Objectives: Recent advancements in single-cell RNA sequencing (scRNA-seq) have revolutionized the study of cellular heterogeneity, particularly within the hematological system. However, accurately annotating cell types remains challenging due to the complexity of immune cells. To address this challenge, we develop a PAN-blood single-cell Data Annotator (scPANDA), which leverages a comprehensive 10-million-cell atlas to provide precise cell type annotation.
Methods: The atlas, constructed from data collected in 16 studies, incorporated rigorous quality control, preprocessing, and integration steps to ensure a high-quality reference for annotation. scPANDA utilizes a three-layer inference approach, progressively refining cell types from broad compartments to specific clusters. Iterative clustering and harmonization processes were employed to maintain cell type purity throughout the analysis. Furthermore, the performance of scPANDA was evaluated in three external datasets.
Results: The atlas was structured hierarchically, consisting of 16 compartments, 54 classes, 4,460 low-level clusters (pd_cc_cl_tfs), and 611 high-level clusters (pmid_cts). Robust performance of the tool was demonstrated in annotating diverse immune scRNA-seq datasets, analyzing immune-tumor coexisting clusters in renal cell carcinoma, and identifying conserved cell clusters across species.
Conclusions: scPANDA exemplifies effective reference mapping with a large-scale atlas, enhancing the accuracy and reliability of blood cell type identification.
目的: 单细胞测序的最新进展彻底改变了细胞异质性的研究，特别是在血液系统中尤为明显。由于免疫细胞的复杂性，准确注释细胞类型仍然具有极大挑战。为了应对这一挑战，我们开发了泛血液单细胞数据注释工具（PAN-blood single-cell Data Annotator，scPANDA），利用一个全面的1000万细胞图谱来实现细胞类型的精确注释。方法: 我们搜集了来自16项研究的单细胞转录组数据，进行了严格的质量控制、预处理和整合以确保质量。scPANDA采用三层推断方法，逐步将细胞类型从宽泛的分类细化到特定细胞簇。在整个分析过程中，采用迭代聚类和整合来保持细胞类型的纯度。我们进一步在三个外部数据集中评估了scPANDA的性能。结果: 该图谱的分层结构由16个大类、54个小类、4460个低级簇（pd_cc_cl_tfs）和611个高级簇（pmid_cts）构组。该工具在注释不同的免疫数据集、分析癌症中免疫-肿瘤共存簇以及鉴定不同物种的保守细胞簇方面的稳健表现体现了其有效性。结论: scPANDA通过大规模细胞图谱展示了高效的参考映射方法，提升了血液细胞类型识别的准确性和可靠性。.
Keywords: blood cells; cell type annotation; immunology; single-cell RNA sequencing; single-cell atlas.