ZanotelliSpheroids2020: Deprecated function - 'ZanotelliSpheroids2020' dataset

In BodenmillerGroup/imcdatasets: Collection of publicly available imaging mass cytometry (IMC) datasets

Deprecated function - 'ZanotelliSpheroids2020' dataset

Description

These functions are provided for compatibility with older versions of ‘imcdatasets’ only, and will be defunct at the next release. This dataset consists consists of three data objects: single cell data, multichannel images and cell segmentation masks. The data were obtained by imaging mass cytometry of sections of 3D spheroids generated from different cell lines.

Usage

ZanotelliSpheroids2020_sce(metadata = FALSE)
ZanotelliSpheroids2020_images(metadata = FALSE)
ZanotelliSpheroids2020_masks(metadata = FALSE)

Arguments

metadata

logical value indicating whether ExperimentHub metadata (describing the overall dataset) should be returned only, or if the whole dataset should be loaded. Default = FALSE, which loads the whole dataset.

Details

This is an Imaging Mass Cytometry (IMC) dataset from Zanotelli et al. (2020), consisting of three data objects. Note: The following functions are deprecated and will be made defunct; use the replacements indicated below:

• ZanotelliSpheroids2020_images -> ZanotelliSpheroids2020Data contains 517 multichannel images, each containing 51 channels, in the form of a CytoImageList class object.

• ZanotelliSpheroids2020_masks -> ZanotelliSpheroids2020Data contains the cell segmentation masks associated with the images, in the form of a CytoImageList class object.

• ZanotelliSpheroids2020_sce -> ZanotelliSpheroids2020Data contains the single cell data extracted from the images using the cell segmentation masks, as well as the associated metadata, in the form of a SingleCellExperiment. This represents a total of 229,047 cells x 51 channels.

All data are downloaded from ExperimentHub and cached for local re-use.

Mapping between the three data objects is performed via variables located in their metadata columns: mcols() for the CytoImageList objects and ColData() for the SingleCellExperiment object. Mapping at the image level can be performed with the ImageName or ImageNumber variables. Mapping between cell segmentation masks and single cell data is performed with the CellNumber variable, the values of which correspond to the intensity values of the ZanotelliSpheroids2020_masks object. For practical examples, please refer to the "Accessing IMC datasets" vignette.

This dataset was obtained as following (the names of the experimental variables, located in the colData of the SingleCellExperiment object, are indicated in parentheses): i) Cells from four different cell lines (cellline) were seeded at three different densities (concentration, relative densities) and grown for either 72 or 96 hours (time_point, duration in hours). In the appropriate experimental conditions (see the paper for details), the cells aggregate into 3D spheroids. ii) Cells were harvested and pooled into 60-well barcoding plates. iii) A pellet of each spheroid pool was generated and cut into several 6 um-thick sections. iv) A subset of these sections (site_id) were stained with an IMC panel and acquired as one or more acquisitions (acquisition_id) containing multiple spheres each. v) Spheres in these acquisitions were identified by computer vision and cropped into individual images (ImageNumber).

Other relevant cell metadata include:

• condition_name: experimental conditions in the format: "Cell line name"_c"seeding density"_tp"time point".

• Center_X/Y: object centroid position in image.

• Area: area of the cell (um^2).

• dist.rim: estimated distance to spheroid border.

• dist.sphere: distance to spheroid section border.

• dist.other: distance to the closest of the other spheroid sections in the same image (if there is any).

• dist.bg: distance to background pixels.

• counts_neighb: contains arsinh-transformed counts, with cofactor 1.

• exprs_neighb: contains arsinh-transformed counts, with cofactor 1.

For a full description of the other experimental variables, please refer to the publication (https://doi.org/10.15252/msb.20209798) and to the original dataset repository (https://doi.org/10.5281/zenodo.4271910).

The marker-associated metadata, including antibody information and metal tags are stored in the rowData of the SingleCellExperiment object. The channels with names starting with "BC_" are the channels used for barcoding. Post-transcriptional modification of the protein targets are indicated in brackets.

The assay slot of the SingleCellExperiment object contains four assays:

• counts: mean ion counts per cell.

• exprs: arsinh-transformed counts per cell, with cofactor 1.

• counts_neighb: mean ion counts of the neighboring cells.

• exprs_neighb: arsinh-transformed counts (cofactor 1) of the neighboring cells.

The metadata slot of the SingleCellExperiment object contains a graph of cell neighbors, generated with the igraph::graph_from_data_frame function.

File sizes:

• `images`: size in memory = 21.2 Gb, size on disk = 881 Mb.

• `masks`: size in memory = 426 Mb, size on disk = 11.6 Mb.

• `sce`: size in memory = 584 Mb, size on disk = 340 Mb.

Original source: Zanotelli et al. (2020): https://doi.org/10.15252/msb.20209798

Original link to raw data, also containing the entire dataset: https://doi.org/10.5281/zenodo.4271910

Value

Returns a SingleCellExperiment or CytoImageList object.

Author(s)

Nicolas Damond

Source

Publication Original dataset

References

Zanotelli VRT et al. (2020). A quantitative analysis of the interplay of environment, neighborhood, and cell state in 3D spheroids Mol Syst Biol 16(12), e9798.

Examples

sce <- ZanotelliSpheroids2020Data(data_type = "sce")
sce
images <- ZanotelliSpheroids2020Data(data_type = "images")
head(images)
masks <- ZanotelliSpheroids2020Data(data_type = "masks")
head(masks)

BodenmillerGroup/imcdatasets documentation built on July 5, 2022, 4:34 p.m.