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)