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calculate overlap between cellular structures (polygons) and features (points)

Usage

calculateOverlapParallel(
  gobject,
  name_overlap = NULL,
  spatial_info = "cell",
  feat_info = "rna",
  poly_ID_names = "all",
  polygon_group_size = 500,
  return_gobject = TRUE,
  verbose = TRUE
)

Arguments

gobject

giotto object

name_overlap

name for the overlap results (default to feat_info parameter)

spatial_info

polygon information

feat_info

feature information

poly_ID_names

list of poly_IDs to use

polygon_group_size

number of polygons to process per parallelization group

return_gobject

return giotto object (default: TRUE)

verbose

be verbose

Value

giotto object or spatVector with overlapping information

Details

parallel follows the future approach. This means that plan(multisession) does not work, since the underlying terra objects are internal C pointers. plan(multicore) is also not supported for Rstudio users.

Examples

g <- GiottoData::loadGiottoMini("vizgen")
#> 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 : 'giotto_env'
#>  python version : 3.10
#> checking default envname 'giotto_env'
#> a system default python environment was found
#> Using python path:
#>  "/usr/share/miniconda/envs/giotto_env/bin/python"

calculateOverlapParallel(g, spatial_info = "z1")
#> An object of class giotto 
#> >Active spat_unit:  z0 
#> >Active feat_type:  rna 
#> [SUBCELLULAR INFO]
#> polygons      : z0 z1 aggregate 
#> features      : rna 
#> [AGGREGATE INFO]
#> expression -----------------------
#>   [z0][rna] raw
#>   [z1][rna] raw
#>   [aggregate][rna] raw normalized scaled pearson
#> spatial locations ----------------
#>   [z0] raw
#>   [z1] raw
#>   [aggregate] raw
#> spatial networks -----------------
#>   [aggregate] Delaunay_network kNN_network
#> spatial enrichments --------------
#>   [aggregate][rna] cluster_metagene
#> dim reduction --------------------
#>   [aggregate][rna] pca umap tsne
#> nearest neighbor networks --------
#>   [aggregate][rna] sNN.pca
#> attached images ------------------
#> images      : 4 items...
#> 
#> 
#> Use objHistory() to see steps and params used