cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7575859
title: Example imaging mass cytometry raw data

description: If you are working with these files, please cite them as follows:Windhager, J., Zanotelli, V.R.T., Schulz, D. et al. An end-to-end workflow for multiplexed image processing and analysis. Nat Protoc (2023). https://doi.org/10.1038/s41596-023-00881-0
This imaging mass cytometry (IMC) dataset serves as an example to demonstrate raw data processing and downstream analysis tools. The data was generated as part of the Integrated iMMUnoprofiling of large adaptive CANcer patient cohorts (IMMUcan) project (immucan.eu) using the Hyperion imaging system (www.fluidigm.com/products-services/instruments/hyperion). To get an overview on the technology and available analysis strategies, please visit bodenmillergroup.github.io/IMCWorkflow. The individual data files are described below:

Patient1.zip, Patient2.zip, Patient3.zip, Patient4.zip: raw data files of 4 patient samples. Each .zip archive contains a folder in which one .mcd file (IMC raw data) and multiple .txt files (one per acquisition) can be found.
compensation.zip: This .zip archive holds a folder which contains one .mcd file and multiple .txt files. Multiple spots of a "spillover slide" were acquired and each .txt file is named based on the spotted metal. This data is used for channel spillover correction. For more information, please refer to the original publication: Compensation of Signal Spillover in Suspension and Imaging Mass Cytometry
panel.csv: This file contains metadata for each antibody/channel used in the experiment. The full column indicates which channel should be analysed. The ilastik column specifies which channels were used for ilastik pixel classification and the deepcell column indicates the channels used for deepcell segmentation.
sample_metadata.csv: This file links each patient to their cancer type (SCCHN - head and neck cancer; BCC - breast cancer; NSCLC - lung cancer; CRC - colorectal cancer).
DOI: 10.5281/zenodo.7624451
title: steinbock results of IMC example data

description: If you are working with these files, please cite them as follows:Windhager, J., Zanotelli, V.R.T., Schulz, D. et al. An end-to-end workflow for multiplexed image processing and analysis. Nat Protoc (2023). https://doi.org/10.1038/s41596-023-00881-0
This repository hosts the results of processing example imaging mass cytometry (IMC) data hosted at zenodo.org/record/5949116 using the steinbock framework available at github.com/BodenmillerGroup/steinbock. Please refer to steinbock.sh for how these data were generated from the raw data.
The following files are part of this repository:

panel.csv: contains channel information regarding the used antibodies in steinbock format
img.zip: contains hot pixel filtered multi-channel images derived from the IMC raw data. One file per acquisition is generated
images.csv: contains metadata per acquisition
pixel_classifier.ilp: ilastik pixel classifier (same as the  one in zenodo.org/record/6043544)
ilastik_crops.zip: image crops on which the ilastik classifier was trained (same as the ones in zenodo.org/record/6043544)
ilastik_img.zip: contains multi-channel images (one per acquisition) in .h5 format for ilastik pixel classification
ilastik_probabilities.zip: 3 channel images containing the pixel probabilities after pixel classification
masks_ilastik.zip: segmentation masks derived from the ilastik pixel probabilities using the cell_segmentation.cppipe pipeline
masks_deepcell.zip: segmentation masks derived by deepcell segmentation
intensities.zip: Contains one .csv file per acquisition. Each file contains single-cell measures of the mean pixel intensity per cell and channel based on the files in img.zip and masks_deepcell.zip.
regionprops.zip: Contains one .csv file per acquisition. Each file contains single-cell measures of the morphological features and location of cells based on masks_deepcell.zip.
neighbors.zip: Contains one .csv file per acquisition. Each file contains an edge list of cell IDs indicating cells in close proximity based on masks_deepcell.zip.
ome.zip: contains .ome.tiff files derived from img.zip; one file per acquisition
histocat.zip: contains single-channel .tiff files with segmentation masks derived from masks_deepcell.zip for upload to histoCAT (bodenmillergroup.github.io/histoCAT)
cells.csv: contains intensity and regionprop measurements of all cells
cells_csv.zip: contains intensity and regionprop measurements of all cells per acquisition
cells.fcs: contains intensity and regionprop measurements of all cells in fcs format
cells_fcs.zip: contains intensity and regionprop measurements of all cells per acquisition in fcs format
cells.h5ad: contains intensity, regionprop and neighbor measurements of all cells in anndata format
cells_h5ad: contains intensity regionprop and neighbor measurements of all cells per acquisition in anndata format
graphs.zip: contains spatial object graphs in .graphml format; one file per acquisition
DOI: 10.5281/zenodo.6043599
title: steinbock results of IMC example data

