2 datasets found
  1. scvi-citeseq.h5ad

    • figshare.com
    hdf
    Updated Sep 1, 2021
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    Luke Zappia (2021). scvi-citeseq.h5ad [Dataset]. http://doi.org/10.6084/m9.figshare.16553751.v1
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    hdfAvailable download formats
    Dataset updated
    Sep 1, 2021
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Luke Zappia
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    H5AD file created by following the scvi-tools totalVI tutorial

  2. CITE-seq data from Staphylococcus aureus induce drug resistance in cancer T...

    • figshare.com
    application/gzip
    Updated Jan 25, 2024
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    Terkild Brink Buus; Chella Krishna Vadivel; Niels Ødum (2024). CITE-seq data from Staphylococcus aureus induce drug resistance in cancer T cells in Sézary Syndrome [Dataset]. http://doi.org/10.6084/m9.figshare.23649780.v1
    Explore at:
    application/gzipAvailable download formats
    Dataset updated
    Jan 25, 2024
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Terkild Brink Buus; Chella Krishna Vadivel; Niels Ødum
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    CITE-seq dataset of cells from a Sézary Syndrome patient cultured in the presence or absence of Romidepsin and/or S. aureus enterotoxins (SE) used in article:Chella Krishna Vadivel, Andreas Willerslev-Olsen, Martin Rich Javadi Namini, Ziao Zeng, Lang Yan, Maria Danielsen, Maria Gluud, Emil Marek Heymans Pallesen, Karolina Wojewoda, Amra Osmancevic, Signe Hedebo, Yun-Tsan Chang, Lise M. Lindahl, Sergei B. Koralov, Larisa J Geskin, Susan E Bates, Lars Iversen, Thomas Litman, Rikke Bech, Marion Wobser, Emmanuella Guenova, Maria R. Kamstrup, Niels Odum*, Terkild B. Buus*; Staphylococcus aureus induce drug resistance in cancer T cells in Sézary Syndrome. Blood 2024; blood.2023021671. DOI: https://doi.org/10.1182/blood.2023021671SS17.rds is contains R Data Serialization (RDS) file of a SingleCellExperiment (SCE) R object containing integrated single-cell CITE-seq data from four samples (PBS, Romidepsin, SE and Romidepsin+SE treatment) after 36 hours of in vitro culture.The column data (colData) of the SCE object contains the following information from each cell:treatment - whether cell was cultured in the presence (Romidepsin) or absence (DMSO) of Romidepsinstimulation - whether cell was cultured in the presence (SE) or absence (PBS) of S. aureus enterotoxins (SE)group - cell sample condition origin (a combination of stimulation and treatment columns)lane - whether cell was included in lane1 or lane2 of the two 10X Chromium lanes run in parallel from the same cell suspension poolsum - number of Unique Molecular Identifiers (UMIs) assigned to the celldetected - number of genes detected in the cellsubsets_Mito_percent - proportion of UMIs stemming from mitochondrial genessizeFactor - calculated sizeFactor for normalizationTRA_top5 - assignment of TCRalpha chain clonotype to one of the top5 clonotypes detected based on CDR3 amino acid sequenceTRB_top5 - assignment of TCRbeta chain clonotype to one of the top5 clonotypes detected based on CDR3 amino acid sequencecc_phase - inferred cell cycle phasecc_score_s - inferred cell cycle S-phase scorecc_score_G2M - inferred cell cycle G2M-phase scoreleiden_totalVI - leiden clustering assignment from lantent space of totalVI runcell_type - Cell type assignment of the cellSCE object contains three alternative experiment objects:ADT - Antibody derived tag (ADT) UMI counts from surface protein modalityVI_ADT - Antibody derived tag (ADT) UMI counts from surface protein modality denoised and normalized by totalVITF - Transcription factor activation scores (from DoRothEA) for each cell calculated using decoupleRSCE object contains three dimension reductions:PCA - principal component analysis calculated based on highly variable genestotalVI - latent space loadings from totalVI analysisumap - Uniform Manifold Approximation and Projection calculated based on latent space from totalVICode used in the analysis of this data is available on GitHub

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Click to copy link
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Luke Zappia (2021). scvi-citeseq.h5ad [Dataset]. http://doi.org/10.6084/m9.figshare.16553751.v1
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scvi-citeseq.h5ad

Explore at:
hdfAvailable download formats
Dataset updated
Sep 1, 2021
Dataset provided by
Figsharehttp://figshare.com/
Authors
Luke Zappia
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

H5AD file created by following the scvi-tools totalVI tutorial

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