calculateDiffusionMap {scater} | R Documentation |
Produce a diffusion map for the cells, based on the data in a SingleCellExperiment object.
calculateDiffusionMap(x, ...) ## S4 method for signature 'ANY' calculateDiffusionMap(x, ncomponents = 2, ntop = 500, subset_row = NULL, feature_set = NULL, scale = FALSE, scale_features = NULL, transposed = FALSE, ...) ## S4 method for signature 'SummarizedExperiment' calculateDiffusionMap(x, ..., exprs_values = "logcounts") ## S4 method for signature 'SingleCellExperiment' calculateDiffusionMap(x, ..., exprs_values = "logcounts", dimred = NULL, use_dimred = NULL, n_dimred = NULL) runDiffusionMap(x, ..., altexp = NULL, name = "DiffusionMap")
x |
For For |
... |
For the For |
ncomponents |
Numeric scalar indicating the number of UMAP dimensions to obtain. |
ntop |
Numeric scalar specifying the number of features with the highest variances to use for PCA, see |
subset_row |
Vector specifying the subset of features to use for PCA, see |
feature_set |
Deprecated, same as |
scale |
Logical scalar, should the expression values be standardised? See |
scale_features |
Deprecated, same as |
transposed |
Logical scalar, is |
exprs_values |
Integer scalar or string indicating which assay of |
dimred |
String or integer scalar specifying the existing dimensionality reduction results to use, see |
use_dimred |
Deprecated, same as |
n_dimred |
Integer scalar or vector specifying the dimensions to use if |
altexp |
String or integer scalar specifying an alternative experiment to use to compute the PCA, see |
name |
String specifying the name to be used to store the result in the |
The function DiffusionMap
is used internally to compute the diffusion map.
The behaviour of DiffusionMap
seems to be non-deterministic, in a manner that is not responsive to any set.seed
call.
The reason for this is unknown.
For calculateDiffusionMap
, a matrix is returned containing the diffusion map coordinates for each cell (row) and dimension (column).
For runDiffusionMap
, a modified x
is returned that contains the diffusion map coordinates in reducedDim(x, name)
.
Aaron Lun, based on code by Davis McCarthy
Haghverdi L, Buettner F, Theis FJ (2015). Diffusion maps for high-dimensional single-cell analysis of differentiation data. Bioinformatics 31(18), 2989-2998.
DiffusionMap
, to perform the underlying calculations.
plotDiffusionMap
, to quickly visualize the results.
?"scater-red-dim-args"
, for a full description of various options.
example_sce <- mockSCE() example_sce <- logNormCounts(example_sce) example_sce <- runDiffusionMap(example_sce, scale_features=NULL) reducedDimNames(example_sce) head(reducedDim(example_sce))