celdaUmap {celda}R Documentation

Embeds cells in two dimensions using umap.

Description

Embeds cells in two dimensions using umap.

Usage

celdaUmap(counts, celdaMod, maxCells = 25000, minClusterSize = 100,
  initialDims = 20, modules = NULL, seed = 12345,
  umapConfig = umap::umap.defaults)

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. Default 25000.

minClusterSize

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

initialDims

Integer. PCA will be used to reduce the dimentionality of the dataset. The top 'initialDims' principal components will be used for umap. Default 20.

modules

Integer vector. Determines which features modules to use for tSNE. 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.

umapConfig

An object of class "umapConfig" specifying parameters to the UMAP algorithm.

Value

Numeric Matrix of dimension 'ncol(counts)' x 2, colums representing the "X" and "Y" coordinates in the data's t-SNE represetation.

Examples

data(celdaCGSim, celdaCGMod)
tsneRes <- celdaUmap(celdaCGSim$counts, celdaCGMod)

[Package celda version 1.0.1 Index]