run_rtsne: Computing t-SNE with 'Rtsne'.

In markgene/yamatClassifier: Yet Another Methylation Array Toolkit: Classifier

Computing t-SNE with Rtsne.

Description

Perform t-SNE with fit-SNE algorithm using Rtsne.

Usage

run_rtsne(
  trainer,
  top_n = 10000,
  perplexity = 30,
  n_iter = 3000,
  random_state = 123,
  pca = TRUE,
  verbose = TRUE,
  save_result = FALSE,
  ...
)

Arguments

trainer	A S3 object of YamatClassifierTrainer class.
top_n	an integer of the most variable N loci for t-SNE
perplexity	Numeric scalar controlling the neighborhood used when estimating the embedding. Default to 30.
n_iter	Integer scalar specifying the number of iterations to complete. Default to 3000.
random_state	Integer scalar specifying the seed used by the random number generator.
pca	Logical scalar specifying whether PCA should be run on the data before creating the embedding.
save_result	Logical scalar specifying whether result should be saved in Rda file.
...	other arguments of Rtsne.

Details

Notice set pca argument as default (TRUE).

Value

A matrix of t-SNE embeddings.

markgene/yamatClassifier documentation built on Oct. 14, 2024, 2:36 a.m.