Seurat (version 2.3.4)

RunDiffusion: Run diffusion map

Description

NOTE: Prior to v2.3.4, this function used the R package diffusionMap to compute the diffusion map components. This package was being archived and thus RunDiffusion now uses the destiny package for the diffusion computations. Please be aware that this will result in different default values as the two underlying package implementations are different.

Usage

RunDiffusion(object, cells.use = NULL, dims.use = 1:5, genes.use = NULL,
  reduction.use = "pca", q.use = 0.01, max.dim = 2, scale.clip = 10,
  reduction.name = "dm", reduction.key = "DM", ...)

Arguments

object

Seurat object

cells.use

Which cells to analyze (default, all cells)

dims.use

Which dimensions to use as input features

genes.use

If set, run the diffusion map procedure on this subset of genes (instead of running on a set of reduced dimensions). Not set (NULL) by default

reduction.use

Which dimensional reduction (PCA or ICA) to use for the diffusion map input. Default is PCA

q.use

Quantile to clip diffusion map components at. This addresses an issue where 1-2 cells will have extreme values that obscure all other points. 0.01 by default

max.dim

Max dimension to keep from diffusion calculation

scale.clip

Max/min value for scaled data. Default is 3

reduction.name

dimensional reduction name, specifies the position in the object$dr list. dm by default

reduction.key

dimensional reduction key, specifies the string before the number for the dimension names. DM by default

...

Additional arguments to the DiffusionMap call

Value

Returns a Seurat object with a diffusion map

Examples

# NOT RUN {
pbmc_small
# Run Diffusion on variable genes
pbmc_small <- RunDiffusion(pbmc_small,genes.use = [e-mail])
# Run Diffusion map on first 10 PCs
pbmc_small <- RunDiffusion(pbmc_small,genes.use = [e-mail])
# Plot results
DMPlot(pbmc_small)
# }
# NOT RUN {
# }