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Run diffusion map (DM)

Source: R/RunDM.R
RunDM.Rd

Run diffusion map (DM)

Usage

RunDM(object, ...)

# S3 method for class 'Seurat'
RunDM(
  object,
  reduction = "pca",
  dims = 1:30,
  features = NULL,
  assay = NULL,
  layer = "data",
  ndcs = 2,
  sigma = "local",
  k = 30,
  dist.method = "euclidean",
  npcs = NULL,
  reduction.name = "dm",
  reduction.key = "DM_",
  verbose = TRUE,
  seed.use = 11,
  ...
)

# Default S3 method
RunDM(
  object,
  assay = NULL,
  layer = "data",
  ndcs = 2,
  sigma = "local",
  k = 30,
  dist.method = "euclidean",
  npcs = NULL,
  reduction.key = "DM_",
  verbose = TRUE,
  seed.use = 11,
  ...
)

Arguments

object

An object. This can be a Seurat object or a matrix-like object.

...

Additional arguments to be passed to destiny::DiffusionMap.

reduction

Which dimensionality reduction to use. Default is "pca".

dims

The dimensions to be used. Default is NULL.

features

A character vector of features to use. Default is NULL.

assay

Which assay to use. If NULL, the default assay of the Seurat object will be used.

layer

Which layer to use. Default is data.

ndcs

A number of diffusion components (dimensions) to be computed. Default is 2.

sigma

The diffusion scale parameter of the Gaussian kernel. Currently supported values are "local" (default) and "global".

k

A number of nearest neighbors to be used for the construction of the graph. Default is 30.

dist.method

The distance metric to be used for the construction of the knn graph. Currently supported values are "euclidean" and "cosine". Default is "euclidean".

npcs

Number of principal components to use for dimensionality reduction before computing diffusion map. This can speed up computation when using many features. Default is NULL (auto-determined based on the number of features).

reduction.name

The name of the reduction to be stored in the Seurat object. Default is "dm".

reduction.key

The prefix for the column names of the basis vectors. Default is "DM_".

verbose

Whether to print the message. Default is TRUE.

seed.use

Random seed for reproducibility. Default is 11.

Examples

data(pancreas_sub)
pancreas_sub <- standard_scop(pancreas_sub)
#> ℹ [2026-01-27 08:07:52] Start standard scop workflow...
#> ℹ [2026-01-27 08:07:53] Checking a list of <Seurat>...
#> ! [2026-01-27 08:07:53] Data 1/1 of the `srt_list` is "unknown"
#> ℹ [2026-01-27 08:07:53] Perform `NormalizeData()` with `normalization.method = 'LogNormalize'` on the data 1/1 of the `srt_list`...
#> ℹ [2026-01-27 08:07:56] Perform `Seurat::FindVariableFeatures()` on the data 1/1 of the `srt_list`...
#> ℹ [2026-01-27 08:07:56] Use the separate HVF from srt_list
#> ℹ [2026-01-27 08:07:56] Number of available HVF: 2000
#> ℹ [2026-01-27 08:07:57] Finished check
#> ℹ [2026-01-27 08:07:57] Perform `Seurat::ScaleData()`
#> ℹ [2026-01-27 08:07:57] Perform pca linear dimension reduction
#> ℹ [2026-01-27 08:07:58] Perform `Seurat::FindClusters()` with `cluster_algorithm = 'louvain'` and `cluster_resolution = 0.6`
#> ℹ [2026-01-27 08:07:58] Reorder clusters...
#> ℹ [2026-01-27 08:07:58] Perform umap nonlinear dimension reduction
#> ℹ [2026-01-27 08:07:58] Non-linear dimensionality reduction (umap) using (Standardpca) dims (1-50) as input
#> ℹ [2026-01-27 08:08:03] Non-linear dimensionality reduction (umap) using (Standardpca) dims (1-50) as input
#> ✔ [2026-01-27 08:08:08] Run scop standard workflow completed
pancreas_sub <- RunDM(
  object = pancreas_sub,
  features = SeuratObject::VariableFeatures(pancreas_sub)
)
#> ◌ [2026-01-27 08:08:08] Running destiny::DiffusionMap
#> ℹ [2026-01-27 08:08:16] Using 50 principal components to speed up computation (provided 2000 features)
#> Error in loadNamespace(name): there is no package called ‘destiny’

CellDimPlot(
  pancreas_sub,
  group.by = "CellType",
  reduction = "dm"
)