addStatistics

Adds feature and cell statistics to the giotto object

addStatistics(
  gobject,
  feat_type = NULL,
  spat_unit = NULL,
  stats = c("feature", "cell", "area"),
  expression_values = c("normalized", "scaled", "custom"),
  detection_threshold = 0,
  return_gobject = TRUE,
  verbose = TRUE
)

Arguments

gobject

giotto object

feat_type

feature type

spat_unit

spatial unit

stats

character. What statistics to add. default = c("cell", "feature") See details

expression_values

expression values to use

detection_threshold

detection threshold to consider a feature detected

return_gobject

boolean: return giotto object (default = TRUE)

verbose

be verbose

Value

giotto object if return_gobject = TRUE, else a list with results

stats options

"feature" - includes addFeatStatistics results "cell" - includes addCellStatistics results "area" - includes polygon areas

Examples

g <- GiottoData::loadGiottoMini("visium")
#> 1. read Giotto object
#> 2. read Giotto feature information
#> 3. read Giotto spatial information
#> 3.1 read Giotto spatial shape information
#> 3.2 read Giotto spatial centroid information
#> 3.3 read Giotto spatial overlap information
#> 4. read Giotto image information
#> python already initialized in this session
#>  active environment : '/usr/bin/python3'
#>  python version : 3.12
#> checking default envname 'giotto_env'
#> a system default python environment was found
#> Using python path:
#>  "/usr/bin/python3"

addStatistics(g)
#> calculating statistics for "normalized" expression
#> feat statistics has already been applied once; overwriting
#> cells statistics has already been applied once; overwriting
#> An object of class giotto 
#> >Active spat_unit:  cell 
#> >Active feat_type:  rna 
#> dimensions    : 634, 624 (features, cells)
#> [SUBCELLULAR INFO]
#> polygons      : cell 
#> [AGGREGATE INFO]
#> expression -----------------------
#>   [cell][rna] raw normalized scaled
#> spatial locations ----------------
#>   [cell] raw
#> spatial networks -----------------
#>   [cell] Delaunay_network spatial_network
#> spatial enrichments --------------
#>   [cell][rna] cluster_metagene DWLS
#> dim reduction --------------------
#>   [cell][rna] pca custom_pca umap custom_umap tsne
#> nearest neighbor networks --------
#>   [cell][rna] sNN.pca custom_NN
#> attached images ------------------
#> images      : alignment image 
#> 
#> 
#> Use objHistory() to see steps and params used