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DOI . ORG {}

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  2. Matching Content Categories
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  6. Keywords
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We began analyzing https://zenodo.org/records/5850952, but it redirected us to https://zenodo.org/records/5850952. The analysis below is for the second page.

Title[redir]:
Breast tumour microenvironment structures are associated with genomic features and clinical outcome
Description:
The data comprise three types: Full stack tiff images that contain multiplexed imaging mass cytometry (IMC) images. Image masks that identify image regions associated with cells, epithelium and vessels Processed data that contain measurements taken using the associated images.     All full stacks and masks are tiff images. Each IMC acquisition (image) is associated with six images in total: the full stack image itself and five image masks (whole cell, nucleus, cytoplasm, tumour and vessel). The naming convention for these images is MB####_###_ImageType.tiff, where: MB#### is the METABRIC identifier. This can be used to link the data to other METABRIC data in the public domain. ### is the ImageNumber. This links the image to columns in processed data files. It is a sequential integer between one and three digits long. Note that this number, assigned based on file order, is not the same across studies so cannot be used to link images from other METABRIC data sets e.g. Ali et al Nat Cancer 2020. Each image corresponds to a core from a tissue microarray (TMA) slide. ImageType. A descriptive label that identifies the type of image. Notes: The order of image layers in full stack images corresponds to the markerStackOrder.csv file, which identifies each image layer with its corresponding isotope and epitope. Masks are grayscale images where each discrete region is identified by a set of contiguous pixels associated with a single integer value. These tend to be sequential from the top to the bottom of the image (this is why a mask appears as a gradation of gray and white when opened in an image viewer). The processed single cell data ‘ObjectNumber’ column corresponds to whole cell masks, where the integer values of each cell maps to ‘ObjectNumber’, allowing for marker values and other features to be mapped to images.     Two processed data files: SingleCells.csv where each row represents a cell, and columns are data associated with each cell. Each observation is uniquely identified by the combination of ImageNumber and ObjectNumber. These data have already been spillover corrected. Single cell measurements correspond to

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Not every website is profit-driven; some are created to spread information or serve as an online presence. Websites can be made for many reasons. This could be one of them. Doi.org might be making money, but it's not detectable how they're doing it.

Keywords {🔍}

data, image, images, cell, files, masks, processed, full, columns, objectnumber, cookies, version, dataset, tumour, show, stack, imc, convention, metabric, integer, corresponds, single, column, details, january, breast, microenvironment, features, ali, tiff, imaging, mass, cytometry, measurements, link, imagenumber, sequential, file, order, cancer, identifies, type, notes, identified, values, singlecellscsv, row, represents, annotation, metabricbreastcancerimctmezip,

Topics {✒️}

type imc acquisition tumour dataset details vessels processed data processed tabular files processed data files column annotation files full stack image imc published january 14 metabric data sets cell-cell interaction identify image regions support 'cellmask' image masks single integer image corresponds newer version metabric data full stacks annotation files data comprise zip files cell maps index cell neighbouring cell cell masks metabric identifier tiff images main communities dashboard log public domain digits long assigned based tissue microarray descriptive label discrete region contiguous pixels mask appears integer values marker values row represents spillover corrected graph format `is_` variables zip md5 openaire keywords image layers

