runtSNE

runtSNE

Description

run tSNE

Usage

runtSNE(
  gobject,
  expression_values = c("normalized", "scaled", "custom"),
  reduction = c("cells", "genes"),
  dim_reduction_to_use = "pca",
  dim_reduction_name = "pca",
  dimensions_to_use = 1:10,
  name = "tsne",
  genes_to_use = NULL,
  return_gobject = TRUE,
  dims = 2,
  perplexity = 30,
  theta = 0.5,
  do_PCA_first = F,
  set_seed = T,
  seed_number = 1234,
  verbose = TRUE,
  ...
)

Arguments

Argument	Description
gobject	giotto object
expression_values	expression values to use
reduction	cells or genes
dim_reduction_to_use	use another dimension reduction set as input
dim_reduction_name	name of dimension reduction set to use
dimensions_to_use	number of dimensions to use as input
name	arbitrary name for tSNE run
genes_to_use	if dim_reduction_to_use = NULL, which genes to use
return_gobject	boolean: return giotto object (default = TRUE)
dims	tSNE param: number of dimensions to return
perplexity	tSNE param: perplexity
theta	tSNE param: theta
do_PCA_first	tSNE param: do PCA before tSNE (default = FALSE)
set_seed	use of seed
seed_number	seed number to use
verbose	verbosity of the function
...	additional tSNE parameters

Details

See ``Rtsne` <#rtsne>`_ for more information about these and other parameters. list()

• Input for tSNE dimension reduction can be another dimension reduction (default = ‘pca’)

• To use gene expression as input set dim_reduction_to_use = NULL

• If dim_reduction_to_use = NULL, genes_to_use can be used to select a column name of highly variable genes (see ``calculateHVG` <#calculatehvg>`_ ) or simply provide a vector of genes

• multiple tSNE results can be stored by changing the name of the analysis

Value

giotto object with updated tSNE dimension recuction

Examples

data(mini_giotto_single_cell)

mini_giotto_single_cell <- runtSNE(mini_giotto_single_cell,
dimensions_to_use = 1:3,
n_threads = 1,
n_neighbors = 3,
perplexity = 1)

plotTSNE(gobject = mini_giotto_single_cell)