Single-cell landscape of innate and acquired drug resistance in acute myeloid leukemia: scRNA-seq and CyTOF processed datasets

<p><strong>This data was generated as part of the Tumor Profiler study. If you use it in your research, please cite:</strong></p> <p>Wegmann, R., Bonilla, X., Casanova, R.&nbsp;<em>et al.</em>&nbsp;Single-cell landscape of innate and acquired drug resistance in acute myeloid leukemia.&nbsp;<em>Nat Commun</em>&nbsp;15, 9402 (2024). https://doi.org/10.1038/s41467-024-53535-4</p> <p><strong>Derived data - scRNA-seq</strong></p> <p>This is an R data set (.RDS) containing a SingleCellExperiment object with the following slots:</p> <div> <ul> <li>Assays: <ul> <li>counts: raw counts</li> </ul> </li> </ul> </div> <div> <ul> <li>colData: Cell-level metadata <ul> <li>&nbsp;barcodes: The cell barcode</li> <li>&nbsp;fractionMT: Fraction mitochondrial genes per cell</li> <li>&nbsp;n_umi: Total number of UMIs per cell</li> <li>&nbsp;n_gene: Total number of genes per cell</li> <li>&nbsp;log_umi: log10 total number of UMIs per cell</li> <li>&nbsp;g2m_score: Cell cycle phase score for G2M</li> <li>s_score: Cell cycle phase score for S</li> <li>cycle_phase: predicted cell cycle phase</li> <li>celltype_major_full_ct_name: Major cell type full name</li> <li>celltype_major: Major cell type short name</li> <li>celltype_final_full_ct_name: Cell subtype full name</li> <li>celltype_final: Cell subtype short name&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;</li> <li>sample_id&nbsp;&nbsp;</li> </ul> </li> </ul> </div> <div> <ul> <li>rowData: Gene-level metadata <ul> <li>gene_ids</li> <li>gene_names</li> </ul> </li> </ul> </div> <p><strong>Derived data - CyTOF</strong></p> <p>This is an R data set (.RDS) containing a SingleCellExperiment object with the following slots:</p> <ul> <li>Assays:<br> <ul> <li>counts_raw: signal intensity based on CyTOF dual counts</li> <li>exprs_raw: arcsinh transformed raw counts (cofactor 5)</li> <li>counts: batch corrected raw counts (linear scaling based on a quantile)</li> <li>exprs: arcsin transformed counts (cofactor 5)</li> <li>scaled: 0-1 normalized exprs (clipped to the 99.95th percentile)</li> </ul> </li> <li>colData (cell metadata) <ul> <li>bc_id: barcode of the sample during staining &nbsp;</li> <li>run: CyTOF experiment batch, named after the first sample of the batch</li> <li>type: Sample type (blood or bone marrow)</li> <li>sample_id: TuPro sample ID</li> <li>pred_id: Predicted cell type [char]</li> <li>pred_n: Predicted cell type [integer]</li> </ul> </li> <li>rowData (marker metadata) <ul> <li>channel_name: Name and isotopic mass of the metal ion corresponding to this marker</li> <li>marker_name: Protein name</li> <li>channel_group, channel_group_integer: Biological processes the channel identifies, e.g. specific cell type, signalling, cell death</li> <li>tsne_channel: Logical - use this channel for dimensionality reduction?</li> <li>channel_order: Define the order of channels for plotting</li> <li>cluster_channel: Logical - use this channel for clustering?</li> </ul> </li> </ul>