COVID-19 vaccination single cell datasets

The datasets presented here comprise the sequencing data featured in the research paper titled: "Multimodal single-cell datasets characterize antigen-specific CD8⁺ T cells across SARS-CoV-2 vaccination and infection": https://www.nature.com/articles/s41590-023-01608-9 Peripheral Blood Mononuclear Cell (PBMC) samples utilized for both CITE-seq and ASAP-seq were systematically collected at four distinct time intervals: Pre-vaccination (Day 0) Post-primary vaccination (Day 2 and Day 10. Seven days post-boost vaccination (Day 28). The count matrix folder contains count matrices for each experimental type, specifically CITE-seq, ASAP-seq, and ECCITE-seq. In addition, we have included the fully integrated, processed Seurat objects for downstream analysis. Details of the content within the count matrix folder are as follows: The RNA, ATAC, and TCR modality outputs were generated using the 10x Cellranger pipeline. HTO and ADT modalities were mapped with Alevin. Outlined below are the three processed single-cell datasets: PBMC_vaccine_CITE.rds: 3' RNA and surface proteins (173 TotalSeq-A antibodies) PBMC_vaccine_ASAP.rds: Chromatin accessibility and surface proteins (173 TotalSeq-A antibodies) PBMC_vaccine_ECCITE_TCR.rds: 5' RNA, surface proteins (137 TotalSeq-C antibodies), TCR and dextramer loaded with peptides of SARS-CoV-2 spike protein. antigen_module_genes.rds: This file contains the vaccine-induced gene sets. antigen_module_peaks.rds: This file contains the DE peaks specific for vaccine-induced cells. To map the scRNA-seq query dataset onto our CITE-seq reference: <pre><code>library(Seurat) PBMC_CITE &lt;- readRDS("/zenedo/PBMC_vaccine_CITE.rds") query_scRNA &lt;- readRDS("/home/xx/your_own_data.rds") anchors &lt;- FindTransferAnchors( reference = PBMC_CITE, query = query_scRNA, normalization.method = "SCT", k.anchor = 5, reference.reduction = "spca", dims = 1:50) query_scRNA &lt;- MapQuery( anchorset = anchors, query = query_scRNA, reference = PBMC_CITE, refdata = list( l1 = "celltypel1", l2 = "celltypel2", l3 = "celltypel3"), reference.reduction = "spca", reduction.model = "wnn.umap") </code></pre> To use the scATAC-seq data, please run the commands below to update the path of the fragment file for the object. <pre><code>Vaccine_ASAP &lt;- readRDS("PBMC_vaccine_ASAP.rds") # remove fragment file information Fragments(Vaccine_ASAP) &lt;- NULL # Update the path of the fragment file Fragments(Vaccine_ASAP) &lt;- CreateFragmentObject(path = "download/PBMC_vaccine_ASAP_fragments.tsv.gz", cells = Cells(Vaccine_ASAP))</code></pre>

本数据集收录于研究论文《多模态单细胞数据集表征新冠疫苗接种与感染后的抗原特异性CD8⁺T细胞（Multimodal single-cell datasets characterize antigen-specific CD8⁺ T cells across SARS-CoV-2 vaccination and infection）》，论文链接：https://www.nature.com/articles/s41590-023-01608-9。用于CITE-seq与ASAP-seq实验的外周血单个核细胞（Peripheral Blood Mononuclear Cell, PBMC）样本，在四个明确的时间节点完成系统采集：疫苗接种前（第0天）、初次疫苗接种后（第2天与第10天）、加强疫苗接种后7天（第28天）。计数矩阵文件夹包含各实验类型的计数矩阵，具体涵盖CITE-seq、ASAP-seq及ECCITE-seq三类实验。此外，本数据集还提供了经过完整整合与预处理的Seurat对象，可用于下游分析。计数矩阵文件夹内的内容详情如下：RNA、ATAC及TCR模态的输出通过10x Cellranger流程生成；HTO与ADT模态通过Alevin软件完成比对注释。本次提供的三个预处理单细胞数据集如下：1. PBMC_vaccine_CITE.rds：包含3'端RNA测序数据与表面蛋白谱（共173种TotalSeq-A抗体）；2. PBMC_vaccine_ASAP.rds：包含染色质开放状态测序数据与表面蛋白谱（共173种TotalSeq-A抗体）；3. PBMC_vaccine_ECCITE_TCR.rds：包含5'端RNA测序数据、表面蛋白谱（共137种TotalSeq-C抗体）、TCR受体测序数据及负载有新冠病毒刺突蛋白肽段的多聚体（dextramer）。辅助数据文件说明如下：- antigen_module_genes.rds：该文件包含疫苗诱导的基因集；- antigen_module_peaks.rds：该文件包含疫苗诱导细胞特异性的差异表达峰（DE peaks）。若需将单细胞RNA测序（scRNA-seq）查询数据集映射至本研究的CITE-seq参考数据集，请运行如下代码：
r
library(Seurat)
PBMC_CITE <- readRDS("/zenedo/PBMC_vaccine_CITE.rds")
query_scRNA <- readRDS("/home/xx/your_own_data.rds")
anchors <- FindTransferAnchors(
reference = PBMC_CITE,
query = query_scRNA,
normalization.method = "SCT",
k.anchor = 5,
reference.reduction = "spca",
dims = 1:50
)
query_scRNA <- MapQuery(
anchorset = anchors,
query = query_scRNA,
reference = PBMC_CITE,
refdata = list(
l1 = "celltypel1",
l2 = "celltypel2",
l3 = "celltypel3"
),
reference.reduction = "spca",
reduction.model = "wnn.umap"
)

若需使用单细胞ATAC测序（scATAC-seq）数据，请运行如下命令更新对象内的片段文件路径：
r
Vaccine_ASAP <- readRDS("PBMC_vaccine_ASAP.rds")
# 移除原有片段文件信息
Fragments(Vaccine_ASAP) <- NULL
# 更新片段文件路径
Fragments(Vaccine_ASAP) <- CreateFragmentObject(path = "download/PBMC_vaccine_ASAP_fragments.tsv.gz", cells = Cells(Vaccine_ASAP))