RunTSNEspaceST: t-SNE of spaceST data

In ludvigla/spaceST: spaceST

Description

Run t-SNE on spaceST object. Results are saved in the tsne slot.

Usage

RunTSNEspaceST(object, dims = 2, initial.dims = 50, theta = 0,
  check_duplicates = FALSE, pca = FALSE, perplexity = 15,
  max_iter = 1000, verbose = FALSE, seed = 0, plot.tSNE = FALSE,
  use.dims = "topics", select.dims = NULL, group_by = NULL,
  cols = NULL, ...)

Arguments

object	A spaceST object
dims	integer; Output dimensionality (default: 2)
initial.dims	integer; the number of dimensions that should be retained in the initial PCA step (default: 50). Only applicable if pca = TRUE.
theta	numeric; Speed/accuracy trade-off (increase for less accuracy), set to 0.0 for exact TSNE (default: 0.5).
check_duplicates	logical; Checks whether duplicates are present. It is best to make sure there are no duplicates present and set this option to FALSE, especially for large datasets (default: TRUE).
pca	logical; Whether an initial PCA step should be performed (default: FALSE.
perplexity	numeric; Perplexity parameter.
max_iter	integer; Number of iterations (default: 1000).
verbose	logical; Whether progress updates should be printed (default: FALSE).
seed	Set seed for reproducibility.
plot.tSNE	logical specifying whether or not t-SNE results should be plotted.
use.dims	specify what dimensions should be used for t-SNE (currently only "topics" available).
select.dims	integer; Select specific dimensions of input data, i.e. columns (default: NULL).
cols	character; Specify colors for grouping variable.
...	Parameters passed to Rtsne.
clusters	integer vector used to color features in t-SNE plot.

Value

Matrix with t-SNE results

See Also

Rtsne

ludvigla/spaceST documentation built on May 29, 2019, 3:43 a.m.