run_fitsne: Computing t-SNE with fit-SNE algorithm.

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

Computing t-SNE with fit-SNE algorithm.

Description

Perform t-SNE with fit-SNE algorithm using fitsne in snifter package.

Usage

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

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 fitsne.

Details

Notice set pca argument as default (FALSE). Otherwise, project will not work.

Value

A matrix of t-SNE embeddings.

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