clusterIndividualSamples {phemd} | R Documentation |
Takes as input a Phemd object with all single-cell expression data of all single-cell samples in @data slot and Monocle2 object (already embedded and ordered) in @monocle_obj slot. Returns updated object with cell subtype frequencies of each sample in @data_cluster_weights slot
clusterIndividualSamples(obj, verbose = FALSE, cell_model = c("monocle2", "seurat"))
obj |
'Phemd' object containing single-cell expression data of all samples in @data slot and Monocle2 object (already embedded and ordered) in @monocle_obj slot |
verbose |
Boolean that determines whether progress (sequential processing of samples) should be printed. FALSE by default |
cell_model |
Either "monocle2" or "seurat" depending on method used to model cell state space |
embedCells
and orderCellsMonocle
need to be called before calling this function.
'Phemd' object with cell subtype frequencies of each sample 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)