description: If you are working with these files, please cite them as follows:Windhager, J., Zanotelli, V.R.T., Schulz, D. et al. An end-to-end workflow for multiplexed image processing and analysis. Nat Protoc (2023). https://doi.org/10.1038/s41596-023-00881-0
This repository hosts the results of processing example imaging mass cytometry (IMC) data hosted at zenodo.org/record/5949116 using the steinbock framework available at github.com/BodenmillerGroup/steinbock. Please refer to steinbock.sh for how these data were generated from the raw data.
The following files are part of this repository:

panel.csv: contains channel information regarding the used antibodies in steinbock format
img.zip: contains hot pixel filtered multi-channel images derived from the IMC raw data. One file per acquisition is generated
images.csv: contains metadata per acquisition
pixel_classifier.ilp: ilastik pixel classifier (same as the  one in zenodo.org/record/6043544)
ilastik_crops.zip: image crops on which the ilastik classifier was trained (same as the ones in zenodo.org/record/6043544)
ilastik_img.zip: contains multi-channel images (one per acquisition) in .h5 format for ilastik pixel classification
ilastik_probabilities.zip: 3 channel images containing the pixel probabilities after pixel classification
masks_ilastik.zip: segmentation masks derived from the ilastik pixel probabilities using the cell_segmentation.cppipe pipeline
masks_deepcell.zip: segmentation masks derived by deepcell segmentation
intensities.zip: Contains one .csv file per acquisition. Each file contains single-cell measures of the mean pixel intensity per cell and channel based on the files in img.zip and masks_deepcell.zip.
regionprops.zip: Contains one .csv file per acquisition. Each file contains single-cell measures of the morphological features and location of cells based on masks_deepcell.zip.
neighbors.zip: Contains one .csv file per acquisition. Each file contains an edge list of cell IDs indicating cells in close proximity based on masks_deepcell.zip.
ome.zip: contains .ome.tiff files derived from img.zip; one file per acquisition
histocat.zip: contains single-channel .tiff files with segmentation masks derived from masks_deepcell.zip for upload to histoCAT (bodenmillergroup.github.io/histoCAT)
cells.csv: contains intensity and regionprop measurements of all cells
cells_csv.zip: contains intensity and regionprop measurements of all cells per acquisition
cells.fcs: contains intensity and regionprop measurements of all cells in fcs format
cells_fcs.zip: contains intensity and regionprop measurements of all cells per acquisition in fcs format
cells.h5ad: contains intensity, regionprop and neighbor measurements of all cells in anndata format
cells_h5ad: contains intensity regionprop and neighbor measurements of all cells per acquisition in anndata format
graphs.zip: contains spatial object graphs in .graphml format; one file per acquisition
DOI: 10.25502/0sps-wx25/d
title: Comparative study on direct-planted and transplanted yam nodal cuttings

description: YIIFSWA developed new strategies for improved propagation of quality yam planting materials and increased the multiplication ratio from 1:3 to 1:300 using leaf-bud cuttings.
DOI: 10.6084/m9.figshare.24639013
title: Supplementary Table 1: Late Cryogenian and Early Ediacaran Rare Metal-rich Granites in the Eastern Desert of Egypt: Constraints from Zircon Ages and Whole-Rock Sr- and Nd- and Feldspar Pb- Isotopic Compositions

description: Table 1. Samples.
DOI: 10.6084/m9.figshare.24639013.v1
title: Supplementary Table 1: Late Cryogenian and Early Ediacaran Rare Metal-rich Granites in the Eastern Desert of Egypt: Constraints from Zircon Ages and Whole-Rock Sr- and Nd- and Feldspar Pb- Isotopic Compositions

