plotHeatmaps {phemd} | R Documentation |
Takes as input a Phemd object containing either a Monocle2, Seurat, or PHATE object (already embedded and clustered) and plots heatmap characterizing cell subtypes
plotHeatmaps( obj, cell_model = c("monocle2", "seurat", "phate"), selected_genes = NULL, w = 8, h = 5, ... )
obj |
'Phemd' object containing cell-state embedding object |
cell_model |
Method by which cell state was modeled ("monocle2", "seurat", or "phate") |
selected_genes |
Vector containing gene names to include in heatmap (optional) |
w |
Width of plot in inches |
h |
Height of plot in inches |
... |
Additional parameters to be passed on to pheatmap function |
embedCells
(and orderCellsMonocle
if using Monocle2) need to be called before calling this function. Required additional package: 'pheatmap'
Heatmap containing expression values for each cell subtype. If cell_model is 'seurat', then returns a list of heatmaps (1 for each batch) that may be subsequently plotted individually
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_lg <- selectFeatures(my_phemdObj_lg, selected_genes) my_phemdObj_monocle <- embedCells(my_phemdObj_lg, data_model = 'gaussianff', pseudo_expr=0, sigma=0.02, maxIter=2) my_phemdObj_monocle <- orderCellsMonocle(my_phemdObj_monocle) myheatmap <- plotHeatmaps(my_phemdObj_monocle, cell_model='monocle2')