celdaTsne {celda} | R Documentation

## Embeds cells in two dimensions using tSNE based on celda_CG results.

### Description

Embeds cells in two dimensions using tSNE based on celda_CG results.

### Usage

    celdaTsne(
      counts,
      celdaMod,
      maxCells = 25000,
      minClusterSize = 100,
      initialDims = 20,
      modules = NULL,
      perplexity = 20,
      maxIter = 2500,
      ...
    )

### 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. The number of dimensions that should be retained in the initial PCA step. Default 20.
`modules` | Integer vector. Determines which features modules to use for tSNE. If NULL, all modules will be used. Default NULL.
`perplexity` | Numeric. Perplexity parameter for tSNE. Default 20.
`maxIter` | Integer. Maximum number of iterations in tSNE generation. Default 2500.
`...` | Additional parameters.

### 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 <- celdaTsne(celdaCGSim$counts, celdaCGMod)

[Package celda version 1.3.4 Index]