description: Table 1. Samples.
DOI: 10.6084/m9.figshare.24639019
title: Supplementary Table 3: Late Cryogenian and Early Ediacaran Rare Metal-rich Granites in the Eastern Desert of Egypt: Constraints from Zircon Ages and Whole-Rock Sr- and Nd- and Feldspar Pb- Isotopic Compositions

description: Table 3. d18O data table.
DOI: 10.6084/m9.figshare.24639019.v1
title: Supplementary Table 3: Late Cryogenian and Early Ediacaran Rare Metal-rich Granites in the Eastern Desert of Egypt: Constraints from Zircon Ages and Whole-Rock Sr- and Nd- and Feldspar Pb- Isotopic Compositions

description: Table 3. d18O data table.
DOI: 10.6084/m9.figshare.24639025
title: Supplementary Table 2: Late Cryogenian and Early Ediacaran Rare Metal-rich Granites in the Eastern Desert of Egypt: Constraints from Zircon Ages and Whole-Rock Sr- and Nd- and Feldspar Pb- Isotopic Compositions

description: Table 2. U-Pb data table.
DOI: 10.6084/m9.figshare.24639025.v1
title: Supplementary Table 2: Late Cryogenian and Early Ediacaran Rare Metal-rich Granites in the Eastern Desert of Egypt: Constraints from Zircon Ages and Whole-Rock Sr- and Nd- and Feldspar Pb- Isotopic Compositions

description: Table 2. U-Pb data table.
DOI: 10.5281/zenodo.6554611
title: Single-cell information extracted from IMC example data

description: This repository contains additional information related to IMC example data available at zenodo.org/record/5949116. The following files are available: <strong>gated_cells.zip:</strong> contains SpatialExperiment objects storing cells that were manually gated based on their expression values to derive ground truth cell phenotype labels.
DOI: 10.5281/zenodo.6807184
title: Single-cell information extracted from IMC example data

description: This repository contains additional information related to IMC example data available at zenodo.org/record/5949116. The following files are available and are part of the IMC Data Analysis workflow <strong>gated_cells.zip:</strong> contains SpatialExperiment objects storing cells that were manually gated based on their expression values to derive ground truth cell phenotype labels. <strong>spe.rds:</strong> SpatialExperiment object containing the single-cell information (mean intensity per cell and per channel; cellular metadata; channel metadata) of the processed data. <strong>images.rds:</strong> CytoImageList object containing the spillover-corrected images. <strong>masks.rds:</strong> CytoImageList object containing the segmentation masks.
DOI: 10.5281/zenodo.6670610
title: Single-cell information extracted from IMC example data

description: This repository contains additional information related to IMC example data available at zenodo.org/record/5949116. The following files are available: <strong>gated_cells.zip:</strong> contains SpatialExperiment objects storing cells that were manually gated based on their expression values to derive ground truth cell phenotype labels.
DOI: 10.5281/zenodo.6810879
title: Single-cell information extracted from IMC example data

description: This repository contains additional information related to IMC example data available at zenodo.org/record/5949116. The following files are available and are part of the IMC Data Analysis workflow <strong>gated_cells.zip:</strong> contains SpatialExperiment objects storing cells that were manually gated based on their expression values to derive ground truth cell phenotype labels. <strong>spe.rds:</strong> SpatialExperiment object containing the single-cell information (mean intensity per cell and per channel; cellular metadata; channel metadata) of the processed data. <strong>images.rds:</strong> CytoImageList object containing the spillover-corrected images. <strong>masks.rds:</strong> CytoImageList object containing the segmentation masks.
DOI: 10.5281/zenodo.7411425
title: Single-cell information extracted from IMC example data

