclinical  0.7600000 0.4382404 38  1.7342079 0.00198806
3 None - Treat1    Clinical -0.2054107 0.4243245 38 -0.4840888 0.63110121

> Gene1.statuspval
                contrast Treatment   estimate        SE df    t.ratio     p.value
1  Control - Subclinical      None -0.8213417 0.4382404 38 -1.8741807 0.160062190
2     Control - Clinical      None  0.7792297 0.4382404 38  1.7780872 0.190553770
3 Subclinical - Clinical      None  1.6005714 0.4382404 38  3.6522678 0.002203273
4  Control - Subclinical    Treat1  0.1338393 0.4243245 38  0.3154173 0.946712730
5     Control - Clinical    Treat1  0.7690000 0.4099364 38  1.8759008 0.159552669
6 Subclinical - Clinical    Treat1  0.6351607 0.4243245 38  1.4968750 0.303748340

如何将 emmeans 中的显着 p 值添加到我的 ggplot 中？作为包含四舍五入 p 值的括号还是（最好）星号？这是许多失败的尝试之一：

ggplot(Gene1.means, 
            aes(x=Status, y=AvgRQ, fill=Treatment)) +
        geom_bar(position=position_dodge(), stat="identity") +
        geom_errorbar(aes(ymin=AvgRQ-se, ymax=AvgRQ+se), width=0.2, position=position_dodge(0.9)) +
        ggtitle("Gene1") +
        theme_classic() +
        theme(plot.title = element_text(hjust=0.5)) +
        scale_fill_grey(start = 0.25, end = 0.8, na.value = "red", aesthetics = "fill") +
        ylab("Fold Change") +
        xlab("Status") +
  stat_pvalue_manual(
  comparisons=Gene1.treatpval, y.position = 3.5,
  label = "p.value",
  position = position_dodge(0.8))

这是我用来创建 ggplot 的数据：

> Gene1means
       Status Treatment Detector    AvgRQ        sd        se
1     Control      None    Gene1 3.653349 2.1593373 0.8161528
2     Control    Treat1    Gene1 2.562429 0.8453975 0.3195302
3 Subclinical      None    Gene1 2.445429 1.2227579 0.4621591
4 Subclinical    Treat1    Gene1 4.066000 1.5334035 0.5795721
5    Clinical      None    Gene1 2.939667 1.0487113 0.4281346
6    Clinical    Treat1    Gene1 3.252429 1.5754542 0.5954657

会话信息：

> sessionInfo()
R version 3.6.1 (2019-07-05)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Catalina 10.15.5
> rstudioapi::versionInfo()
$version
[1] ‘1.2.5042’
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