R绘制带误差棒和统计检验的柱状图和箱线图

数据格式：

#数据储存在gene_exp.csv文件里Gene A1 B1 C1Gene1 20.381824 20.381824 10.381824Gene1 21.96907 21.96907 11.96907Gene1 19.19391 19.19391 9.19391Gene2 0.532916 8.96025 30.00767639Gene2 0.00767639 8.02883 29.0406903Gene2  0.0406903  10.0192096  29.0192096

代码如下：

library(grafify)library(ggplot2)library(ggsignif)
dt <- read.csv('gene_exp.csv')dt1 <- reshape2::melt(dt, id.vars = 'Gene',                      variable.name = 'Type',                      value.name = 'Value')#柱状图plot_scatterbar_sd(data = dt1,                   xcol = Type,                               ycol = Value,                   symsize = 3, fontsize = 13, # symsize: 散点的大小; fontsize: 字体大小                   bwid = 0.6, ewid = 0.4,# bwid: 条形的宽度; # ewid: 误差线的宽度                   b_alpha = 0.5, s_alpha = 0.8,# b_alpha: 条形的透明度 # s_alpha: 散点的透明度                   jitter = 0.2, # jitter: 数据点的抖动量                   ColPal = 'okabe_ito')   # ColPal: 颜色调色板                   labs(title = 'scatterbar_sd')                     facet_wrap('Gene')   #根据'Gene'列分面        geom_signif(mapping = aes(x = Type, y = Value),  # 显著性线的映射              comparisons = list(c('A1', 'B1'), c('B1', 'C1'), c('A1', 'C1')),  # 两两比较              map_signif_level = TRUE,  # 映射显著性水平              tip_length = c(0, 0, 0),  # 显著性线的长度              y_position = c(28, 29.5, 31),  # 显著性线的纵坐标位置              size = 0.5,  # 显著性线的粗细              textsize = 4,  # 显著性标记的大小              test = 't.test')#散点图plot_scatterbox(data = dt1,                xcol = Type,                ycol = Value,                symsize = 3, fontsize = 13,                bwid = 0.6, ewid = 0.4,                b_alpha = 0.5, s_alpha = 0.8,                jitter = 0.2,                ColPal = 'okabe_ito')                  labs(title = 'plot_scatterbox')                  facet_wrap('Gene')            geom_signif(mapping = aes(x = Type, y = Value),              comparisons = list(c('A1', 'B1'), c('B1', 'C1'), c('A1', 'C1')),              map_signif_level = TRUE,              tip_length = c(0, 0, 0),              y_position = c(28, 29.5, 31),              size = 0.5,              textsize = 4,              test = 't.test')

输出结果：