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). Resources in this dataset:Resource Title: Herrera-Uribe & Wiarda et al. PBMCs - All Cells 10X Format. File Name: PBMC7_AllCells.zipResource 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.csvResource 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 cellResource Title: Herrera-Uribe & Wiarda et al. PBMCs - All Cells PCA Coordinates. File Name: PBMC7_AllCells_PCAcoord.csvResource 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.csvResource 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.csvResource 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.csvResource 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.csvResource 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.csvResource 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.csvResource 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.txtResource 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.tarResource Description: .h5Seurat object of all cells in PBMC dataset. File needs to be untarred, then read into R using function LoadH5Seurat().

本数据集收录了由Herrera-Uribe与Wiarda等人在2021年发表的《通过群体与单细胞RNA测序构建猪外周免疫细胞参考转录组学》一文中呈现的单细胞数据重建文件。该研究采集了七头猪的周围血液单核细胞（PBMCs）样本，并对其进行单细胞RNA测序（scRNA-seq）处理，旨在提供猪免疫细胞转录组学在增强的单细胞分辨率下的参考注释。单细胞数据分析揭示了36个细胞簇，这些细胞簇进一步被分类为13种细胞类型，包括单核细胞、树突状细胞、B细胞、抗体分泌细胞、多种T细胞群体、自然杀伤细胞和红细胞。用户可以利用这些文件重建论文中展示的数据，并允许其他用户进行个体查询。原始数据分析脚本可在https://github.com/USDA-FSEPRU/PorcinePBMCs_bulkRNAseq_scRNAseq上获取。原始数据可在https://www.ebi.ac.uk/ena/browser/view/PRJEB43826上获取。本数据集的资助亦由NRSP8：国家动物基因组研究计划（https://www.nimss.org/projects/view/mrp/outline/18464）提供。数据集包含以下资源：

资源标题：Herrera-Uribe & Wiarda等. PBMCs - 所有细胞10X格式。文件名：PBMC7_AllCells.zip
资源描述：包含PBMC计数矩阵、基因名称和细胞ID的压缩文件夹。文件如下：

* 基因计数矩阵（matrix.mtx.gx）
* 基因名称（features.tsv.gz）
* 细胞ID（barcodes.tsv.gz）

* 实际上的‘原始’计数矩阵是去除环境RNA后获得的基因计数。在去除环境RNA的过程中，我们指定计算非整数计数估计值，因此此矩阵中的大多数基因计数实际上是非整数值，但仍应被视为需要进一步归一化/转换的原始/未归一化数据。
数据可通过R中的Read10X()函数读取。

资源标题：Herrera-Uribe & Wiarda等. PBMCs - 所有细胞元数据。文件名：PBMC7_AllCells_meta.csv
资源描述：包含最终数据集中包含的细胞元数据的.csv文件。元数据列包括：

nCount_RNA = 细胞中检测到的转录本数量
nFeature_RNA = 细胞中检测到的基因数量
Loupe = 细胞条形码；对应于所有细胞的.h5Seurat和10X格式对象中的细胞ID
prcntMito = 细胞中线粒体读数的百分比
Scrublet = 分配给细胞的倍体概率得分
seurat_clusters = 分配给细胞的簇ID
PaperIDs = 细胞的样本ID
celltypes = 分配给细胞的细胞类型ID

资源标题：Herrera-Uribe & Wiarda等. PBMCs - 所有细胞PCA坐标。文件名：PBMC7_AllCells_PCAcoord.csv
资源描述：包含细胞前100个PCA坐标的.csv文件。

资源标题：Herrera-Uribe & Wiarda等. PBMCs - 所有细胞t-SNE坐标。文件名：PBMC7_AllCells_tSNEcoord.csv
资源描述：包含所有细胞t-SNE坐标的.csv文件。

资源标题：Herrera-Uribe & Wiarda等. PBMCs - 所有细胞UMAP坐标。文件名：PBMC7_AllCells_UMAPcoord.csv
资源描述：包含所有细胞UMAP坐标的.csv文件。

资源标题：Herrera-Uribe & Wiarda等. PBMCs - CD4 T细胞t-SNE坐标。文件名：PBMC7_CD4only_tSNEcoord.csv
资源描述：包含仅CD4 T细胞（簇0、3、4、28）的t-SNE坐标的.csv文件。可以从PBMC7_AllCells.h5Seurat重建仅CD4 T细胞的数据集，并使用此.csv文件重新分配论文中使用的t-SNE坐标。

资源标题：Herrera-Uribe & Wiarda等. PBMCs - CD4 T细胞UMAP坐标。文件名：PBMC7_CD4only_UMAPcoord.csv
资源描述：包含仅CD4 T细胞（簇0、3、4、28）的UMAP坐标的.csv文件。可以从PBMC7_AllCells.h5Seurat重建仅CD4 T细胞的数据集，并使用此.csv文件重新分配论文中使用的UMAP坐标。

资源标题：Herrera-Uribe & Wiarda等. PBMCs - Gamma Delta T细胞UMAP坐标。文件名：PBMC7_GDonly_UMAPcoord.csv
资源描述：包含仅gamma delta T细胞（簇6、21、24、31）的UMAP坐标的.csv文件。可以从PBMC7_AllCells.h5Seurat重建仅gamma delta T细胞的数据集，并使用此.csv文件重新分配论文中使用的UMAP坐标。

资源标题：Herrera-Uribe & Wiarda等. PBMCs - Gamma Delta T细胞t-SNE坐标。文件名：PBMC7_GDonly_tSNEcoord.csv
资源描述：包含仅gamma delta T细胞（簇6、21、24、31）的t-SNE坐标的.csv文件。可以从PBMC7_AllCells.h5Seurat重建仅gamma delta T细胞的数据集，并使用此.csv文件重新分配论文中使用的t-SNE坐标。

资源标题：Herrera-Uribe & Wiarda等. PBMCs - 基因注释信息。文件名：UnfilteredGeneInfo.txt
资源描述：包含用于在数据集中分配基因名称的基因命名信息的.txt文件。'Name'列对应于数据集中特征分配的名称。

资源标题：Herrera-Uribe & Wiarda等. PBMCs - 所有细胞H5Seurat。文件名：PBMC7.tar
资源描述：包含PBMC数据集中所有细胞的.h5Seurat对象。需要解压文件，然后使用LoadH5Seurat()函数将其读取到R中。