Data from: Reference transcriptomics of porcine peripheral immune cells created through bulk and single-cell RNA sequencing

This dataset contains files reconstructing single-cell data presented in 'Reference transcriptomics of porcine peripheral immune cells created through bulk and single-cell RNA sequencing' by Herrera-Uribe & Wiarda et al. 2021. Samples of peripheral blood mononuclear cells (PBMCs) were collected from seven pigs and processed for single-cell RNA sequencing (scRNA-seq) in order to provide a reference annotation of porcine immune cell transcriptomics at enhanced, single-cell resolution. Analysis of single-cell data allowed identification of 36 cell clusters that were further classified into 13 cell types, including monocytes, dendritic cells, B cells, antibody-secreting cells, numerous populations of T cells, NK cells, and erythrocytes. Files may be used to reconstruct the data as presented in the manuscript, allowing for individual query by other users. Scripts for original data analysis are available at https://github.com/USDA-FSEPRU/PorcinePBMCs_bulkRNAseq_scRNAseq. Raw data are available at https://www.ebi.ac.uk/ena/browser/view/PRJEB43826.

Funding for this dataset was also provided by NRSP8: National Animal Genome Research Program (https://www.nimss.org/projects/view/mrp/outline/18464).

• Resource Title: Herrera-Uribe & Wiarda et al. PBMCs - All Cells 10X Format.

  File Name: PBMC7_AllCells.zip

  Resource Description: Zipped folder containing PBMC counts matrix, gene names, and cell IDs. Files are as follows:

  • matrix of gene counts* (matrix.mtx.gx)
  • gene names (features.tsv.gz)
  • cell IDs (barcodes.tsv.gz)

  *The ‘raw’ count matrix is actually gene counts obtained following ambient RNA removal. During ambient RNA removal, we specified to calculate non-integer count estimations, so most gene counts are actually non-integer values in this matrix but should still be treated as raw/unnormalized data that requires further normalization/transformation.

  Data can be read into R using the function Read10X().




• Resource Title: Herrera-Uribe & Wiarda et al. PBMCs - All Cells Metadata.

  File Name: PBMC7_AllCells_meta.csv

  Resource Description: .csv file containing metadata for cells included in the final dataset. Metadata columns include:

  • nCount_RNA = the number of transcripts detected in a cell
  • nFeature_RNA = the number of genes detected in a cell
  • Loupe = cell barcodes; correspond to the cell IDs found in the .h5Seurat and 10X formatted objects for all cells
  • prcntMito = percent mitochondrial reads in a cell
  • Scrublet = doublet probability score assigned to a cell
  • seurat_clusters = cluster ID assigned to a cell
  • PaperIDs = sample ID for a cell
  • celltypes = cell type ID assigned to a cell
  
  

  • Resource Title: Herrera-Uribe & Wiarda et al. PBMCs - All Cells PCA Coordinates.

    File Name: PBMC7_AllCells_PCAcoord.csv

    Resource Description: .csv file containing first 100 PCA coordinates for cells.

  
  

  • Resource Title: Herrera-Uribe & Wiarda et al. PBMCs - All Cells t-SNE Coordinates.

    File Name: PBMC7_AllCells_tSNEcoord.csv

    Resource Description: .csv file containing t-SNE coordinates for all cells.

  
  

  • Resource Title: Herrera-Uribe & Wiarda et al. PBMCs - All Cells UMAP Coordinates.

    File Name: PBMC7_AllCells_UMAPcoord.csv

    Resource Description: .csv file containing UMAP coordinates for all cells.

  
  

  • Resource Title: Herrera-Uribe & Wiarda et al. PBMCs - CD4 T Cells t-SNE Coordinates.

    File Name: PBMC7_CD4only_tSNEcoord.csv

    Resource Description: .csv file containing t-SNE coordinates for only CD4 T cells (clusters 0, 3, 4, 28). A dataset of only CD4 T cells can be re-created from the PBMC7_AllCells.h5Seurat, and t-SNE coordinates used in publication can be re-assigned using this .csv file.

  
  

  • Resource Title: Herrera-Uribe & Wiarda et al. PBMCs - CD4 T Cells UMAP Coordinates.

    File Name: PBMC7_CD4only_UMAPcoord.csv

    Resource Description: .csv file containing UMAP coordinates for only CD4 T cells (clusters 0, 3, 4, 28). A dataset of only CD4 T cells can be re-created from the PBMC7_AllCells.h5Seurat, and UMAP coordinates used in publication can be re-assigned using this .csv file.

  
  

  • Resource Title: Herrera-Uribe & Wiarda et al. PBMCs - Gamma Delta T Cells UMAP Coordinates.

    File Name: PBMC7_GDonly_UMAPcoord.csv

    Resource Description: .csv file containing UMAP coordinates for only gamma delta T cells (clusters 6, 21, 24, 31). A dataset of only gamma delta T cells can be re-created from the PBMC7_AllCells.h5Seurat, and UMAP coordinates used in publication can be re-assigned using this .csv file.

  
  

  • Resource Title: Herrera-Uribe & Wiarda et al. PBMCs - Gamma Delta T Cells t-SNE Coordinates.

    File Name: PBMC7_GDonly_tSNEcoord.csv

    Resource Description: .csv file containing t-SNE coordinates for only gamma delta T cells (clusters 6, 21, 24, 31). A dataset of only gamma delta T cells can be re-created from the PBMC7_AllCells.h5Seurat, and t-SNE coordinates used in publication can be re-assigned using this .csv file.

  
  

  • Resource Title: Herrera-Uribe & Wiarda et al. PBMCs - Gene Annotation Information.

    File Name: UnfilteredGeneInfo.txt

    Resource Description: .txt file containing gene nomenclature information used to assign gene names in the dataset. 'Name' column corresponds to the name assigned to a feature in the dataset.

  
  

  • Resource Title: Herrera-Uribe & Wiarda et al. PBMCs - All Cells H5Seurat.

    File Name: PBMC7.tar

    Resource Description: .h5Seurat object of all cells in PBMC dataset. File needs to be untarred, then read into R using function LoadH5Seurat().