description: This repository contains additional information related to IMC example data available at zenodo.org/record/5949116. The following files are available and are part of the IMC Data Analysis workflow <strong>gated_cells.zip:</strong> contains SpatialExperiment objects storing cells that were manually gated based on their expression values to derive ground truth cell phenotype labels. <strong>spe.rds:</strong> SpatialExperiment object containing the single-cell information (mean intensity per cell and per channel; cellular metadata; channel metadata) of the processed data. <strong>images.rds:</strong> CytoImageList object containing the spillover-corrected images. <strong>masks.rds:</strong> CytoImageList object containing the segmentation masks.
DOI: 10.5281/zenodo.7432486
title: Single-cell information extracted from IMC example data

description: This repository contains additional information related to IMC example data available at zenodo.org/record/5949116. The following files are available and are part of the IMC Data Analysis workflow <strong>gated_cells.zip:</strong> contains SpatialExperiment objects storing cells that were manually gated based on their expression values to derive ground truth cell phenotype labels. <strong>spe.rds:</strong> SpatialExperiment object containing the single-cell information (mean intensity per cell and per channel; cellular metadata; channel metadata) of the processed data. <strong>images.rds:</strong> CytoImageList object containing the spillover-corrected images. <strong>masks.rds:</strong> CytoImageList object containing the segmentation masks.
DOI: 10.5281/zenodo.7647079
title: Single-cell information extracted from IMC example data

description: This repository contains additional information related to IMC example data available at zenodo.org/record/5949116. The following files are available and are part of the IMC Data Analysis workflow <strong>gated_cells.zip:</strong> contains SpatialExperiment objects storing cells that were manually gated based on their expression values to derive ground truth cell phenotype labels. <strong>spe.rds:</strong> SpatialExperiment object containing the single-cell information (mean intensity per cell and per channel; cellular metadata; channel metadata) of the processed data. <strong>images.rds:</strong> CytoImageList object containing the spillover-corrected images. <strong>masks.rds:</strong> CytoImageList object containing the segmentation masks.
DOI: 10.5281/zenodo.6554544
title: Single-cell information extracted from IMC example data

description: If you are working with these files, please cite them as follows:Windhager, J., Zanotelli, V.R.T., Schulz, D. et al. An end-to-end workflow for multiplexed image processing and analysis. Nat Protoc (2023). https://doi.org/10.1038/s41596-023-00881-0
This repository contains additional information related to IMC example data available at zenodo.org/record/5949116. The following files are available and are part of the IMC Data Analysis workflow

gated_cells.zip: contains SpatialExperiment objects storing cells that were manually gated based on their expression values to derive ground truth cell phenotype labels.
spe.rds: SpatialExperiment object containing the single-cell information (mean intensity per cell and per channel; cellular metadata; channel metadata) of the processed data.
images.rds: CytoImageList object containing the spillover-corrected images.
masks.rds: CytoImageList object containing the segmentation masks.
DOI: 10.5281/zenodo.6554545
title: Single-cell information extracted from IMC example data

description: This repository contains additional information related to IMC example data available at zenodo.org/record/5949116. The following files are available: <strong>gated_cells.zip:</strong> contains SpatialExperiment objects storing cells that were manually gated based on their expression values to derive ground truth cell phenotype labels.
DOI: 10.5281/zenodo.7079294
title: Single-cell information extracted from IMC example data

description: This repository contains additional information related to IMC example data available at zenodo.org/record/5949116. The following files are available and are part of the IMC Data Analysis workflow <strong>gated_cells.zip:</strong> contains SpatialExperiment objects storing cells that were manually gated based on their expression values to derive ground truth cell phenotype labels. <strong>spe.rds:</strong> SpatialExperiment object containing the single-cell information (mean intensity per cell and per channel; cellular metadata; channel metadata) of the processed data. <strong>images.rds:</strong> CytoImageList object containing the spillover-corrected images. <strong>masks.rds:</strong> CytoImageList object containing the segmentation masks.
DOI: 10.5281/zenodo.8095133
title: Single-cell information extracted from IMC example data

description: If you are working with these files, please cite them as follows:Windhager, J., Zanotelli, V.R.T., Schulz, D. et al. An end-to-end workflow for multiplexed image processing and analysis. Nat Protoc (2023). https://doi.org/10.1038/s41596-023-00881-0
This repository contains additional information related to IMC example data available at zenodo.org/record/5949116. The following files are available and are part of the IMC Data Analysis workflow

