今天为了画这个cluster中怎么显示标签的图，研究了一个Seurat中怎么画这个图的，下面是学习过程中做的总结

运行例子

rm(list=ls())
library(Seurat)
library(SeuratData)
library(ggplot2)
library(patchwork)
pbmc3k.final <- LoadData("pbmc3k", type = "pbmc3k.final")
#print(DimPlot(pbmc3k.final,label = TRUE, repel = TRUE))

# remove the legend
p=DimPlot(pbmc3k.final,label = TRUE, repel = TRUE)+theme(legend.position = "none")
print(p)

结果如下
这个就是我想要达到的效果，把类别的标签放在类的中心显示，但是这个是Seurat包自己实现的，我要做的事就是把Seurat包的这个Dimplot函数给抽出来，变成自己的ggplot函数

调试

其中核心部分是下面两个函数
一个是SingleDimPlot函数, 另一个是LabelClusters函数，

首先发现Dimplot函数会进入函数SingleDimPlot函数，其函数实现如下
虽然这个函数看起来很复杂，其实大部分都是在判断条件，所以对于自己的需求而言，很多代码可以全删了，经过SingleDimPlot函数后，画出来的效果如图
可以看到，此时这个结果只是普普通通的ggplot画图，所以调整图例到细胞的类别中是在LabelClusters函数里, 其中LabelClusters函数实现如下

这个函数也是很多条件的，其实核心代码就那么几行, 大致看完这个代码之后，可以着手删代码来

自己实现

将Seurat对象转化到画图的csv文件

write.csv(data,file="./pbmc_UMAP.csv")

这里其实有一个问题，就是当把Seurat对象存成csv文件，然后再读入时，有些变量的格式是改变的，最常见的就是因子factor类型和chacracter类型，这个一定要注意，否则很容易出错, 比如在Seurat中，data的ident列是因子类型的
当我把pbmc_UMAP.csv重新读取进来时，该数据框各列的类型如下
可以看到，我重新读取进来的文件的ident列变成了character类型，这一点一定要多加注意，下面的代码也说明了这一点，需要额外进行类型转换

简化代码1

rm(list=ls())
setwd("/Users/yxk/Desktop/test/Seurat_label测试/")
suppressPackageStartupMessages(library(ggplot2))
suppressPackageStartupMessages(library(cowplot))
suppressPackageStartupMessages(library(ggrepel))

data = read.csv("./pbmc_UMAP.csv",row.names = 1) # 相当于python里面的index
plot <- ggplot(data = data)

col.by ="ident"

plot = plot + geom_point(mapping = aes_string(x = "UMAP_1", 
      y = "UMAP_2", color = paste0("`", col.by, "`"), shape = NULL, 
      alpha = NULL), size = 0.6000758)

plot <- plot + guides(color = guide_legend(override.aes = list(size = 3))) + 
labs(color = NULL, title = col.by) 

plot <- plot + theme_cowplot()
print(plot)


# clusters这个是有问题的
LabelClusters = function(plot, id, clusters = NULL, labels = NULL, split.by = NULL, 
  repel = TRUE, box = FALSE, geom = "GeomPoint", position = "median", 
  ...) 
{
#   xynames <- unlist(x = GetXYAesthetics(plot = plot, geom = geom), 
#     use.names = TRUE)
  xynames=c("UMAP_1","UMAP_2")
  names(xynames)=c("x","y")
  if (!id %in% colnames(x = plot$data)) {
    stop("Cannot find variable ", id, " in plotting data")
  }
  if (!is.null(x = split.by) && !split.by %in% colnames(x = plot$data)) {
    warning("Cannot find splitting variable ", id, " in plotting data")
    split.by <- NULL
  }
  data <- plot$data[, c(xynames, id, split.by)]
  possible.clusters <- as.character(x = na.omit(object = unique(x = data[, 
    id])))
  groups <- possible.clusters
    
