Calculate features overlapped by polygons
calculateOverlap.RdCalculate subcellular points/feature info or image values overlapped by polygon annotations. This provides a summary of the spatial data overlapped by the polygon which can be further processed to become an expression matrix.
Usage
# S4 method for giotto,missing
calculateOverlap(
x,
name_overlap = NULL,
spatial_info = NULL,
feat_info = NULL,
image_names = NULL,
poly_subset_ids = NULL,
return_gobject = TRUE,
verbose = TRUE,
...
)
# S4 method for giottoPolygon,giottoPoints
calculateOverlap(
x,
y,
name_overlap = NULL,
poly_subset_ids = NULL,
feat_subset_column = NULL,
feat_subset_ids = NULL,
count_info_column = NULL,
return_gpolygon = TRUE,
verbose = TRUE,
...
)
# S4 method for giottoPolygon,giottoLargeImage
calculateOverlap(
x,
y,
name_overlap = NULL,
poly_subset_ids = NULL,
return_gpolygon = TRUE,
verbose = TRUE,
...
)
# S4 method for giottoPolygon,SpatRaster
calculateOverlap(
x,
y,
name_overlap = NULL,
poly_subset_ids = NULL,
return_gpolygon = TRUE,
verbose = TRUE,
...
)
# S4 method for SpatVector,SpatRaster
calculateOverlap(x, y, poly_subset_ids = NULL, verbose = TRUE, ...)
# S4 method for SpatVector,SpatVector
calculateOverlap(
x,
y,
poly_subset_ids = NULL,
feat_subset_column = NULL,
feat_subset_ids = NULL,
count_info_column = NULL,
verbose = TRUE
)Arguments
- x
Object with spatial annotations:
giottoPolygon, orSpatVectorpolygons. Can also be agiottoobject- name_overlap
name for the overlap results (default to feat_info parameter)
- spatial_info
character. Name polygon information
- feat_info
character. Name of vector feature information to overlap
- image_names
character vector. Name(s) of the image feature information to overlap
- poly_subset_ids
character vector. (optional) Specific poly_IDs to use
- return_gobject
return giotto object (default: TRUE)
- verbose
be verbose
- ...
additional params to pass to methods.
- y
Object with features to overlap:
giottoPoints,giottoLargeImage,SpatVectorpoints orSpatRaster- feat_subset_column
character. (optional) feature info attribute to subset feature points on when performing overlap calculation.
- feat_subset_ids
(optional) values matched against in
feat_subset_columnin order to subset feature points when performing overlap calculation.- count_info_column
character. (optional) column with count information. Useful in cases when more than one detection is reported per point.
- return_gpolygon
default = TRUE. Whether to return the entire giottoPolygon provided to
x, but with the overlaps information appended or as a bare terraSpatVector
Value
Usually an object of the same class as x, with the overlaps
information appended. return_* logical params usually allow return of
a lower-level representation of the results instead. Only the
SpatVector,SpatRaster method is different in that it returns a data.table.
Details
feat_subset_column, feat_subset_ids, and count_info_column are
specific to overlaps on feature points info, and should not be provided
when overlapping image data. These three params can also be passed to the
giotto method through the ... param when working with overlaps on feature
points info.
Examples
g <- GiottoData::loadGiottoMini("vizgen")
#> 1. read Giotto object
#> 2. read Giotto feature information
#> [1] "/home/runner/work/_temp/Library/GiottoData//Mini_datasets/Vizgen/VizgenObject//Features/rna_feature_spatVector.shp"
#> [1] "rna"
#> 3. read Giotto spatial information
#>
#> 3.1 read Giotto spatial shape information
#> [1] "aggregate_spatInfo_spatVector.shp" "z0_spatInfo_spatVector.shp"
#> [3] "z1_spatInfo_spatVector.shp"
#> aggregate
#> z0
#> z1
#>
#> 3.2 read Giotto spatial centroid information
#> aggregate
#> z0
#> z1
#>
#> 3.3 read Giotto spatial overlap information
#> [1] "rna_aggregate_spatInfo_spatVectorOverlaps.shp"
#> [2] "rna_z0_spatInfo_spatVectorOverlaps.shp"
#> [3] "rna_z1_spatInfo_spatVectorOverlaps.shp"
#> [1] "poly_ID" "feat_ID" "feat_ID_uniq" "stack"
#> aggregate and rna
#> [1] "poly_ID" "feat_ID" "feat_ID_uniq"
#> z0 and rna
#> [1] "poly_ID" "feat_ID" "feat_ID_uniq"
#> z1 and rna
#>
#> 4. read Giotto image information
#>
#> no external python path or giotto environment was specified, will check if a
#> default python path is available
#>
#> A default python path was found: /usr/bin/python3 and will be used
#> If this is not the correct python path, either
#>
#> 1. use installGiottoEnvironment() to install a local miniconda python
#> environment along with required modules
#>
#> 2. provide an existing python path to python_path to use your own python path
#> which has all modules installed
#> Set options("giotto.use_conda" = FALSE) if python functionalities are not
#> needed
#> Warning: module: pandas was not found with python path: /usr/bin/python3
