runDiffusionMap {scater} | R Documentation |
Produce a diffusion map plot of two components for an SingleCellExperiment
dataset.
runDiffusionMap(object, ntop = 500, ncomponents = 2, feature_set = NULL, exprs_values = "logcounts", scale_features = TRUE, use_dimred = NULL, n_dimred = NULL, rand_seed = NULL, sigma = NULL, distance = "euclidean", ...) plotDiffusionMap(object, colour_by = NULL, shape_by = NULL, size_by = NULL, return_SCE = FALSE, draw_plot = TRUE, theme_size = 10, legend = "auto", rerun = FALSE, ncomponents = 2, ...)
object |
an |
ntop |
numeric scalar indicating the number of most variable features to
use for the diffusion map. Default is |
ncomponents |
numeric scalar indicating the number of principal
components to plot, starting from the first diffusion map component. Default
is 2. If |
feature_set |
character, numeric or logical vector indicating a set of
features to use for the diffusion map. If character, entries must all be in
|
exprs_values |
character string indicating which values should be used
as the expression values for this plot. Valid arguments are |
scale_features |
logical, should the expression values be standardised
so that each feature has unit variance? Default is |
use_dimred |
character(1), use named reduced dimension representation of cells
stored in |
n_dimred |
integer(1), number of components of the reduced dimension slot
to use. Default is |
rand_seed |
(optional) numeric scalar that can be passed to
|
sigma |
argument passed to |
distance |
argument passed to |
... |
further arguments passed to |
colour_by |
character string defining the column of |
shape_by |
character string defining the column of |
size_by |
character string defining the column of |
return_SCE |
logical, should the function return an |
draw_plot |
logical, should the plot be drawn on the current graphics
device? Only used if |
theme_size |
numeric scalar giving default font size for plotting theme (default is 10). |
legend |
character, specifying how the legend(s) be shown? Default is
|
rerun |
logical, should PCA be recomputed even if |
The function DiffusionMap
is used internally
to compute the diffusion map.
If return_SCE
is TRUE
, then the function returns an
SingleCellExperiment
object, otherwise it returns a ggplot
object.
Haghverdi L, Buettner F, Theis FJ. Diffusion maps for high-dimensional single-cell analysis of differentiation data. Bioinformatics. 2015; doi:10.1093/bioinformatics/btv325
## Set up an example SingleCellExperiment data("sc_example_counts") data("sc_example_cell_info") example_sce <- SingleCellExperiment( assays = list(counts = sc_example_counts), colData = sc_example_cell_info) example_sce <- normalize(example_sce) drop_genes <- apply(exprs(example_sce), 1, function(x) {var(x) == 0}) example_sce <- example_sce[!drop_genes, ] ## Not run: ## Examples plotting diffusion maps plotDiffusionMap(example_sce) plotDiffusionMap(example_sce, colour_by = "Cell_Cycle") plotDiffusionMap(example_sce, colour_by = "Cell_Cycle", shape_by = "Treatment") plotDiffusionMap(example_sce, colour_by = "Cell_Cycle", shape_by = "Treatment", size_by = "Mutation_Status") plotDiffusionMap(example_sce, shape_by = "Treatment", size_by = "Mutation_Status") plotDiffusionMap(example_sce, feature_set = 1:100, colour_by = "Treatment", shape_by = "Mutation_Status") plotDiffusionMap(example_sce, shape_by = "Treatment", return_SCE = TRUE) ## End(Not run)