2 datasets found
  1. f

    Processed CODEX Data (Seurat Objects)

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    application/gzip
    Updated Apr 12, 2024
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    Shovik Bandyopadhyay; Jonathan Sussman; Kyung Jin Ahn; Kai Tan (2024). Processed CODEX Data (Seurat Objects) [Dataset]. http://doi.org/10.25452/figshare.plus.25127657.v1
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    application/gzipAvailable download formats
    Dataset updated
    Apr 12, 2024
    Dataset provided by
    Figshare+
    Authors
    Shovik Bandyopadhyay; Jonathan Sussman; Kyung Jin Ahn; Kai Tan
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Seurat objects containing the raw and normalized data for:Normal bone marrow (NBM) atlas: contains all cells obtained through segmentation after filtering and QC. Includes coarse and fine level of annotations that were obtained through an iterative process of subclustering. Neighborhood analysis results are included as a metadata column. Additional Osteo-MSC and Fibro-MSC cells that were manually annotatedAML/NSM CODEX data: contains all cells after filtering for 3 diagnostic and 2 post-therapy AML samples as well as 3 negative staging marrow samples. Cell labels were derived through reciprocal principal component analysis (RPCA) reference mapping onto the normal bone marrow atlas. Neighborhood analysis was conducted separately for AML Diagnostic, AML Post-Therapy, and NSM samples. Neighborhoods were manually annotated for each set. The results of the neighborhood analysis were merged and included in the metadata of the Seurat object. All normalized data is stored in the Seurat assay object. Markers that were not included in normalization and downstream analysis are included with raw values as a metadata column. Full source code used to generate these objects can be found on GitHub: https://github.com/shovikb94/spatial-bonemarrow-atlas/tree/mainSee related materials in Collection at: https://doi.org/10.25452/figshare.plus.c.7174914

  2. snRNA-seq, CT2A and GL261 murine tumors

    • figshare.com
    bin
    Updated Oct 24, 2024
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    Nicholas Mikolajewicz (2024). snRNA-seq, CT2A and GL261 murine tumors [Dataset]. http://doi.org/10.6084/m9.figshare.25685523.v2
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    binAvailable download formats
    Dataset updated
    Oct 24, 2024
    Dataset provided by
    figshare
    Authors
    Nicholas Mikolajewicz
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    R object containing seurat object of integrated sham, and CT2A- and GL261-engrafted brain samples. Data were integrated using rPCA and annotated as described in the corresponding manuscript (Mikolajewicz 2024). Please contact Dr. Nicholas Mikolajewicz (n.mikolajewicz@utoronto.ca) for any questions regarding the data.

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Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Shovik Bandyopadhyay; Jonathan Sussman; Kyung Jin Ahn; Kai Tan (2024). Processed CODEX Data (Seurat Objects) [Dataset]. http://doi.org/10.25452/figshare.plus.25127657.v1

Processed CODEX Data (Seurat Objects)

Explore at:
application/gzipAvailable download formats
Dataset updated
Apr 12, 2024
Dataset provided by
Figshare+
Authors
Shovik Bandyopadhyay; Jonathan Sussman; Kyung Jin Ahn; Kai Tan
License

CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically

Description

Seurat objects containing the raw and normalized data for:Normal bone marrow (NBM) atlas: contains all cells obtained through segmentation after filtering and QC. Includes coarse and fine level of annotations that were obtained through an iterative process of subclustering. Neighborhood analysis results are included as a metadata column. Additional Osteo-MSC and Fibro-MSC cells that were manually annotatedAML/NSM CODEX data: contains all cells after filtering for 3 diagnostic and 2 post-therapy AML samples as well as 3 negative staging marrow samples. Cell labels were derived through reciprocal principal component analysis (RPCA) reference mapping onto the normal bone marrow atlas. Neighborhood analysis was conducted separately for AML Diagnostic, AML Post-Therapy, and NSM samples. Neighborhoods were manually annotated for each set. The results of the neighborhood analysis were merged and included in the metadata of the Seurat object. All normalized data is stored in the Seurat assay object. Markers that were not included in normalization and downstream analysis are included with raw values as a metadata column. Full source code used to generate these objects can be found on GitHub: https://github.com/shovikb94/spatial-bonemarrow-atlas/tree/mainSee related materials in Collection at: https://doi.org/10.25452/figshare.plus.c.7174914

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