plotCells: Function to visualize cell-level information on segmentation...

In cytomapper: Visualization of highly multiplexed imaging data in R

Description

This function takes a SingleCellExperiment and CytoImageList object containing segmentation masks to colour cells by marker expression or metadata.

Usage

plotCells(
    mask,
    object = NULL,
    cell_id = NULL,
    img_id = NULL,
    colour_by = NULL,
    outline_by = NULL,
    exprs_values = "counts",
    colour = NULL,
    ...
)

Arguments

mask	a CytoImageList containing single-channel Image objects (see section 'Segmentation mask object' below).
object	a SingleCellExperiment object.
cell_id	character specifying the colData(object) entry, in which the integer cell IDs are stored. These IDs should match the integer pixel values in the segmentation mask object.
img_id	character specifying the colData(object) and mcols(mask) entry, in which the image IDs are stored (see section 'Linking the SingleCellExperiment and CytoImageList object' below)
colour_by	character or character vector specifying the features (rownames(object)) or metadata (colData(object) entry) used to colour individual cells. Cells can be coloured by single colData(object) entries or by up to six features.
outline_by	single character indicating the colData(object) entry by which to outline individual cells.
exprs_values	single character indicating which assay(object) entry to use when visualizing feature counts.
colour	a list with names matching the entries to colour_by and/or outline_by. When setting the colour for continous features, at least two colours need to be provided indicating the colours for minimum and maximum values. When colouring discrete vectors, a colour for each unique entry needs to be provided (see section 'Setting the colours' and examples)
...	Further arguments passed to ?"plotting-param"

Value

a list if return_images and/or return_plot is TRUE (see ?"plotting-param").

• plot: a single plot object (display = "all") or a list of plot objects (display = "single")

• images: a SimpleList object containing three-colour Image objects.

Segmentation mask object

In the plotCells function, mask refers to a CytoImageList object that contains a single or multiple segmentation masks in form of individual Image objects. The function assumes that each object in the segmentation mask is a cell. The key features of such masks include:

• each Image object contains only one channel

• pixel values are integers indicating the cells' IDs or 0 (background)

Linking SingleCellExperiment and CytoImageList objects

To colour individual cells contained in the segmentation masks based on features and metadata stored in the SingleCellExperiment object, an img_id and cell_id entry needs to be provided. Image IDs are matched between the SingleCellExperiment and CytoImageList object via entries to the colData(object)[,img_id] and the mcols(mask)[,img_id] slots. Cell IDs are matched between the SingleCellExperiment and CytoImageList object via entries to colData(object)[,cell_id] and the integer values of the segmentation masks.

Setting the colours

By default, features and metadata are coloured based on internally-set colours. To set new colours, a list object must be provided. The names of the object must correspond to the entries to colour_by and/or outline_by. When setting the colours for continous expression values or continous metadata entries, a vector of at least two colours need to be specified. These colours will be passed onto colorRampPalette for interpolation. Discrete metadata entries can be coloured by specifying a named vector in which each entry corresponds to a unique entry to the metadata vector.

Subsetting the CytoImageList object

The CytoImageList object can be subsetted before calling the plotCells function. In that case, only the selected images are displayed.

Subsetting the SingleCellExperiment object

The SingleCellExperiment object can be subsetted before calling the plotCells function. In that case, only cells contained in the SingleCellExperiment object are coloured/outlined.

Colour scaling

When colouring features using the plotCells function, colours are scaled between the minimum and maximum per feature across the full assay contained in the SingleCellExperiment object. When subsetting images, cell-level expression is not scaled across the subsetted images but the whole SingleCellExperiment object. To avoid this, the SingleCellExperiment object can be subsetted to only contain the cells that should be displayed before plotting.

Author(s)

Nils Eling ([e-mail])

Nicolas Damond ([e-mail])

See Also

For further plotting parameters see ?"plotting-param"

Examples

data(pancreasMasks)
data(pancreasSCE)

# Visualize the masks
plotCells(pancreasMasks)

# Colour the masks based on averaged expression
plotCells(pancreasMasks, object = pancreasSCE, img_id = "ImageNb",
            cell_id = "CellNb", colour_by = c("CD99", "CDH"))

# Colour the masks based on metadata
plotCells(pancreasMasks, object = pancreasSCE, img_id = "ImageNb",
            cell_id = "CellNb", colour_by = "CellType")

# Outline the masks based on metadata
plotCells(pancreasMasks, object = pancreasSCE, img_id = "ImageNb",
            cell_id = "CellNb", colour_by = "CD99",
            outline_by = "CellType")

# Colour the masks based on arcsinh-transformed expression
plotCells(pancreasMasks, object = pancreasSCE, img_id = "ImageNb",
            cell_id = "CellNb", colour_by = "CD99",
            exprs_values = "exprs")

# Subset the images
cur_images <- getImages(pancreasMasks, 1:2)
plotCells(cur_images, object = pancreasSCE, img_id = "ImageNb",
            cell_id = "CellNb", colour_by = "CD99")

# Set colour
plotCells(pancreasMasks, object = pancreasSCE, img_id = "ImageNb",
            cell_id = "CellNb", colour_by = "CD99", outline_by = "CellType",
            colour = list(CD99 = c("black", "red"),
                            CellType = c(celltype_A = "blue",
                                        celltype_B = "green",
                                        celltype_C = "red")))

cytomapper documentation built on Jan. 30, 2021, 2:01 a.m.