R/FacetMuiPlotReBoxBar.R

In taowenmicro/EasyAovWlxPlot:

# \item{data}{输入数据框，第一列为样本编号，第二列为分组，注意分组标签必须设定为group，第三列以后就是测定或者收集的指标了}
#
# \item{num}{代表您想要进行统计的列,这里可以输入多个列，只需要指定列号即可：例如：num = c(4:6)}
#
# \item{sig_show}{代表差异展示方式；sig_show ="abc"是使用字母表示;sig_show ="line"是使用连线和星号表示；如果是NA，那么就不显示显著性结果}
#
# \item{result}{代表显著性差异分析结果，是一个数据框，每一列是显著性标记字母,MuiKwWlx}
# \item{ncol}{代表分面展示每一行放几张图}


# Hello, world!
#
# This is an example function named 'hello'
# which prints 'Hello, world!'.
#
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# # #使用案例
# result = MuiKwWlx(data = data_wt,num = c(4:6))
# result
# #
# result1 = FacetMuiPlotReBoxBar (data = data_wt,num = c(4:6),result = result,sig_show ="abc",ncol = 2 )
# result1[[1]]






##------------现在我们需要多组分面出图---分为两种，--第一种箱线图--
# data = data_wt
# num = c(4:6)
# result = result
# sig_show ="abc"
# ncol = 2






FacetMuiPlotReBoxBar = function(data = data_wt,num = c(4:6),result = result,sig_show ="abc",ncol = 3 ){
  Mytheme <- theme_bw()+

    # scale_fill_manual(values = mi, guide = guide_legend(title = NULL))+
    theme(

      panel.grid.major=element_blank(),
      panel.grid.minor=element_blank(),

      plot.title = element_text(vjust = -8.5,hjust = 0.1),
      axis.title.y =element_text(size = 20,face = "bold",colour = "black"),
      axis.title.x =element_text(size = 24,face = "bold",colour = "black"),
      axis.text = element_text(size = 20,face = "bold"),
      axis.text.x = element_text(colour = "black",size = 14),
      axis.text.y = element_text(colour = "black",size = 14),
      legend.text = element_text(size = 15,face = "bold"),
      legend.position = "none"#是否删除图例

    )

  data_wt1 = data
  # N = num[1]
  # name = colnames(data_wt1[N])
  # as = result[match( name,colnames(result))]
  #
  # colnames(as) = "groups"
  # as$group = row.names(as)
  #
  # PlotresultBox = aovMuiBoxP(data = data_wt1, i= N,sig_show =sig_show,result = as)
  #
  # p = PlotresultBox[[2]]
  # p
  #
  #
  # # if (dim(as)[1]>3){p = p + theme(axis.text.x=element_text(angle=45,vjust=1, hjust=1))}
  #
  # name = colnames(data_wt1[N])
  # p$name = name
  # A = p
  # N= 4
  for (N in num) {

    name = colnames(data_wt1[N])

    as = result[match( name,colnames(result))]
    # as = result[c(N - length(num))]
    as
    colnames(as) = "groups"
    as$group = row.names(as)

    PlotresultBox = aovMuiBoxP(data = data_wt1, i= N,sig_show =sig_show,result =as)

    p = PlotresultBox[[2]]
    p
    name = colnames(data_wt1[N])
    p$name = name

    if (N == num[1]) {
      A = p
    }
    if (N != num[1]) {
      A = rbind(A,p)
    }


  }
  head(A)
  library(dplyr)
  iris_groups<- group_by(A, group,name)
  databar<- dplyr::summarise(iris_groups, mean(dd), sd(dd))
  colnames(databar) = c("group","name","mean","sd")

  head(databar)
  p = ggplot(A) +
    geom_bar(data = databar,aes(x= group,y = mean,fill = group),stat = "identity", width = 0.4,position = "dodge",colour= "black") +
    geom_text(data=A, aes(x=group , y=y ,label=stat))+
    geom_errorbar(data = databar,aes(x= group,y = mean,ymin=mean -sd, ymax=mean +sd),colour="black",width=0.1,size = 1)+
    geom_jitter(aes(x=group, y=dd, fill=group),A,position=position_jitter(0.17), size=4, alpha=0.7,pch = 21,color = "black")+
    labs(x="", y="")+
   facet_wrap(.~name,scales="free_y",ncol  = ncol)
  p

  p

  # path = "./Muibox_Facet/"
  # dir.create(path)
  # FileName <- paste(path,name,"Facet_box", ".pdf", sep = "_")
  # ggsave(FileName, p, width = 8, height = 8)

  return(list(p,table = A,bartable = databar))
}