tof_reduce_tsne: Perform t-distributed stochastic neighborhood embedding on...

In keyes-timothy/tidytof: Analyze High-dimensional Cytometry Data Using Tidy Data Principles

Perform t-distributed stochastic neighborhood embedding on single-cell data

Description

This function calculates a tSNE embedding using single-cell data from a 'tof_tibble'.

Usage

tof_reduce_tsne(
  tof_tibble,
  tsne_cols = where(tof_is_numeric),
  num_comp = 2,
  perplexity = 30,
  theta = 0.5,
  max_iterations = 1000,
  verbose = FALSE,
  ...
)

Arguments

tof_tibble	A 'tof_tbl' or 'tibble'.
tsne_cols	Unquoted column names indicating which columns in 'tof_tibble' to use in computing the tSNE embedding. Defaults to all numeric columns in 'tof_tibble'. Supports tidyselect helpers.
num_comp	The number of tSNE components to calculate for the embedding. Defaults to 2.
perplexity	A positive numeric value that represents represents the rough balance between the input data’s local and global structure emphasized in the embedding. Smaller values emphasize local structure; larger values emphasize global structure. The recommended range is generally 5-50. Defaults to 30.
theta	A numeric value representing the speed/accuracy tradeoff for the embedding. Set to 0 for the exact tSNE; increase for a faster approximation. Defaults to 0.5
max_iterations	An integer number of iterations to use during embedding calculation. Defaults to 1000.
verbose	A boolean value indicating whether progress updates should be printed during embedding calculation. Default is FALSE.
...	Additional arguments to pass to Rtsne.

Value

A tibble with the same number of rows as 'tof_tibble', each representing a single cell. Each of the ‘num_comp' columns represents each cell’s embedding in the calculated tSNE space.

See Also

Other dimensionality reduction functions: tof_reduce_dimensions(), tof_reduce_pca(), tof_reduce_umap()

Examples

# simulate single-cell data
sim_data <-
    dplyr::tibble(
        cd45 = rnorm(n = 200),
        cd38 = rnorm(n = 200),
        cd34 = rnorm(n = 200),
        cd19 = rnorm(n = 200)
    )

# calculate tsne
tof_reduce_tsne(tof_tibble = sim_data)

# calculate tsne with only 2 columns
tof_reduce_tsne(tof_tibble = sim_data, tsne_cols = c(cd34, cd38))

keyes-timothy/tidytof documentation built on Aug. 28, 2024, 8:37 a.m.