Schema {🗺️}

https://schema.org/Dataset:
      context:http://schema.org
      id:https://doi.org/10.5281/zenodo.5850952
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            type:Person
            affiliation:
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                  name:CRUK Cambridge Institute, University of Cambridge, Cambridge, UK
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      contentSize:5.79 GB
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                  name:CRUK Cambridge Institute, University of Cambridge, Cambridge, UK
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            type:Person
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                  name:CRUK Cambridge Institute, University of Cambridge, Cambridge, UK
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            name:Bardwell, Helen
            type:Person
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                  type:Organization
                  name:Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
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                  name:Department of Histopathology, Addenbrookes Hospital, Cambridge, UK
            familyName:Provenzano
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            name:Provenzano, Elena
            type:Person
            affiliation:
                  type:Organization
                  name:CRUK Cambridge Institute, University of Cambridge, Cambridge, UK
            familyName:Chin
            givenName:Suet-Feung
            name:Chin, Suet-Feung
            type:Person
            affiliation:
                  type:Organization
                  name:MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
            familyName:Rueda
            givenName:Oscar M
            name:Rueda, Oscar M
            type:Person
            affiliation:
                  type:Organization
                  name:Department of Pathology, University of Nottingham, Nottingham, UK
            familyName:Green
            givenName:Andrew
            name:Green, Andrew
            type:Person
            affiliation:
                  type:Organization
                  name:Department of Pathology, University of Nottingham, Nottingham, UK
            familyName:Rakha
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            affiliation:
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                  name:British Columbia Cancer Agency, University of British Columbia, Vancouver, Canada
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            type:Person
            affiliation:
                  type:Organization
                  name:Department of Pathology, University of Nottingham, Nottingham, UK
            familyName:Ellis
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            type:Person
            affiliation:
                  type:Organization
                  name:Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
            familyName:Bodenmiller
            givenName:Bernd
            name:Bodenmiller, Bernd
            type:Person
            affiliation:
                  type:Organization
                  name:CRUK Cambridge Institute, University of Cambridge, Cambridge, UK
            familyName:Caldas
            givenName:Carlos
            name:Caldas, Carlos
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            type:Person
            affiliation:
                  type:Organization
                  name:CRUK Cambridge Institute, University of Cambridge, Cambridge, UK
            familyName:Ali
            givenName:H. Raza
            name:Ali, H. Raza
      dateCreated:2022-01-14T17:46:14.704989+00:00
      dateModified:2022-11-16T16:33:13.455079+00:00
      datePublished:2022-01-14
      description:<p>The data comprise three types:</p> <ol> <li>Full stack tiff images that contain multiplexed imaging mass cytometry (IMC) images.</li> <li>Image masks that identify image regions associated with cells, epithelium and vessels</li> <li>Processed data that contain measurements taken using the associated images.</li> </ol> <p>&nbsp;</p> <p>&nbsp;</p> <p>All full stacks and masks are tiff images. Each IMC acquisition (image) is associated with six images in total: the full stack image itself and five image masks (whole cell, nucleus, cytoplasm, tumour and vessel). The naming convention for these images is MB####_###_ImageType.tiff, where:</p> <ul> <li>MB#### is the METABRIC identifier. This can be used to link the data to other METABRIC data in the public domain.</li> <li>### is the ImageNumber. This links the image to columns in processed data files. It is a sequential integer between one and three digits long. Note that this number, assigned based on file order, is not the same across studies so cannot be used to link images from other METABRIC data sets e.g. Ali et al Nat Cancer 2020. Each image corresponds to a core from a tissue microarray (TMA) slide.</li> <li>ImageType. A descriptive label that identifies the type of image.</li> </ul> <p>Notes:</p> <p>The order of image layers in full stack images corresponds to the markerStackOrder.csv file, which identifies each image layer with its corresponding isotope and epitope.</p> <p>Masks are grayscale images where each discrete region is identified by a set of contiguous pixels associated with a single integer value. These tend to be sequential from the top to the bottom of the image (this is why a mask appears as a gradation of gray and white when opened in an image viewer). The processed single cell data &lsquo;ObjectNumber&rsquo; column corresponds to whole cell masks, where the integer values of each cell maps to &lsquo;ObjectNumber&rsquo;, allowing for marker values and other features to be mapped to images.</p> <p>&nbsp;</p> <p>&nbsp;</p> <p>Two processed data files:</p> <p>SingleCells.csv where each row represents a cell, and columns are data associated with each cell. Each observation is uniquely identified by the combination of ImageNumber and ObjectNumber. These data have already been spillover corrected. Single cell measurements correspond to &#39;CellMask&#39; image masks.</p> <p>CellNeighbours.csv where each row represents a cell-cell interaction. The data are in graph format, with columns labelled &lsquo;from&rsquo; and &lsquo;to&rsquo; meaning <strong>from</strong> an index cell <strong>to</strong> a neighbouring cell (despite this convention, the data are undirected); the integers within these columns map to ObjectNumber in SingleCells.csv.</p> <p>Notes: The convention for `is_` variables in processed data files is that 0 is FALSE and 1 TRUE.</p> <p>&nbsp;</p> <p>&nbsp;</p> <p>Two column annotation files:</p> <p>Two corresponding annotation files that contain details on the content of each column in processed tabular files are also provided, they are SingleCellsAnnotation.xlsx and CellNeighboursAnnotation.xlsx</p>
      distribution:
            type:DataDownload
            contentUrl:https://zenodo.org/api/records/5850952/files/METABRICBreastCancerIMCTME.zip/content
