View source: R/dimension_reduction.R
runtSNE | R Documentation |
run tSNE
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,
...
)
gobject |
giotto object |
spat_unit |
spatial unit |
feat_type |
feature type |
expression_values |
expression values to use |
reduction |
cells or feats |
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 features 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 |
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
giotto object with updated tSNE dimension recuction
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.