Run tSNE dimensional reduction#

Last Updated: Jan 29, 2024

Description#

run tSNE

Usage#

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

Arguments#

`gobject`	giotto object
`spat_unit`	spatial unit
`feat_type`	feature type
`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
`feats_to_use`	if dim_reduction_to_use = NULL, which genes to use
`genes_to_use`	deprecated, use feats_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 for more information about these and other parameters.

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 calculateHVF) 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