#> Warning: module: igraph was not found with python path: /usr/bin/python3
#> Warning: module: leidenalg was not found with python path: /usr/bin/python3
#> Warning: module: community was not found with python path: /usr/bin/python3
#> Warning: module: networkx was not found with python path: /usr/bin/python3
#> Warning: module: sklearn was not found with python path: /usr/bin/python3
#> Warning: module: pandas was not found with python path: /usr/bin/python3
#> Warning: module: igraph was not found with python path: /usr/bin/python3
#> Warning: module: leidenalg was not found with python path: /usr/bin/python3
#> Warning: module: community was not found with python path: /usr/bin/python3
#> Warning: module: networkx was not found with python path: /usr/bin/python3
#> Warning: module: sklearn was not found with python path: /usr/bin/python3
gpoly <- getPolygonInfo(g,
polygon_name = "aggregate",
return_giottoPolygon = TRUE
)
gpoints <- getFeatureInfo(g, return_giottoPoints = TRUE)
gimg <- getGiottoImage(g, image_type = "largeImage")
gpoly@overlaps <- NULL
overlaps(gpoly) # Should now be NULL
#> NULL
# detections from 2 z-layers are provided
table(gpoints$global_z)
#>
#> 0 1
#> 35889 43872
# calculate all transcripts overlapped
out_all <- calculateOverlap(gpoly, gpoints)
#> 1. convert polygon to raster
#> 2. overlap raster and points
#> 3. add polygon information
#> 4. add points information
#> 5. create overlap polygon information
overlaps_all <- overlaps(out_all)
overlaps_all$rna
#> class : SpatVector
#> geometry : points
#> dimensions : 79761, 3 (geometries, attributes)
#> extent : 6400.037, 6900.032, -5149.983, -4699.979 (xmin, xmax, ymin, ymax)
#> coord. ref. :
#> names : poly_ID feat_ID feat_ID_uniq
#> type : <chr> <chr> <int>
#> values : NA Mlc1 1
#> NA Gprc5b 2
#> NA Gfap 3
# calculate z1 only
out_z1 <- calculateOverlap(gpoly, gpoints,
feat_subset_column = "global_z",
feat_subset_ids = c(1)
)
#> 1. convert polygon to raster
#> 2. overlap raster and points
#> 3. add polygon information
#> 4. add points information
#> 5. create overlap polygon information
overlaps_z1 <- overlaps(out_z1)
overlaps_z1$rna
#> class : SpatVector
#> geometry : points
#> dimensions : 43872, 3 (geometries, attributes)
#> extent : 6400.043, 6900.03, -5149.983, -4699.984 (xmin, xmax, ymin, ymax)
#> coord. ref. :
#> names : poly_ID feat_ID feat_ID_uniq
#> type : <chr> <chr> <int>
#> values : NA Gabbr2 36198
#> NA Gfap 36199
#> NA Gfap 36200
# overlap image to get sum intensities per cell
out_img <- calculateOverlap(gpoly, gimg)
#> Start image extract
#>
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#> End image extract
overlaps_img <- overlaps(out_img)
overlaps_img$intensity
#> $dapi_z0
#> poly_ID mini_dataset_dapi_z0
#> <char> <num>
#> 1: 100210519278873141813371229408401071444 18
#> 2: 100210519278873141813371229408401071444 18
#> 3: 100210519278873141813371229408401071444 18
#> 4: 100210519278873141813371229408401071444 18
#> 5: 100210519278873141813371229408401071444 18
#> ---
#> 3170620: 98561957902191275233320065611022298397 98
#> 3170621: 98561957902191275233320065611022298397 98
#> 3170622: 98561957902191275233320065611022298397 88
#> 3170623: 98561957902191275233320065611022298397 88
#> 3170624: 98561957902191275233320065611022298397 88
#>
# giotto method
# calculate z0 overlaps and return as gobject
out_g <- calculateOverlap(g,
feat_subset_column = "global_z",
feat_subset_ids = 0
)
#> 1. convert polygon to raster
#> 2. overlap raster and points
#> 3. add polygon information
#> 4. add points information
#> 5. create overlap polygon information
#> Warning: module: pandas was not found with python path: /usr/bin/python3
#> Warning: module: igraph was not found with python path: /usr/bin/python3
#> Warning: module: leidenalg was not found with python path: /usr/bin/python3
#> Warning: module: community was not found with python path: /usr/bin/python3
#> Warning: module: networkx was not found with python path: /usr/bin/python3
#> Warning: module: sklearn was not found with python path: /usr/bin/python3
overlaps(getPolygonInfo(out_g, return_giottoPolygon = TRUE))
#> No polygon information named "cell" discovered.
#> Selecting first available (" z0 ")
#> $rna
#> class : SpatVector
#> geometry : points
#> dimensions : 35889, 3 (geometries, attributes)
#> extent : 6400.037, 6900.032, -5149.983, -4699.979 (xmin, xmax, ymin, ymax)
#> coord. ref. :
#> names : poly_ID feat_ID feat_ID_uniq
#> type : <chr> <chr> <int>
#> values : NA Mlc1 1
#> NA Gprc5b 2
#> NA Gfap 3
#>
# note that z0 and z1 nrows match that from the table of global z values.
# With points overlaps, all points are returned, but non-overlapped points
# only have an `NA` value for the `poly_ID` column. Overlapped points will
# have the `poly_ID` of their overlapping polygon.