R tips：celltrek细胞共定位分析

生信菜鸟团

发布于 2025-03-17 20:53:18

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CellTrek是一个空间分析工具包，可以做单细胞和空间的整合分析、空间细胞共定位和空间基因表达分析。

它的共定位分析可以找到空间上距离相互靠近的细胞，并以网络图的形式呈现。

官方教程中，共定位分析需要依赖整合单细胞和空间数据之后的celltrek对象，本文则只使用空间数据进行共定位分析。同时官方提供了一个shiny程序用于展示共定位网络结构，交互性很好，但是无法导出图片，本文则使用igraph从头绘制共定位网络图。

仍以10X的xenium breast官方数据为例，下载后解压。

读取数据，构造用于celltrek共定位分析的对象

# read xenium gene expression data 
xenium_expr <- Read10X_h5("Xenium_V1_FFPE_Human_Breast_IDC/cell_feature_matrix.h5") 
xenium <- CreateSeuratObject( 
    xenium_expr$`Gene Expression`, 
    min.cells = 10, 
    min.features = 10 
 ) %>% 
 RenameCells(add.cell.id = "cell") 
 
# read cell coords data 
# 3 column should exists to run CellTrek::scoloc analysis 
# coord_x, coord_y, id_new 
coords_xenium <- arrow::read_parquet("Xenium_V1_FFPE_Human_Breast_IDC/cells.parquet") 
meta_coords <- 
  coords_xenium %>% 
  dplyr::select( 
    cell_id, 
    coord_x = x_centroid, 
    coord_y = y_centroid 
 ) %>% 
  mutate(cell_id = str_c("cell", cell_id, sep = "_")) %>% 
  mutate(id_new = cell_id) %>% 
  column_to_rownames("cell_id") 
 
xenium <- xenium %>% AddMetaData(meta_coords)

构造模拟的组别和细胞注释，这里只是示意，正常情况下，group是分析组别，annotation是注释好的细胞类型。

set.seed(1234) 
xenium$group <- sample(LETTERS[1:3], size = ncol(xenium), replace = TRUE) 
xenium$annotation <- sample(str_c("Cell", LETTERS[1:10], sep = "_"), size = ncol(xenium), replace = TRUE)

展示一下此时的数据，为了提高绘图速度，只是用10%的细胞绘制空间原位图：

# spatial plot 
xenium[[]] %>% 
  dplyr::slice_sample(prop = 0.1) %>% 
  ggplot(aes(x = coord_x, y = coord_y)) + 
  geom_tile(aes(fill = group), height = 20, width = 20) + 
  coord_equal() + 
  ggsci::scale_fill_aaas() + 
  theme_void() 
 
xenium[[]] %>% 
  dplyr::slice_sample(prop = 0.1) %>% 
  ggplot(aes(x = coord_x, y = coord_y)) + 
  geom_tile(aes(fill = annotation), height = 20, width = 20) + 
  coord_equal() + 
  ggsci::scale_fill_igv() + 
  theme_void()

空间共定位

# run CellTrek analysis sequentially for the three groups 
all_data_grp_ls <- xenium %>% SplitObject(split.by = "group") 
 
# run celltrek 
all_celltrek_ls <- 
  all_data_grp_ls %>% 
  map(function(sc){ # browser() 
    graph_KL <- 
 CellTrek::scoloc( 
        sc, 
        col_cell   ='annotation', 
        use_method ='KL', 
        h   = 10, 
        eps = 1e-50 
 ) 
 
    cells <- sc$annotation %>% unique() 
    names(cells) <- cells %>% make.names() 
 
 ## We extract the minimum spanning tree (MST) result from the graph 
    graph_KL_mst_cons <- graph_KL$mst_cons 
    rownames(graph_KL_mst_cons) <- 
      colnames(graph_KL_mst_cons) <- 
      cells[colnames(graph_KL_mst_cons)] 
 
 ## We then extract the metadata (including cell types and their frequencies) 
    cell_class <- sc[[]] %>% 
      group_by(annotation) %>% 
      summarise(n = n()) %>% 
 as.data.frame() %>% 
      dplyr::rename(id = annotation) 
 
    list( 
      mst = graph_KL_mst_cons, 
      cell_class = cell_class 
 ) 
 }) 
 
# celltrek network can be visualized by scoloc_vis 
# group A: 
CellTrek::scoloc_vis(all_celltrek_lsAmst, meta_data = all_data_grp_ls

共定位网络图绘制

# plot celltrek network by igraph 
 
cell_colors <- ggsci::pal_igv()(10) 
 
p_all_celltrek_ls <- 
  all_celltrek_ls %>% 
  map(function(ct){ 
    graph <- 
      ct$mst %>% 
 as.data.frame() %>% 
      rownames_to_column('from') %>%  
      pivot_longer(-from, names_to = "to", values_to = "weight") %>% 
      dplyr::filter(weight > 0.2) %>% 
      igraph::graph_from_data_frame() %>% 
      tidygraph::as_tbl_graph()  
 
 
 set.seed(12345) 
    p <- 
      graph %>% 
      tidygraph::activate(nodes) %>% 
      left_join(ct$cell_class, by = c(name = 'id')) %>% 
      ggraph::ggraph(layout = 'fr') + #, weights = weight) + 
      ggraph::geom_edge_link(aes(width = weight), color = 'gray', show.legend = FALSE) + 
      ggraph::geom_node_point(aes(size = n, color = name), show.legend = FALSE) + 
      ggraph::geom_node_text(aes(label = name), color = 'gray10', nudge_y= -0.2) + 
      ggraph::scale_edge_width(range = c(1, 4)) + 
      scale_size(range = c(4, 12)) + 
 # ggsci::scale_color_igv() + 
      scale_color_manual(values = cell_colors) + 
      coord_fixed(clip = 'off') + 
      theme_void() 
    p 
 })

celltrek网络图入下：