Methods for Segmentation
objects
# S3 method for Segmentation
Cells(x, ...)
# S3 method for Segmentation
GetTissueCoordinates(object, full = TRUE, ...)
# S3 method for Segmentation
RenameCells(object, new.names = NULL, ...)
# S3 method for Segmentation
lengths(x, use.names = TRUE)
# S3 method for Segmentation
subset(x, cells = NULL, ...)
# S4 method for Segmentation,ANY,ANY,ANY
[(x, i, j, ..., drop = TRUE)
# S4 method for Segmentation
coordinates(obj, full = TRUE, ...)
# S4 method for Segmentation
show(object)
A
Segmentation
object
Arguments passed to other methods
Expand the coordinates to the full polygon
vector of new cell names
Ignored
A vector of cells to keep; if NULL
, defaults
to all cells
Ignored
Cells
: A vector of cell names
GetTissueCoordinates
, coordinates
: A data frame with
three columns:
“x
”: the x-coordinate
“y
”: the y-coordinate
“cell
” or “ID
”: the cell name
If full
is TRUE
, then each coordinate will indicate a vertex
for the cell polygon; otherwise, each coordinate will indicate a centroid
for the cell. Note: GetTissueCoordinates
....
RenameCells
: object
with the cells renamed to
new.names
lengths
: An rle
object for the cells
subset
, [
: x
subsetted to the cells specified
by cells
/i
show
: Invisibly returns NULL
Cells
: Get cell names
GetTissueCoordinates
, coordinates
: Get
tissue coordinates
RenameCells
: Update cell names
lengths
: Generate a run-length encoding of the cells present
subset
, [
: Subset a Segmentation
object to
certain cells
show
: Display an object summary to stdout
The following methods use progressr to render status updates and progress bars:
RenameCells
To enable progress updates, wrap
the function call in with_progress
or run
handlers(global = TRUE)
before running
this function. For more details about progressr, please read
vignette("progressr-intro")
The following methods use future to enable parallelization:
RenameCells
Parallelization strategies can be set using
plan
. Common plans include “sequential
”
for non-parallelized processing or “multisession
” for parallel
evaluation using multiple R sessions; for other plans, see the
“Implemented evaluation strategies” section of
?future::plan
. For a more thorough introduction
to future, see
vignette("future-1-overview")
Segmentation layer classes:
Centroids-class
,
Centroids-methods
,
Molecules-class
,
Molecules-methods
,
Segmentation-class