generateGDM {phemd} | R Documentation |
Takes as input a Phemd object containing cell-state embedding object. Returns updated object with ground distance matrix representing pairwise distances between distinct cell subtypes based on cell state embedding.
generateGDM( obj, cell_model = c("monocle2", "seurat", "phate"), expn_type = "reduced", ndim = 8 )
obj |
'Phemd' object containing cell-state embedding object |
cell_model |
Method by which cell state was modeled (either "monocle2", "seurat", or "phate") |
expn_type |
Data type to use to determine cell-type dissimilarities |
ndim |
Number of embedding dimensions to be used for computing cell-type dissimilarity (optional) |
embedCells
and orderCellsMonocle
need to be called before calling this function. Requires 'igraph' package
Phemd object with ground distance matrix (to be used in EMD computation) in @data_cluster_weights slot
my_phemdObj <- createDataObj(all_expn_data, all_genes, as.character(snames_data)) my_phemdObj_lg <- removeTinySamples(my_phemdObj, 10) my_phemdObj_lg <- aggregateSamples(my_phemdObj_lg, max_cells=1000) my_phemdObj_monocle <- embedCells(my_phemdObj_lg, data_model = 'gaussianff', sigma=0.02, maxIter=2) my_phemdObj_monocle <- orderCellsMonocle(my_phemdObj_monocle) my_phemdObj_final <- clusterIndividualSamples(my_phemdObj_monocle) my_phemdObj_final <- generateGDM(my_phemdObj_final)