celdaTsne-celda_G-method: tSNE for celda_G

Description Usage Arguments Value See Also Examples

Description

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

Usage

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
## S4 method for signature 'celda_G'
celdaTsne(
  counts,
  celdaMod,
  maxCells = NULL,
  minClusterSize = 100,
  initialDims = 20,
  modules = NULL,
  perplexity = 20,
  maxIter = 2500,
  seed = 12345
)

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_G'.

maxCells

Integer. Maximum number of cells to plot. Cells will be randomly subsampled if ncol(conts) > 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.

initialDims

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

modules

Integer vector. Determines which feature 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.

seed

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

Value

A two column matrix of t-SNE coordinates.

See Also

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

Examples

1
2

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