            encodingFormat:application/zip
      identifier:https://doi.org/10.5281/zenodo.5850952
      keywords:Imaging mass cytometry, Breast cancer, Tumour microenvironment, TME, IMC, Hisopathology
      license:https://creativecommons.org/licenses/by/4.0/legalcode
      name:Breast tumour microenvironment structures are associated with genomic features and clinical outcome
      publisher:
         type:Organization
         name:Zenodo
      size:5.79 GB
      url:https://zenodo.org/records/5850952
      version:1.0.0
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            name:CRUK Cambridge Institute, University of Cambridge, Cambridge, UK
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      affiliation:
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            name:CRUK Cambridge Institute, University of Cambridge, Cambridge, UK
      familyName:Bardwell
      givenName:Helen
      name:Bardwell, Helen
      affiliation:
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            name:Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
      familyName:Zanotelli
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      name:Zanotelli, Vito RT
      affiliation:
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      familyName:Provenzano
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      name:Provenzano, Elena
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            name:CRUK Cambridge Institute, University of Cambridge, Cambridge, UK
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      affiliation:
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            name:MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
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      affiliation:
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      affiliation:
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            name:Department of Pathology, University of Nottingham, Nottingham, UK
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            name:Department of Pathology, University of Nottingham, Nottingham, UK
      familyName:Ellis
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      affiliation:
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            name:Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
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            name:CRUK Cambridge Institute, University of Cambridge, Cambridge, UK
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      name:Danenberg, Esther
      affiliation:
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            name:CRUK Cambridge Institute, University of Cambridge, Cambridge, UK
      familyName:Bardwell
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      name:Bardwell, Helen
      affiliation:
            type:Organization
            name:Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
      familyName:Zanotelli
      givenName:Vito RT
      name:Zanotelli, Vito RT
      affiliation:
            type:Organization
            name:Department of Histopathology, Addenbrookes Hospital, Cambridge, UK
      familyName:Provenzano
      givenName:Elena
      name:Provenzano, Elena
      affiliation:
            type:Organization
            name:CRUK Cambridge Institute, University of Cambridge, Cambridge, UK
      familyName:Chin
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      name:Chin, Suet-Feung
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            name:MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
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            name:Department of Pathology, University of Nottingham, Nottingham, UK
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      name:Green, Andrew
      affiliation:
            type:Organization
            name:Department of Pathology, University of Nottingham, Nottingham, UK
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      name:Aparicio, Samuel
      affiliation:
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            name:Department of Pathology, University of Nottingham, Nottingham, UK
      familyName:Ellis
      givenName:Ian O
      name:Ellis, Ian O
      affiliation:
            type:Organization
            name:Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
      familyName:Bodenmiller
      givenName:Bernd
      name:Bodenmiller, Bernd
      affiliation:
            type:Organization
            name:CRUK Cambridge Institute, University of Cambridge, Cambridge, UK
      familyName:Caldas
      givenName:Carlos
      name:Caldas, Carlos
      id:https://orcid.org/0000-0001-7587-0906
      affiliation:
            type:Organization
            name:CRUK Cambridge Institute, University of Cambridge, Cambridge, UK
      familyName:Ali
      givenName:H. Raza
      name:Ali, H. Raza
Organization:
      name:CRUK Cambridge Institute, University of Cambridge, Cambridge, UK
      name:CRUK Cambridge Institute, University of Cambridge, Cambridge, UK
      name:Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
      name:Department of Histopathology, Addenbrookes Hospital, Cambridge, UK
      name:CRUK Cambridge Institute, University of Cambridge, Cambridge, UK
      name:MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
      name:Department of Pathology, University of Nottingham, Nottingham, UK
      name:Department of Pathology, University of Nottingham, Nottingham, UK
      name:British Columbia Cancer Agency, University of British Columbia, Vancouver, Canada
      name:Department of Pathology, University of Nottingham, Nottingham, UK
      name:Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
      name:CRUK Cambridge Institute, University of Cambridge, Cambridge, UK
      name:CRUK Cambridge Institute, University of Cambridge, Cambridge, UK
      name:CRUK Cambridge Institute, University of Cambridge, Cambridge, UK
      name:CRUK Cambridge Institute, University of Cambridge, Cambridge, UK
      name:Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
      name:Department of Histopathology, Addenbrookes Hospital, Cambridge, UK
      name:CRUK Cambridge Institute, University of Cambridge, Cambridge, UK
      name:MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
      name:Department of Pathology, University of Nottingham, Nottingham, UK
      name:Department of Pathology, University of Nottingham, Nottingham, UK
      name:British Columbia Cancer Agency, University of British Columbia, Vancouver, Canada
      name:Department of Pathology, University of Nottingham, Nottingham, UK
      name:Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
      name:CRUK Cambridge Institute, University of Cambridge, Cambridge, UK
      name:CRUK Cambridge Institute, University of Cambridge, Cambridge, UK
      name:Zenodo
DataDownload:
      contentUrl:https://zenodo.org/api/records/5850952/files/METABRICBreastCancerIMCTME.zip/content
      encodingFormat:application/zip

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