一文掌握seurat的umap新姿势，定制你的UMAP图

大家好，欢迎来到单细胞图片美化专辑！本文ump图，大致有四种中，欢迎个性化定制。

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目录：

• 1#1 将坐标轴进行缩放

• 2#2 给umap添加圆圈

• 3 #3.1美化标签

• 3#3.2 配色调整

• 4 # 4 我认为最美umap 图

首先读取seruat官网的pbmc示例数据，待画个性umap图

• aths(c( "/home/data/t040413/R/x86_64-pc-linux-gnu-library/4.2", "/home/data/t040413/R/yll/usr/local/lib/R/site-library", "/home/data/refdir/Rlib/", "/usr/local/lib/R/library"))library(Seurat)library(SeuratData)library(dplyr) pbmc=readRDS("~/gzh/featureplot_dotplot_vlnplot/pbmc3k_final.rds") DimPlot(pbmc,label=TRUE)

• 1 将坐标轴进行缩放,这样的umap图你喜欢吗

1#将坐标轴进行缩放
##调用第三方包#install.packages('tidydr')library(tidydr)library(ggplot2)##绘图DimPlot(pbmc, reduction = "umap", label = TRUE, pt.size = 1.2) +   tidydr::theme_dr(xlength = 0.2,            ylength = 0.2,           arrow = arrow(length = unit(0.2, "inches"),type = "closed")) +  theme(panel.grid = element_blank(),        axis.title = element_text(face = 2,hjust = 0.03)) +  NoLegend()

• 2给umap添加圆圈，代码分为两步

2给umap添加圆圈

2.1###首先提取umap数据table( [email protected])pbmc[['cellType']] = [email protected]umap = pbmc@[email protected] %>%    as.data.frame() %>%   cbind(cellType = [email protected]$cellType)
head(umap)
2.2##调用第三方包library(ggunchull)##绘图ggplot(umap,aes(x = UMAP_1, y = UMAP_2,fill = cellType, color = cellType)) +  theme_dr(xlength = 0.2,            ylength = 0.2,           arrow = arrow(length = unit(0.2, "inches"),type = "closed")) +  stat_unchull(alpha = 0.7, size = 0.5,lty = 2) +  geom_point(size = 0.3,show.legend = F) +  theme(    aspect.ratio = 1,    panel.background = element_blank(),    panel.grid = element_blank(),    axis.line = element_line(arrow = arrow(type = "closed")),    axis.title = element_text(face = 2,hjust = 0.03)) +  guides(fill = guide_legend(override.aes = list(colour = "white", linetype = 1, size = 1)))

• 3.1给umap图加方框

3 #3.1美化标签----##调用第三方包library(ggrepel)##提取umap数据pbmc[['cellType']] = [email protected]umap = pbmc@[email protected] %>%    as.data.frame() %>%   cbind(cellType = [email protected]$cellType)
##计算标签中心位置区域celltypepos <- umap %>%  group_by(cellType) %>%  summarise(    umap_1 = median(UMAP_1),    umap_2 = median(UMAP_2))
##画图p <-  DimPlot(pbmc, reduction = "umap", label = FALSE, pt.size = 1.2) +   theme_dr(xlength = 0.2,            ylength = 0.2,           arrow = arrow(length = unit(0.2, "inches"),type = "closed")) +  theme(panel.grid = element_blank(),        axis.title = element_text(face = 2,hjust = 0.03)) +  NoLegend() +  geom_label_repel(aes(x = umap_1,y = umap_2,label = cellType,color = cellType),                    fontface = "bold",                   data = celltypepos,                   box.padding = 0.5)p

• 3.2 不同杂志的配色方案，可以自定义配色方案。。这里列举四例

3#3.2 配色调整----

##调用第三方包library(ggsci)##随机选取四种色系展示p1 <- p + scale_color_aaas() + labs(title = "aaas", tag = "A")p2 <- p + scale_color_npg() + labs(title = "npg", tag = "B")p3 <- p + scale_color_igv() + labs(title = "igv", tag = "C")p4 <- p + scale_color_jco() + labs(title = "jco", tag = "D")##图形组合patchwork::wrap_plots(p1,p2,p3,p4,ncol = 2)

• 4. 我认为最美的个性化umap图

4 # 4 最美umap 图 -------4.1 #添加标签在图上 ，计算每个cluster的median 坐标位置pbmc[['cell_type']] = [email protected]umap = pbmc@[email protected] %>%    #坐标信息  as.data.frame() %>%   cbind(cell_type = [email protected]$cell_type) # 注释后的cell_type信息head(umap)4.2 #计算每个细胞类型的median 坐标位置，留作在图上加标签cell_type_med <- umap %>%  group_by(cell_type) %>%  summarise(    UMAP_1 = median(UMAP_1),    UMAP_2 = median(UMAP_2)  )head(cell_type_med)
4.3 #设定自己喜欢的颜色allcolour=c("#DC143C","#0000FF","#20B2AA","#FFA500","#9370DB","#98FB98","#F08080","#1E90FF","#7CFC00","#FFFF00",            "#808000","#FF00FF","#FA8072","#7B68EE","#9400D3","#800080","#A0522D","#D2B48C","#D2691E","#87CEEB","#40E0D0","#5F9EA0",            "#FF1493","#0000CD","#008B8B","#FFE4B5","#8A2BE2","#228B22","#E9967A","#4682B4","#32CD32","#F0E68C","#FFFFE0","#EE82EE",            "#FF6347","#6A5ACD","#9932CC","#8B008B","#8B4513","#DEB887")p <- ggplot(umap,aes(x= UMAP_1 , y = UMAP_2 ,color = cell_type)) +    geom_point(size = 1 , alpha =1 )  +   scale_color_manual(values = allcolour);p
p  +  theme(    legend.title = element_blank(), #去掉legend.title     legend.key=element_rect(fill='white'), #    legend.text = element_text(size=20), #设置legend标签的大小    legend.key.size=unit(1,'cm') ) +  # 设置legend标签之间的大小  guides(color = guide_legend(override.aes = list(size=5)))  + #设置legend中 点的大小 
  #缩放坐标轴  tidydr:: theme_dr(xlength = 0.2,                     ylength = 0.2,                    arrow = arrow(length = unit(0.2, "inches"),type = "closed")) +  #添加圈圈  ggunchull::stat_unchull(alpha = 0.1, size = 0.5,lty = 2)  +

  #添加注释 repel防止标签重叠，把注释加到图片的点上去  ggrepel:: geom_label_repel(aes(label=cell_type), fontface="bold",data = cell_type_med,                             point.padding=unit(0.3, "lines")) +
  # #去掉legend  # ggrepel::geom_label_repel(aes(label=cell_type), fontface="bold",data = cell_type_med,  #                  point.padding=unit(0.5, "lines")) +  theme(legend.position = "none") +
  #去掉网格  theme(panel.grid = element_blank(),        axis.title = element_text(face = 2,hjust = 0.03))
head(umap)
# #去掉网格线，坐标轴和背景色# theme(panel.grid.major = element_blank(), #主网格线#       panel.grid.minor = element_blank(), #次网格线#       panel.border = element_blank(), #边框#       axis.title = element_blank(),  #轴标题#       axis.text = element_blank(), # 文本#       axis.ticks = element_blank(),#       panel.background = element_rect(fill = 'white'), #背景色#       plot.background=element_rect(fill="white"))  +#调整标签大小，标签点的大小以及 标签之间的距离

如果你对umap画图所用到的数据不理解，可以回看我的第三场直播，让你举一反三、触类旁通

单细胞直播三seurat数据结构与数据可视化