isolating territories from vesalius image segments

Usage

isolate_territories(
  vesalius_assay,
  method = "distance",
  trial = "last",
  capture_radius = 0.05,
  global = TRUE,
  min_spatial_index = 10,
  verbose = TRUE
)

Arguments

vesalius_assay: vesalius_Assay object
method: character describing barcode pooling method. Currently, only "distance" availble
trial: character string describing which segmentation trial to use. Default is "last" which is the last segmentation trial used.
capture_radius: numeric - proportion of maximum distance between barcodes that will be used to pool barcodes together (range 0 - 1).
global: logical - If TRUE, territories will be numbered across all colour segments. If FALSE, territories will be numbered within each colour segment.
min_spatial_index: integer - minimum number of barcodes/spots/beads required in each territory
verbose: logical - progress message output.

Value

a vesalius_assay object

Details

Image segments can be further subdivided into 2D seperated territorires. This is accomplished by pooling barcodes that are associated with a colour cluster into territories based on the distance between each barcode.

First, isolate_territories considers the maximum distance between all beads. The capture_radius will define which proportion of this distance should be considered.

Second, a seed barcode will be selected and all barcodes that are within the capture distance of the seed barcode with be pooled together. This process is then applied on barcodes that have been selected in this manner. The process is repeated until all barcodes have been pooled into a territory. If there are still barcodes remaining, a new seed barcode is selected and the whole process is repeated. NOTE : Territory isolation is applied to each colour segment independently.

If a territory does not contain enough barcodes, it will be pooled into the isolated territory. This territory contains all isolated territories regardless of colour cluster of origin.

Examples

if (FALSE) { # \dontrun{
data(vesalius)
# First we build a simple object
ves <- build_vesalius_object(coordinates, counts)
# We can do a simple run
ves <- build_vesalius_embeddings(ves)

# simple smoothing
ves <- smooth_image(ves, dimensions = seq(1, 30))

# quick segmentation
ves <- segment_image(ves, dimensions = seq(1, 30))

# isolate territories
ves <- isolate_territories(ves)
} # }