(视频教程): Monocle3分析流程-分析简化函数和可视化函

刚刚更新完monocle2的视频教程（(视频教程): Monocle2安装包测试、分析流程及可视化修饰），那么monocle3也不能落下，毕竟不能厚此薄彼，有小伙伴也是有需求。所以我们紧接着制作了这部分内容。主要做了两个事情，第一是对流程进行了讲解，第二是写了两个函数，一个是分析函数，一个是热图可视化函数，主要的目的还是为了简化工作。至于monocle3其他的内容强参考之前的帖子。
首先是分析过程，monocle3的分析其实很简洁；

##run
cds_data <- ks_run_monocle3(object=cytotrace2_sce,
                     idents="cluster",
                     use_partition=F,
                     learn_graph_control=list(minimal_branch_len=9.5,euclidean_distance_ratio=1),
                     define_root=T,
                     know_root=T,
                     root_state="YSMP")
#plot
plot_cells(cds_data, label_cell_groups = F, 
           color_cells_by = "pseudotime", 
           label_branch_points = F, 
           label_roots =F,
           label_leaves =F,
           graph_label_size = 0, 
           cell_size=2, 
           trajectory_graph_color='black',
           trajectory_graph_segment_size = 2)

然后就是拟时热图绘制：

#在monocle3分析中，我们使用graph_test函数分析过拟时差异基因，这个过程比较慢
modulated_genes <- graph_test(cds_data, neighbor_graph = "principal_graph", cores = 5)
plot_genes <- row.names(subset(modulated_genes, q_value < 0.01 & morans_I > 0.25))

image.png

#plot

ht1 = ks_monocle3_heatmap(cds = cds_data,
                        graph_gene = plot_genes,
                        celltype_color = c("#E69253", "#EDB931", "#E4502E", "#4f372d"),
                        cluster_color =c("#8f657d", "#42819F", "#86AA7D", "#CBB396"),
                        num_clusters=4)

image.png

#label gene
genes <- c("C1QB","C1QC","C1QA","MRC1","LGMN","MS4A7","MAF","FOLR2",
           "HLA-DPA1","CLEC10A","IL10RA","CD163","KCTD12","CLEC7A","MS4A6A","CD14",
           "ITM2A","CYTL1","MDK","SELP","CD24",
           "S100A8","S100A9","S100A12")

ht2 = ks_monocle3_heatmap(cds = cds_data,
                        graph_gene = plot_genes,
                        celltype_color = c("#E69253", "#EDB931", "#E4502E", "#4f372d"),
                        cluster_color =c("#8f657d", "#42819F", "#86AA7D", "#CBB396"),
                        num_clusters=4,
                        labels = T,
                        label_genes = genes)

image.png