celdaTsne {celda} | R Documentation |
Embeds cells in two dimensions using tSNE based on celda_CG results.
celdaTsne(counts, celdaMod, maxCells = 25000, minClusterSize = 100, initialDims = 20, modules = NULL, perplexity = 20, maxIter = 2500, ...)
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. |
Numeric Matrix of dimension 'ncol(counts)' x 2, colums representing the "X" and "Y" coordinates in the data's t-SNE represetation.
data(celdaCGSim, celdaCGMod) tsneRes <- celdaTsne(celdaCGSim$counts, celdaCGMod)