Imaging mass cytometry of human pancreas in type 1 diabetes (Damond et al. 2019)

Cell types and positions from imaging mass cytometry of pancreas sections from 12 donors at three stages of type 1 diabetes (Damond et al. 2019): 4 non-diabetic donors, 4 at onset and 4 with long-duration disease. The object holds 253,777 cells from 120 images, 10 images per donor. It has no assays: only the cell data used by spicyR.

Usage

data("diabetesData")

Format

A SingleCellExperiment with one column per cell and these colData columns:

imageID: the image (character)
cellID, imageCellID: cell identifiers, in the whole data set and within its image
x, y: the cell's coordinates in the image, in micrometres
cellType: the cell type assigned by the authors (factor)
case: the donor (integer)
slide, part: the slide, and the part of the pancreas (head, body or tail)
group, stage: the stage of type 1 diabetes, as a code and as a factor with levels "Non-diabetic", "Onset" and "Long-duration"

Source

Damond N et al. (2019). Mendeley Data, doi:10.17632/cydmwsfztj.1 , under the CC BY 4.0 licence. How the subset was made is described in inst/scripts/make-diabetesData.R.

References

Damond N, Engler S, Zanotelli VRT, et al. (2019). A map of human type 1 diabetes progression by imaging mass cytometry. Cell Metabolism 29(3), 755-768. doi:10.1016/j.cmet.2018.11.014

Examples

data("diabetesData")
table(unique(as.data.frame(SummarizedExperiment::colData(diabetesData))[, c("case", "stage")])$stage)
#> 
#>  Non-diabetic         Onset Long-duration 
#>             4             4             4