计算每个基因的 pseudotime

require(monocle) require(Seurat) require(dplyr) #-------------------------------------------------------# #Identify genes for ordering cells, "fullModelFormulaStr=" specify the conditions that we want to dominate the cell trajectory #Or, we can use the genes identify by other ways diff_test_res <- differentialGeneTest(Monocle2_object, fullModelFormulaStr = "~Media") #In this case, "Media" is condition that we want to dominate the cell trajectory trajectory_ordering_genes <- row.names (subset(diff_test_res, qval < 0.01)) #-------------------------------------------------------# #Set the highly variable genes for dimension reduction Monocle2_object <- setOrderingFilter(Monocle2_object, ordering_genes=trajectory_ordering_genes) #-------------------------------------------------------# #Dimension reduction by PCA, then other method based on PCA results #For pseudotime calculation, the dimension reduction method "DDRTree" is recommended Monocle2_object <- reduceDimension(Monocle2_object, max_components = 2, num_dim = 6, reduction_method = 'DDRTree', verbose = T) #-------------------------------------------------------# #Order cells (calculate pseudotime) by dimension reduction results (not PCA) produced by reduceDimension() Monocle2_object <- orderCells(Monocle2_object, num_paths=1) #-------------------------------------------------------# #Show the dimention reduction and pseudotime results plot_cell_trajectory(Monocle2_object)