  if (any(!groups %in% possible.clusters)) {
    stop("The following clusters were not found: ", paste(groups[!groups %in% 
      possible.clusters], collapse = ","))
  }
  pb <- ggplot_build(plot = plot)
  if (geom == "GeomSpatial") {
    xrange.save <- layer_scales(plot = plot)$x$range$range
    yrange.save <- layer_scales(plot = plot)$y$range$range
    data[, xynames["y"]] = max(data[, xynames["y"]]) - data[, 
      xynames["y"]] + min(data[, xynames["y"]])
    if (!pb$plot$plot_env$crop) {
      y.transform <- c(0, nrow(x = pb$plot$plot_env$image)) - 
        pb$layout$panel_params[[1]]$y.range
      data[, xynames["y"]] <- data[, xynames["y"]] + sum(y.transform)
    }
  }
  data <- cbind(data, color = pb$data[[1]][[1]])
  labels.loc <- lapply(X = groups, FUN = function(group) {
    data.use <- data[data[, id] == group, , drop = FALSE]
    data.medians <- if (!is.null(x = split.by)) {
      do.call(what = "rbind", args = lapply(X = unique(x = data.use[, 
        split.by]), FUN = function(split) {
        medians <- apply(X = data.use[data.use[, split.by] == 
          split, xynames, drop = FALSE], MARGIN = 2, 
          FUN = median, na.rm = TRUE)
        medians <- as.data.frame(x = t(x = medians))
        medians[, split.by] <- split
        return(medians)
      }))
    }
    else {
      as.data.frame(x = t(x = apply(X = data.use[, xynames, 
        drop = FALSE], MARGIN = 2, FUN = median, na.rm = TRUE)))
    }
    data.medians[, id] <- group
    data.medians$color <- data.use$color[1]
    return(data.medians)
  })
  if (position == "nearest") {
    labels.loc <- lapply(X = labels.loc, FUN = function(x) {
      group.data <- data[as.character(x = data[, id]) == 
        as.character(x[3]), ]
      nearest.point <- nn2(data = group.data[, 1:2], query = as.matrix(x = x[c(1, 
        2)]), k = 1)$nn.idx
      x[1:2] <- group.data[nearest.point, 1:2]
      return(x)
    })
  }
  labels.loc <- do.call(what = "rbind", args = labels.loc)
#   labels.loc[, id] <- factor(x = labels.loc[, id], levels = levels(data[, 
#     id]))
  labels.loc$'ident'= as.factor(labels.loc$'ident') 
    
  labels <-  groups
  if (length(x = unique(x = labels.loc[, id])) != length(x = labels)) {
    stop("Length of labels (", length(x = labels), ") must be equal to the number of clusters being labeled (", 
      length(x = labels.loc), ").")
  }
  names(x = labels) <- groups
  for (group in groups) {
    labels.loc[labels.loc[, id] == group, id] <- labels[group]
  }
  #print(labels.loc)
  if (box) {
    geom.use <- ifelse(test = repel, yes = geom_label_repel, 
      no = geom_label)
    plot <- plot + geom.use(data = labels.loc, mapping = aes_string(x = xynames["x"], 
      y = xynames["y"], label = id, fill = id), show.legend = FALSE, 
      ...) + scale_fill_manual(values = labels.loc$color[order(labels.loc[, 
      id])])
  }
  else {
    geom.use <- ifelse(test = repel, yes = geom_text_repel, 
      no = geom_text)
    plot <- plot + geom.use(data = labels.loc, mapping = aes_string(x = xynames["x"], 
      y = xynames["y"], label = id), show.legend = FALSE, 
      ...)
  }
  if (geom == "GeomSpatial") {
    plot <- suppressMessages(expr = plot + coord_fixed(xlim = xrange.save, 
      ylim = yrange.save))
  }
  #print(plot)
  return(plot)
}

plot <- LabelClusters(plot = plot, id = "ident", repel = TRUE, 
  size = 4, split.by = NULL, box = FALSE, 
  color = "black")

print(plot)

结果如下

简化代码2

rm(list=ls())
setwd("/Users/yxk/Desktop/test/Seurat_label测试/")
suppressPackageStartupMessages(library(ggplot2))
suppressPackageStartupMessages(library(cowplot))
suppressPackageStartupMessages(library(ggrepel))

data = read.csv("./pbmc_UMAP.csv",row.names = 1) # 相当于python里面的index

plot <- ggplot(data = data)

col.by ="ident"
plot = plot + geom_point(mapping = aes_string(x = "UMAP_1", 
                                              y = "UMAP_2", color = paste0("`", col.by, "`"), shape = NULL, 
                                              alpha = NULL), size = 0.6000758)

plot <- plot + guides(color = guide_legend(override.aes = list(size = 3))) + 
  labs(color = NULL, title = col.by) 

plot <- plot + theme_cowplot()
print(plot)


