celdaUmap-celda_G-method: umap for celda_G

Description Usage Arguments Value See Also Examples

Description

Embeds cells in two dimensions using umap based on a 'celda_G' model. umap is run on module probabilities to reduce the number of features instead of using PCA. Module probabilities square-root trasformed before applying tSNE.

Usage

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## S4 method for signature 'celda_G'
celdaUmap(
  counts,
  celdaMod,
  maxCells = NULL,
  minClusterSize = 100,
  modules = NULL,
  seed = 12345,
  nNeighbors = 30,
  minDist = 0.2,
  spread = 1,
  cores = 1,
  ...
)

Arguments

counts

Integer matrix. Rows represent features and columns represent cells. This matrix should be the same as the one used to generate 'celdaMod'.

celdaMod

Celda object of class 'celda_CG'.

maxCells

Integer. Maximum number of cells to plot. Cells will be randomly subsampled if ncol(counts) > maxCells. Larger numbers of cells requires more memory. If NULL, no subsampling will be performed. Default NULL.

minClusterSize

Integer. Do not subsample cell clusters below this threshold. Default 100.

modules

Integer vector. Determines which features modules to use for UMAP. If NULL, all modules will be used. Default NULL.

seed

Integer. Passed to with_seed. For reproducibility, a default value of 12345 is used. If NULL, no calls to with_seed are made.

nNeighbors

The size of local neighborhood used for manifold approximation. Larger values result in more global views of the manifold, while smaller values result in more local data being preserved. Default 30. See '?uwot::umap' for more information.

minDist

The effective minimum distance between embedded points. Smaller values will result in a more clustered/clumped embedding where nearby points on the manifold are drawn closer together, while larger values will result on a more even dispersal of points. Default 0.2. See '?uwot::umap' for more information.

spread

The effective scale of embedded points. In combination with ‘min_dist’, this determines how clustered/clumped the embedded points are. Default 1. See '?uwot::umap' for more information.

cores

Number of threads to use. Default 1.

...

Other parameters to pass to 'uwot::umap'.

Value

A two column matrix of umap coordinates

See Also

'celda_G()' for clustering features and cells and 'celdaHeatmap()' for displaying expression

Examples

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celda documentation built on June 9, 2020, 2 a.m.