A Map of Human Type 1 Diabetes Progression by Imaging Mass Cytometry

Published: 9 April 2020| Version 2 | DOI: 10.17632/cydmwsfztj.2
Nicolas Damond


Data related to the publication: "A Map of Human Type 1 Diabetes Progression by Imaging Mass Cytometry". Damond N, Engler S, Zanotelli VRT, Schapiro D, Wasserfall CH, Kusmartseva I, Nick HS, Thorel F, Herrera PL, Atkinson MA and Bodenmiller B. Cell Metab. 2019 Mar 5;29(3):755-768.e5. https://doi.org/10.1016/j.cmet.2018.11.014 We used imaging mass cytometry to simultaneously image 37 biomarkers with single-cell and spatial resolution in pancreas sections from 12 human donors at different stages of type 1 diabetes. CODE: - Python script for coordinate transformation - Functions for custom histoCAT neighborhood analysis DATA: - Single-cell data - Islet-level data - Cell type information - Cell relationships (cell-cell neighborhoods and cell-islet relationships) - Donors and image metadata. - Subset containing the data for 100 images from 3 donors IMAGES: - Image stacks (37 channels) for all donors (one .7z file per donor, numbers indicate nPOD case IDs) - Cell masks - Panel file with information related to antibodies and metal tags - Metadata file linking donor information to images - Metadata file linking image stack slices and panel information - Subset containing 100 images from 3 donors



Universitat Zurich Institut fur Molekulare Biologie


Image Acquisition, Pancreas, Type 1 Diabetes, T Cell, Beta Cell