LabelClusters = function(plot, id, clusters = NULL, labels = NULL, split.by = NULL, 
                         repel = TRUE, box = FALSE, geom = "GeomPoint", position = "median", 
                         ...) 
{
  #   xynames <- unlist(x = GetXYAesthetics(plot = plot, geom = geom), 
  #     use.names = TRUE)
  xynames=c("UMAP_1","UMAP_2")
  names(xynames)=c("x","y")
  data <- plot$data[, c(xynames, id, split.by)]
  possible.clusters <- as.character(x = na.omit(object = unique(x = data[, id])))
  groups <- possible.clusters
  pb <- ggplot_build(plot = plot)
  data <- cbind(data, color = pb$data[[1]][[1]])
  labels.loc <- lapply(X = groups, FUN = function(group) {
    data.use <- data[data[, id] == group, , drop = FALSE]
    data.medians <- as.data.frame(x = t(x = apply(X = data.use[, xynames, drop = FALSE], MARGIN = 2, FUN = median, na.rm = TRUE)))
    
    data.medians[, id] <- group
    data.medians$color <- data.use$color[1]
    return(data.medians)
  })
  labels.loc <- do.call(what = "rbind", args = labels.loc)
  #labels.loc[, id] <- factor(x = labels.loc[, id], levels = levels(data[,  id]))
  labels.loc$'ident'= as.factor(labels.loc$'ident')
  
  labels <-  groups

  names(x = labels) <- groups
  for (group in groups) {
    labels.loc[labels.loc[, id] == group, id] <- labels[group]
  }
  #print(labels.loc)

  geom.use <- ifelse(test = repel, yes = geom_text_repel, 
                     no = geom_text)
  plot <- plot + geom.use(data = labels.loc, mapping = aes_string(x = xynames["x"], 
                                                                  y = xynames["y"], label = id), show.legend = FALSE,  ...)
  return(plot)
}

plot <- LabelClusters(plot = plot, id = "ident", repel = TRUE, 
                      size = 4, split.by = NULL, box = FALSE, 
                      color = "black")

print(plot)

结果如下

简化代码3

 rm(list=ls())
setwd("/Users/yxk/Desktop/test/Seurat_label测试/")
suppressPackageStartupMessages(library(ggplot2))
suppressPackageStartupMessages(library(cowplot))
suppressPackageStartupMessages(library(ggrepel))

data = read.csv("./pbmc_UMAP.csv",row.names = 1) # 相当于python里面的index
plot <- ggplot(data = data)
col.by ="ident"
plot = plot + geom_point(mapping = aes_string(x = "UMAP_1", 
                                              y = "UMAP_2", color = paste0("`", col.by, "`"), shape = NULL, 
                                              alpha = NULL), size = 0.6000758)

plot <- plot + guides(color = guide_legend(override.aes = list(size = 3))) + 
  labs(color = NULL, title = col.by) 

plot <- plot + theme_cowplot()
print(plot)

###########

id = "ident"
size = 4
color = "black"
xynames=c("UMAP_1","UMAP_2")
names(xynames)=c("x","y")
data <- plot$data[, c(xynames, id)]
clusters<- as.character(x = na.omit(object = unique(x = data[, id])))
groups <- clusters
pb <- ggplot_build(plot = plot)
data <- cbind(data, color = pb$data[[1]][[1]])
labels.loc <- lapply(X = groups, FUN = function(group) {
  data.use <- data[data[, id] == group, , drop = FALSE]
  data.medians <- as.data.frame(x = t(x = apply(X = data.use[, xynames, drop = FALSE], MARGIN = 2, FUN = median, na.rm = TRUE)))
  data.medians[, id] <- group
  data.medians$color <- data.use$color[1]
  return(data.medians)
})
labels.loc <- do.call(what = "rbind", args = labels.loc)
#labels.loc[, id] <- factor(x = labels.loc[, id], levels = levels(data[,  id]))
labels.loc$'ident'= as.factor(labels.loc$'ident')

labels <-  groups

names(x = labels) <- groups
for (group in groups) {
  labels.loc[labels.loc[, id] == group, id] <- labels[group]
}
#print(labels.loc)

geom.use <- ifelse(test = TRUE, yes = geom_text_repel, 
                   no = geom_text)
plot <- plot + geom.use(data = labels.loc, mapping = aes_string(x = xynames["x"], 
                                                                y = xynames["y"], label = id), show.legend = FALSE)
print(plot)

结果如下