r - 来自预先计算值的 ggplot errorbars

Question

是否可以在 ggplot 条形图上“逐列”绘制预先计算值的误差线？

鉴于以下情况:

require(ggplot2)
library("ggplot2")
require(reshape2)
library("reshape2")

df <- structure(list(PVC1 = 0.4019026, PVC2 = 0.4479259, PVC3 = 0.4494118, PVC4 = 0.4729437,
                 PVC5 = 0.4800556, PVC6 = 0.449229, PVC7 = 0.4905295, PVC8 = 0.4457566,
                 PVC9 = 0.4271259, PVC10 = 0.4850341, PVC11 = 0.4369965, PVC12 = 0.4064052,
                 PVC13 = 0.3743776, PVC14 = 0.3603853, PVC15 = 0.3965469, PVC16 = 0.365461),
                .Names = c("PVC1","PVC2","PVC3","PVC4","PVC5","PVC6","PVC7","PVC8",
                           "PVC9","PVC10","PVC11","PVC12","PVC13","PVC14","PVC15","PVC16"),
                class = "data.frame",
                row.names = c(NA, -1L)
            )

melted_df <- melt(df, variable.name = "Locus", value.name = "GC")
st_dev <- c(0.023031363,    0.024919217,    0.017371129,
        0.019008759,    0.026650605,    0.026904926,
        0.024227542,    0.017767553,    0.026152478,
        0.039770898,    0.023929714,    0.028845442,
        0.015572219,    0.024967336,    0.014955416,    0.024569096)



gc_chart <- ggplot(melted_df, aes(Locus, GC*100, fill=Locus,)) +
                geom_bar(stat = "identity")
gc_chart <- gc_chart + ylab("GC Content (%)")
gc_chart <- gc_chart + theme(axis.text.x = element_text(angle=45, hjust=1))
gc_chart <- gc_chart + geom_abline(intercept=40.8891366,
                               slope=0,
                               colour="blue",
                               linetype="dashed")
gc_chart <- gc_chart + coord_cartesian(ylim=c(0,60))
gc_chart

生成此条形图:

我希望能够在图中相应的列上绘制我预先计算的 st devs 的每个值。

这可以通过提供 geom_errorbar 向量来完成吗？或者首先在数据框中包含 st dev 信息可能更容易？

(顺便说一句，我没有让 R 来计算 st dev 本身的原因是我已经在图表上绘制了平均值，所以 R 没有数据来计算它)

Answer 1

如果可能的话，我认为这是不值得推荐的。特别是当您需要 melted_df 的 GC 值来计算 ymin 和 ymax 值时。但是如果出于某种原因想要避免修改 melted_df，你总是可以这样做:

gc_chart + 
  geom_errorbar(aes(Locus, 
                    ymin = (GC - cbind(melted_df, st_dev)$st_dev)*100, 
                    ymax = (GC + cbind(melted_df, st_dev)$st_dev)*100))