calculate overlap between cellular structures (polygons) and features (points).
Usage
calculateOverlapRaster(
gobject,
name_overlap = NULL,
spatial_info = NULL,
poly_ID_names = NULL,
feat_info = NULL,
feat_subset_column = NULL,
feat_subset_ids = NULL,
count_info_column = NULL,
return_gobject = TRUE,
verbose = TRUE
)Arguments
- gobject
giotto object
- name_overlap
name for the overlap results (default to feat_info parameter)
- spatial_info
character. name polygon information
- poly_ID_names
(optional) list of poly_IDs to use
- feat_info
character. name of feature information
- feat_subset_column
feature info column to subset features with
- feat_subset_ids
ids within feature info column to use for subsetting
- count_info_column
column with count information (optional)
- return_gobject
return giotto object (default: TRUE)
- verbose
be verbose
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"
calculateOverlapRaster(g)
#> 1. convert polygon to raster
#> 2. overlap raster and points
#> 3. add polygon information
#> 4. add points information
#> 5. create overlap polygon
#> information
#> An object of class giotto
#> >Active spat_unit: z0
#> >Active feat_type: rna
#> dimensions : 337, 498 (features, cells)
#> [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