gated_cells.zip: contains SpatialExperiment objects storing cells that were manually gated based on their expression values to derive ground truth cell phenotype labels.
spe.rds: SpatialExperiment object containing the single-cell information (mean intensity per cell and per channel; cellular metadata; channel metadata) of the processed data.
images.rds: CytoImageList object containing the spillover-corrected images.
masks.rds: CytoImageList object containing the segmentation masks.
DOI: 10.5281/zenodo.10210274
title: Kinect Dataset (Raw video) (Part 2)

description: Contains the raw video of the long and short captures.
Data structure:long_capture/calibration.json
long_capture/data.jsonl
long_capture/data.mkv
long_capture/data2.mkv
long_capture/vio_config.yaml
short_capture/calibration.json
short_capture/data.jsonl
short_capture/data.mkv
short_capture/data2.mkv
short_capture/vio_config.yaml
DOI: 10.5281/zenodo.10210273
title: Kinect Dataset (Raw video) (Part 2)

description: Contains the raw video of the long and short captures.
Data structure:long_capture/calibration.json
long_capture/data.jsonl
long_capture/data.mkv
long_capture/data2.mkv
long_capture/vio_config.yaml
short_capture/calibration.json
short_capture/data.jsonl
short_capture/data.mkv
short_capture/data2.mkv
short_capture/vio_config.yaml
DOI: 10.5281/zenodo.6043544
title: IMC Segmentation Pipeline results of example IMC data

description: This repository hosts the results of processing example imaging mass cytometry (IMC) data hosted at 10.5281/zenodo.5949116 using the IMC Segmentation Pipeline available at https://github.com/BodenmillerGroup/ImcSegmentationPipeline. Please refer to https://github.com/BodenmillerGroup/steinbock as alternative processing framework and 10.5281/zenodo.6043600 for the data generated by <em>steinbock</em>. The following files are part of the "analysis" folder when running the IMC Segmentation Pipeline: <strong>cpinp.zip</strong>: contains input files for the segmentation pipeline <strong>cpout.zip</strong>: contains all final output files of the pipeline: <em>cell.csv</em> containing the single-cell features; <em>Experiment.csv</em> containing CellProfiler metadata; <em>Image.csv</em> containing acquisition metadata; <em>Object relationships.csv</em> containing an edge list indicating interacting cells; <em>panel.csv</em> containing channel information; <em>var_cell.csv</em> containing cell feature information; <em>var_Image.csv</em> containing acquisition feature information <strong>histocat.zip</strong>: contains single channel .tiff files per acquisition for upload to histoCAT (https://bodenmillergroup.github.io/histoCAT/) <strong>ilastik.zip</strong>: contains upscaled image crops in .h5 format for ilastik (https://www.ilastik.org/) training <strong>ometiff.zip</strong>: contains .ome.tiff files per acquisition, .png files per panorama and additional metadata files per slide <strong>tiffs.zip</strong>: contains multi channel .tiff files of all channels for analysis (<em>_full.tiff</em>) and their channel order (<em>_full.csv</em>); multi channel images for ilastik pixel classification (<em>_ilastik.full</em>) and their channel order (<em>_ilastik.csv</em>); upscaled multi channel images for ilastik pixel prediction (<em>_ilastik_s2.h5</em>); 3 channel images containing ilastik pixel probabilities (<em>_ilastik_s2_Probabilities.tiff</em>) and segmentation masks (<em>_ilastik_s2_Probabilities_mask.tiff</em>). The remaining files are part of the root directory: <strong>config.zip</strong>: containing the antibody panel used for the experiment. <strong>cp4_pipelines.zip</strong>: containing the CellProfiler pipelines for analysis. <strong>documentation.zip</strong>: containing a description of the IMC Segmentation Pipeline <strong>scripts.zip</strong>: containing a jupyter notebook to perform image pre-processing <strong>setup.zip</strong>: containing a .yml describing the dependencies to be installed via conda