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.
ZanotelliSpheroids2020_sce(metadata = FALSE) ZanotelliSpheroids2020_images(metadata = FALSE) ZanotelliSpheroids2020_masks(metadata = FALSE)
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:
ZanotelliSpheroids2020Data contains 517 multichannel images,
each containing 51 channels, in the form of a CytoImageList
ZanotelliSpheroids2020Data contains the cell segmentation
masks associated with the images, in the form of a
CytoImageList class object.
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
ColData() for the SingleCellExperiment
object. Mapping at the image level can be performed with the
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 (
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
exprs_neighb: contains arsinh-transformed counts, with cofactor
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.
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
metadata slot of the SingleCellExperiment object
contains a graph of cell neighbors, generated with the
`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
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.
sce <- ZanotelliSpheroids2020Data(data_type = "sce") sce images <- ZanotelliSpheroids2020Data(data_type = "images") head(images) masks <- ZanotelliSpheroids2020Data(data_type = "masks") head(masks)
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