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


x, object, obj

A Segmentation object


Arguments passed to other methods


Expand the coordinates to the full polygon


vector of new cell names



i, cells

A vector of cells to keep; if NULL, defaults to all cells

j, drop



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

Progress Updates with progressr

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")

Parallelization with future

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")